for Journals by Title or ISSN
for Articles by Keywords

Publisher: Elsevier   (Total: 3043 journals)

 A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

        1 2 3 4 5 6 7 8 | Last   [Sort by number of followers]   [Restore default list]

Showing 1 - 200 of 3043 Journals sorted alphabetically
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 22, SJR: 1.402, h-index: 51)
Academic Radiology     Hybrid Journal   (Followers: 21, SJR: 1.008, h-index: 75)
Accident Analysis & Prevention     Partially Free   (Followers: 84, SJR: 1.109, h-index: 94)
Accounting Forum     Hybrid Journal   (Followers: 25, SJR: 0.612, h-index: 27)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 30, SJR: 2.515, h-index: 90)
Achievements in the Life Sciences     Open Access   (Followers: 4)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 5, SJR: 0.338, h-index: 19)
Acta Astronautica     Hybrid Journal   (Followers: 351, SJR: 0.726, h-index: 43)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Biomaterialia     Hybrid Journal   (Followers: 25, SJR: 2.02, h-index: 104)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 1)
Acta de Investigación Psicológica     Open Access   (Followers: 2)
Acta Ecologica Sinica     Open Access   (Followers: 8, SJR: 0.172, h-index: 29)
Acta Haematologica Polonica     Free   (SJR: 0.123, h-index: 8)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.604, h-index: 38)
Acta Materialia     Hybrid Journal   (Followers: 238, SJR: 3.683, h-index: 202)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.615, h-index: 21)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.442, h-index: 21)
Acta Oecologica     Hybrid Journal   (Followers: 10, SJR: 0.915, h-index: 53)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription   (Followers: 1)
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, SJR: 0.311, h-index: 16)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 2)
Acta Poética     Open Access   (Followers: 4)
Acta Psychologica     Hybrid Journal   (Followers: 23, SJR: 1.365, h-index: 73)
Acta Sociológica     Open Access  
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.059, h-index: 77)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 4)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 3)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 4, SJR: 0.383, h-index: 19)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 2)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 5, SJR: 0.141, h-index: 3)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 4, SJR: 0.112, h-index: 2)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 4)
Acute Pain     Full-text available via subscription   (Followers: 13)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.967, h-index: 57)
Addictive Behaviors     Hybrid Journal   (Followers: 15, SJR: 1.514, h-index: 92)
Addictive Behaviors Reports     Open Access   (Followers: 5)
Additive Manufacturing     Hybrid Journal   (Followers: 7, SJR: 1.039, h-index: 5)
Additives for Polymers     Full-text available via subscription   (Followers: 21)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 135, SJR: 5.2, h-index: 222)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.265, h-index: 53)
Advanced Powder Technology     Hybrid Journal   (Followers: 17, SJR: 0.739, h-index: 33)
Advances in Accounting     Hybrid Journal   (Followers: 9, SJR: 0.299, h-index: 15)
Advances in Agronomy     Full-text available via subscription   (Followers: 15, SJR: 2.071, h-index: 82)
Advances in Anesthesia     Full-text available via subscription   (Followers: 25, SJR: 0.169, h-index: 4)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 3)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 6, SJR: 1.054, h-index: 35)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 0.801, h-index: 26)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 22, SJR: 1.286, h-index: 49)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 16, SJR: 3.31, h-index: 42)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.277, h-index: 43)
Advances in Botanical Research     Full-text available via subscription   (Followers: 3, SJR: 0.619, h-index: 48)
Advances in Cancer Research     Full-text available via subscription   (Followers: 25, SJR: 2.215, h-index: 78)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, SJR: 0.9, h-index: 30)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 2.139, h-index: 42)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 12)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 26, SJR: 0.183, h-index: 23)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.665, h-index: 29)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 9, SJR: 1.268, h-index: 45)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 29, SJR: 0.938, h-index: 33)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 18, SJR: 2.314, h-index: 130)
Advances in Computers     Full-text available via subscription   (Followers: 16, SJR: 0.223, h-index: 22)
Advances in Dermatology     Full-text available via subscription   (Followers: 12)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 11)
Advances in Digestive Medicine     Open Access   (Followers: 6)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 22)
Advances in Ecological Research     Full-text available via subscription   (Followers: 41, SJR: 3.25, h-index: 43)
Advances in Engineering Software     Hybrid Journal   (Followers: 25, SJR: 0.486, h-index: 10)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 41, SJR: 5.465, h-index: 64)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 3)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 50, SJR: 0.674, h-index: 38)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Genetics     Full-text available via subscription   (Followers: 15, SJR: 2.558, h-index: 54)
Advances in Genome Biology     Full-text available via subscription   (Followers: 11)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 2.325, h-index: 20)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 22, SJR: 0.906, h-index: 24)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 9, SJR: 0.497, h-index: 31)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.396, h-index: 27)
Advances in Immunology     Full-text available via subscription   (Followers: 35, SJR: 4.152, h-index: 85)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 9, SJR: 1.132, h-index: 42)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 3, SJR: 1.274, h-index: 27)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 6)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.764, h-index: 15)
Advances in Lipobiology     Full-text available via subscription   (Followers: 2)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Marine Biology     Full-text available via subscription   (Followers: 16, SJR: 1.645, h-index: 45)
Advances in Mathematics     Full-text available via subscription   (Followers: 10, SJR: 3.261, h-index: 65)
Advances in Medical Sciences     Hybrid Journal   (Followers: 6, SJR: 0.489, h-index: 25)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.44, h-index: 51)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 22)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 10)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.324, h-index: 8)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 4)
Advances in Oncobiology     Full-text available via subscription   (Followers: 3)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 15, SJR: 2.885, h-index: 45)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.148, h-index: 11)
Advances in Parasitology     Full-text available via subscription   (Followers: 7, SJR: 2.37, h-index: 73)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.4, h-index: 28)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 13)
Advances in Pharmacology     Full-text available via subscription   (Followers: 15, SJR: 1.718, h-index: 58)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.384, h-index: 26)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.248, h-index: 11)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 8)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 17)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 20, SJR: 1.5, h-index: 62)
Advances in Psychology     Full-text available via subscription   (Followers: 61)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 5, SJR: 0.478, h-index: 32)
Advances in Radiation Oncology     Open Access  
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 3, SJR: 0.1, h-index: 2)
Advances in Space Research     Full-text available via subscription   (Followers: 353, SJR: 0.606, h-index: 65)
Advances in Structural Biology     Full-text available via subscription   (Followers: 8)
Advances in Surgery     Full-text available via subscription   (Followers: 7, SJR: 0.823, h-index: 27)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 30, SJR: 1.321, h-index: 56)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 17)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 13)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 1.878, h-index: 68)
Advances in Water Resources     Hybrid Journal   (Followers: 43, SJR: 2.408, h-index: 94)
Aeolian Research     Hybrid Journal   (Followers: 5, SJR: 0.973, h-index: 22)
Aerospace Science and Technology     Hybrid Journal   (Followers: 325, SJR: 0.816, h-index: 49)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.318, h-index: 36)
African J. of Emergency Medicine     Open Access   (Followers: 5, SJR: 0.344, h-index: 6)
Ageing Research Reviews     Hybrid Journal   (Followers: 8, SJR: 3.289, h-index: 78)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 405, SJR: 1.385, h-index: 72)
Agri Gene     Hybrid Journal  
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 15, SJR: 2.18, h-index: 116)
Agricultural Systems     Hybrid Journal   (Followers: 30, SJR: 1.275, h-index: 74)
Agricultural Water Management     Hybrid Journal   (Followers: 39, SJR: 1.546, h-index: 79)
Agriculture and Agricultural Science Procedia     Open Access  
Agriculture and Natural Resources     Open Access   (Followers: 1)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 54, SJR: 1.879, h-index: 120)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.434, h-index: 14)
Air Medical J.     Hybrid Journal   (Followers: 5, SJR: 0.234, h-index: 18)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.285, h-index: 3)
Alcohol     Hybrid Journal   (Followers: 10, SJR: 0.922, h-index: 66)
Alcoholism and Drug Addiction     Open Access   (Followers: 8)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.436, h-index: 12)
Alexandria J. of Medicine     Open Access  
Algal Research     Partially Free   (Followers: 8, SJR: 2.05, h-index: 20)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 3)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.46, h-index: 29)
Allergology Intl.     Open Access   (Followers: 4, SJR: 0.776, h-index: 35)
Alpha Omegan     Full-text available via subscription   (SJR: 0.121, h-index: 9)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 8, SJR: 0.158, h-index: 9)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 48, SJR: 4.289, h-index: 64)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 6)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 5)
American Heart J.     Hybrid Journal   (Followers: 49, SJR: 3.157, h-index: 153)
American J. of Cardiology     Hybrid Journal   (Followers: 47, SJR: 2.063, h-index: 186)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 39, SJR: 0.574, h-index: 65)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 8, SJR: 1.091, h-index: 45)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 15, SJR: 1.653, h-index: 93)
American J. of Human Genetics     Hybrid Journal   (Followers: 31, SJR: 8.769, h-index: 256)
American J. of Infection Control     Hybrid Journal   (Followers: 25, SJR: 1.259, h-index: 81)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 32, SJR: 2.313, h-index: 172)
American J. of Medicine     Hybrid Journal   (Followers: 45, SJR: 2.023, h-index: 189)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 235, SJR: 2.255, h-index: 171)
American J. of Ophthalmology     Hybrid Journal   (Followers: 57, SJR: 2.803, h-index: 148)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 5)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.249, h-index: 88)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, h-index: 45)
American J. of Pathology     Hybrid Journal   (Followers: 26, SJR: 2.653, h-index: 228)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 22, SJR: 2.764, h-index: 154)
American J. of Surgery     Hybrid Journal   (Followers: 34, SJR: 1.286, h-index: 125)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.653, h-index: 70)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 5)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.066, h-index: 51)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 57, SJR: 0.124, h-index: 9)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 11)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 2, SJR: 0.209, h-index: 27)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription   (SJR: 0.104, h-index: 3)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4, SJR: 2.577, h-index: 7)
Analytica Chimica Acta     Hybrid Journal   (Followers: 37, SJR: 1.548, h-index: 152)
Analytical Biochemistry     Hybrid Journal   (Followers: 167, SJR: 0.725, h-index: 154)
Analytical Chemistry Research     Open Access   (Followers: 8, SJR: 0.18, h-index: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 11)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 1)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 22, SJR: 0.421, h-index: 40)
Angiología     Full-text available via subscription   (SJR: 0.124, h-index: 9)
Angiologia e Cirurgia Vascular     Open Access  
Animal Behaviour     Hybrid Journal   (Followers: 161, SJR: 1.907, h-index: 126)
Animal Feed Science and Technology     Hybrid Journal   (Followers: 5, SJR: 1.151, h-index: 83)
Animal Reproduction Science     Hybrid Journal   (Followers: 5, SJR: 0.711, h-index: 78)
Annales d'Endocrinologie     Full-text available via subscription   (Followers: 1, SJR: 0.394, h-index: 30)
Annales d'Urologie     Full-text available via subscription  
Annales de Cardiologie et d'Angéiologie     Full-text available via subscription   (SJR: 0.177, h-index: 13)
Annales de Chirurgie de la Main et du Membre Supérieur     Full-text available via subscription  
Annales de Chirurgie Plastique Esthétique     Full-text available via subscription   (Followers: 2, SJR: 0.354, h-index: 22)
Annales de Chirurgie Vasculaire     Full-text available via subscription   (Followers: 1)

        1 2 3 4 5 6 7 8 | Last   [Sort by number of followers]   [Restore default list]

Journal Cover Agricultural Systems
  [SJR: 1.275]   [H-I: 74]   [30 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0308-521X
   Published by Elsevier Homepage  [3043 journals]
  • Yield gaps in Dutch arable farming systems: Analysis at crop and crop
           rotation level
    • Authors: João Vasco Silva; Pytrik Reidsma; Alice G. Laborte; Martin K. van Ittersum
      Pages: 223 - 241
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): João Vasco Silva, Pytrik Reidsma, Martin K. van Ittersum
      Arable farming systems in the Netherlands are characterized by crop rotations in which potato, sugar beet, spring onion, winter wheat and spring barley are the most important crops. The objectives of this study were to decompose crop yield gaps within such rotations into efficiency, resource and technology yield gaps and to explain those yield gaps based on observed cropping frequencies and alternative farmers' objectives. Data from specialized Dutch arable farms between 2008 and 2012 were used. Production frontiers and efficiency yield gaps were estimated using the stochastic frontier framework. The resource yield gap was quantified through the estimation of highest farmers' yields (YHF, average across farms with actual yields above the 90th percentile). Crop model simulations and variety trials were compiled to assess climatic potential yields (Yp) and technology yield gaps. The contribution of crop area shares and farmers' objectives to actual yields were assessed using regression analysis and based on five different farm level indicators (N production, energy production, gross margin, nitrogen-use efficiency and labour use), respectively. The average yield gap per crop (as percentage of Yp which is given in parentheses) was: 29.2% (of 72.6t ha−1) for ware potato, 39.7% (of 71.6t ha−1) for starch potato, 26.4% (of 107.1t ha−1) for sugar beet, 32.3% (of 88.3t ha−1) for spring onion, 25.2% (of 12.3t ha−1) for winter wheat and 37.5% (of 10.4t ha−1) for spring barley. The efficiency yield gap ranged between 6.6% (starch potato) and 18.1% (spring onion) of Yp. The resource yield gap was lower than 10% of Yp for all the crops and the technology yield gap ranged between 7.1% (ware potato) and 30.7% of Yp (starch potato). There were statistically significant effects of potato (positive quadratic) and onion (positive) area shares on ware potato, sugar beet and winter wheat yields, of sugar beet area share (positive quadratic) on winter wheat yield and of cereal area share (negative) on sugar beet and winter wheat yields. Farmers' objectives explain part of the variability observed in crop yields which were 7–24%, 13–24% and 12–32% lower than YHF, respectively, for gross margin maximising, labour minimising and N use efficiency maximising farms. In addition, there was a significant positive relationship between gross margin and the yield of ware potato, sugar beet and winter wheat. By contrast, no significant relationships were found between crop yields and NUE or labour use. We conclude that most of the yield gap is explained by the efficiency yield gap for ware potato and spring onion and by both the efficiency and technology yield gaps for sugar beet and cereals. The resource yield gap explains most of the yield gap of seed potato, and the technology yield gap of starch potato. The results regarding the effects of cropping frequency and crop rotations to crop yields are not very conclusive which suggest that agronomic principles become less evident at ‘systems level’ given the number of interacting factors at crop rotation level. Finally, although N and energy production are lower for gross margin maximising farms, most crop yields are not significantly different between farms with the highest N and energy production compared to farms performing best on economic (gross margin) objectives.

      PubDate: 2017-10-08T18:55:37Z
      DOI: 10.1016/j.eja.2016.06.017
      Issue No: Vol. 82 (2017)
  • Identification of production challenges and benefits using value chain
           mapping of egg food systems in Nairobi, Kenya
    • Authors: Joshua Orungo Onono; Pablo Alarcon; Maurice Karani; Patrick Muinde; James Miser Akoko; Carron Maud; Eric M. Fevre; Barbara Häsler; Jonathan Rushton
      Pages: 1 - 8
      Abstract: Publication date: January 2018
      Source:Agricultural Systems, Volume 159
      Author(s): Joshua Orungo Onono, Pablo Alarcon, Maurice Karani, Patrick Muinde, James Miser Akoko, Carron Maud, Eric M. Fevre, Barbara Häsler, Jonathan Rushton
      Commercial layer and indigenous chicken farming in Nairobi and associated activities in the egg value chains are a source of livelihood for urban families. A value chain mapping framework was used to describe types of inputs and outputs from chicken farms, challenges faced by producers and their disease control strategies. Commercial layer farms were defined as farms keeping exotic breeds of chicken, whereas indigenous chicken farms kept different cross breeds of indigenous chicken. Four focus group discussions were held with producers of these chickens in peri-urban area: Dagoretti, and one informal settlement: Kibera. Qualitative data were collected on interactions between farmers, sources of farm inputs and buyers of poultry products, simple ranking of production challenges, farmers' perception on diseases affecting chicken and strategies for management of sick chicken and waste products. Value chain profiles were drawn showing sources of inputs and channels for distribution of chicken products. Production challenges and chicken disease management strategies were presented as qualitative summaries. Commercial layer farms in Dagoretti kept an average of 250 chickens (range 50–500); while flock sizes in Kibera were 12 chickens (range 5–20). Farms keeping indigenous chicken had an average of 23 chickens (range 8–40) in Dagoretti, and 10 chickens (range 5–16) in Kibera. Commercial layer farms in Dagoretti obtained chicks from distributors of commercial hatcheries, but farms in Kibera obtained chicks from hawkers who in turn sourced them from distributors of commercial hatcheries. Indigenous chicken farms from Dagoretti relied on natural hatching of fertilised eggs, but indigenous chicken farms in Kibera obtained chicks from their social connection with communities living in rural areas. Outlets for eggs from commercial layer farms included local shops, brokers, restaurants and hawkers, while eggs from indigenous chicken farms were sold to neighbours and restaurants. Sieved chicken manure from Dagoretti area was fed to dairy cattle; whereas non-sieved manure was used as fertilizer on crops. Production challenges included poor feed quality, lack of space for expansion, insecurity, occurrence of diseases and lack of sources of information on chicken management. In Kibera, sick and dead chickens were slaughtered and consumed by households; this practice was not reported in Dagoretti. The chicken layer systems contribute to food security of urban households, yet they have vulnerabilities and deficiencies with regard to disease management and food safety that need to be addressed with support on research and extension.

      PubDate: 2017-10-13T19:09:21Z
      DOI: 10.1016/j.agsy.2017.10.001
      Issue No: Vol. 159 (2017)
  • Assessment of grazing management on farm greenhouse gas intensity of beef
           production systems in the Canadian Prairies using life cycle assessment
    • Authors: Aklilu W. Alemu; Henry Janzen; Shannan Little; Xiying Hao; Donald J. Thompson; Vern Baron; Alan Iwaasa; Karen A. Beauchemin; Roland Kröbel
      Pages: 1 - 13
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): Aklilu W. Alemu, Henry Janzen, Shannan Little, Xiying Hao, Donald J. Thompson, Vern Baron, Alan Iwaasa, Karen A. Beauchemin, Roland Kröbel
      Grazing is a common practice in the beef cattle industry and is an integral component of pasture and rangeland management. The objective of this study was to evaluate impacts of grazing management scenarios on greenhouse gas (GHG) intensity [kg carbon dioxide equivalents (CO2e)kg−1 beef] at the farm-gate for beef production systems in western Canada using life cycle assessment. A life cycle assessment over an 8-year period was conducted on a hypothetical but typical beef farm that managed 120 cows, 4 bulls, and their progeny. Calves were backgrounded (raised) on rangeland and market cattle were finished on grain for an average of 134±11d. Four grazing management scenarios were examined: i) light continuous grazing (LC) for all cattle, ii) heavy continuous grazing (HC) for all cattle, iii) light continuous grazing for cow-calf pairs and moderate rotational grazing for backgrounded cattle (LCMR), and iv) heavy continuous grazing for cow-calf pairs and moderate rotational grazing for backgrounded cattle (HCMR). Greenhouse gas emissions from various sources within the farm were estimated using the whole-farm model, Holos. Soil organic carbon (C) change due to each grazing management scenario was estimated using the Introductory Carbon Balance Model. Primary model inputs came from short- and long-term grazing management studies. Greenhouse gas intensity of beef varied among grazing management scenarios, ranging from 14.5–16.0kgCO2ekg−1 live weight and 24.1–26.6kgCO2ekg−1 carcass weight. Greenhouse gas intensity decreased with increasing stocking rate: that of HC grazing management was 9.2% lower than that of LC treatment (14.5 vs 16.0kgCO2ekg−1 live weight, respectively). Greenhouse gas intensity was similar (<3%) between LC and LCMR or between HC and HCMR, indicating that the use of moderate rotational grazing for the backgrounding operation in LCMR and HCMR had no effect on overall intensity estimates. However, LCMR management had 7% higher GHG intensity than HCMR (15.6 vs 14.6kgCO2ekg−1 live weight, respectively). Average farm production efficiency (kg beef per unit land area) was 17–25% higher for the HC and HCMR grazing management scenarios than the LC and LCMR scenarios. Regardless of grazing management, methane emission from enteric fermentation was the major source of emissions (67–68% of total), followed by nitrous oxide (14–16% of total) from manure management. The rate of soil C sequestration ranged from 0.01MgCha−1 yr−1 for rangeland under HC to 0.46MgCha−1 yr−1 for a triticale field used for swath grazing. When soil C sequestration was included in the total emission analysis, GHG intensity estimates decreased by 12–25%, and there was no difference in intensity estimates among the scenarios. The largest reduction in GHG intensity arising from soil C sequestration was observed for LC (22%) and LCMR (25%) because they sequestered more C than HC and HCMR. Overall, results of our study indicated that grazing management impacted GHG intensity of beef production by influencing diet quality, animal performance and soil C change. It also emphasizes the importance of accounting for all emission sources and sinks within a beef production system when estimating its environmental impacts.

      PubDate: 2017-08-28T02:14:18Z
      DOI: 10.1016/j.agsy.2017.08.003
      Issue No: Vol. 158 (2017)
  • Productivity of a building-integrated roof top greenhouse in a
           Mediterranean climate
    • Authors: J.I. Montero; E. Baeza; E. Heuvelink; J. Rieradevall; P. Muñoz; M. Ercilla; C. Stanghellini
      Pages: 14 - 22
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): J.I. Montero, E. Baeza, E. Heuvelink, J. Rieradevall, P. Muñoz, M. Ercilla, C. Stanghellini
      Urban Agriculture (UA) is an emerging field of agricultural production aimed to improve food security and the resilience of cities and to improve the environmental, social, and economic sustainability of urban areas. One of the options of UA are roof top greenhouses (RTGs), which are greenhouses built on the roof of a building, typically fitted with soilless culture systems. Further benefits can be achieved if the greenhouse and building are integrated, so that they exchange and optimise energy, water and CO2 flows. Integration is possible if the RTG and the building can exchange air and can collect rain water or use properly treated grey water for irrigation. Such type of integrated RTG is referred to as i-RTG. Both the environmental profile and the social value of i-RTGs have been studied, but information on their productivity is rather scarce. As the economic viability of i-RTGs is given by the value of all services provided, including the yield, the productivity of such systems needs to be maximised. This study attempts this, through the analysis (and discussion) of an i-RTG built in a Mediterranean climate (Barcelona area, Spain), producing beef type tomatoes (“Coeur de boeuf” cultivar). The experimental study showed that the i-RTG had poor light transmission. As a consequence, yield was low and the radiation use efficiency (RUE), referred to the outside radiation, was lower than in standard production (unheated greenhouses) in the same region. Nevertheless, RUE referred to the radiation above crop canopy, was similar in the i-RTG and standard greenhouses. Compared to conventional greenhouses in the area, which are generally unheated, a strong asset of the i-RTG was its improved (night-time) temperature regime, thanks to the thermal connection to the building. This advantage translates into energy savings referred to greenhouses on the ground, in case such greenhouses were heated. In order to discuss possible improvements, we adapted an existing greenhouse tomato production model to simulate this particular type of system. After validation, we quantify and discuss the yield rise that could be achieved by improving transparency of the RTG and by increasing CO2 concentration through daytime connection to the building. We show that there is potential to more than double the yield in comparison with the measured crop yield in the i-RTG. Last but not least, we discuss the option of switching to a cropping pattern more adequate for this growing system, that is: to extend the cropping cycle during the winter months, which is not possible in unheated greenhouses in the area. To our knowledge, this work is the very first attempt to evaluate productivity of roof top greenhouses in mild winter regions and quantify options for improving their agronomic performance.

      PubDate: 2017-08-28T02:14:18Z
      DOI: 10.1016/j.agsy.2017.08.002
      Issue No: Vol. 158 (2017)
  • Development of a fodder beet potential yield model in the next generation
    • Authors: E.N. Khaembah; H.E. Brown; R. Zyskowski; E. Chakwizira; J.M. de Ruiter; E.I. Teixeira
      Pages: 23 - 38
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): E.N. Khaembah, H.E. Brown, R. Zyskowski, E. Chakwizira, J.M. de Ruiter, E.I. Teixeira
      The growing importance of fodder beet (Beta vulgaris subsp. vulgaris var. alba L.) as stock feed in recent years has created the need to develop a crop model to help assess crop yield potential across environmental growth conditions. This paper describes the development of a biophysical model for simulating fodder beet growth and development. The model was developed using the Plant Modelling Framework (PMF) within the next generation Agricultural Production Systems sIMulator (PMF-APSIM). The model was parameterised/calibrated and validated using independent datasets from field experiments conducted in the Canterbury region of New Zealand. A sensitivity analysis was conducted to explore yield response to variation in the extinction coefficient and the air temperature. The results show that canopy-related variables (leaf appearance, leaf senescence, leaf area index and light interception) were the most accurately simulated. Dynamic dry matter (DM) and nitrogen (N) accumulation in different plant organs were simulated with intermediary accuracy. Reduced accuracy was mainly observed in the earliest (September) and latest (December) sowing dates. This suggests that responses to seasonal environmental drivers, such as day length and threshold temperatures, are areas that require further research. Similarly, more mechanistic representations of carbon and N partitioning to different plant organs may improve simulation accuracy. The sensitivity analysis showed that DM production was responsive to temperature and the extinction coefficient. This initial development and testing of the fodder beet model in APSIM has helped to identify key knowledge gaps in the understanding of the physiology of the crop and provides new directions for model development.

      PubDate: 2017-09-06T11:04:08Z
      DOI: 10.1016/j.agsy.2017.08.005
      Issue No: Vol. 158 (2017)
  • Small can be beautiful for organic market gardens: an exploration of the
           economic viability of French microfarms using MERLIN
    • Authors: Kevin Morel; Magali San Cristobal; François Gilbert Léger
      Pages: 39 - 49
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): Kevin Morel, Magali San Cristobal, François Gilbert Léger
      Microfarms are commercial soil-based market gardens cultivating organic vegetables with less than 1.5ha per farmer in rural France. Microfarms typically grow crops in both outdoor and protected (tunnel) areas. Despite their growing popularity among young farmers with no agricultural background, there are no data on expected income generated by these small-scale farms. Our objective was to determine the economic viability generated by a given agricultural area based on distinct microfarm scenarios. We used the stochastic model MERLIN to simulate 18microfarm scenarios combining three technical systems (varying with respect to the mechanization level, use of commercial inputs, cropping density, and number of cropping cycles per year), two marketing strategies (varying with respect to the length of the selling period and the range of crops grown), and three investment hypotheses (varying with respect to the level of bank loans and the percentage of workload used for self-built equipment). Viability was calculated from the number of simulations that generated a selected minimum monthly income (600, 1,000, or 1,400 Euro) for a maximum annual workload (1,800 or 2,500h). This study shows that organic microfarms can be made economically viable in some cases but that the risks of not reaching viability in microfarms are not to be neglected. For microfarms, system redesign based on low mechanization, higher cropping density, more cropping cycles per year, low-input practices, lower fixed costs, and lower initial investment (manual and bio-intensive system with tiller cultivation) was more favorable (meaning a higher modeled viability) than input substitution (classic system) at a small scale. A 9-month selling period without winter storage crop cultivation led to higher viability than a 12-month selling period with winter storage crop cultivation. Low-cost investment strategies based on self-built equipment and second-hand materials led to lower viability than high-cost investment strategies that purchased equipment because the low-cost strategies increased the workload. Further research on microfarms should integrate other types of production and activities, such as small-scale breeding and on-farm processing and examine in which extent collaborations between microfarmers and larger scale farms could contribute to reshape farming systems and impact rural communities beyond the gate of microfarms.

      PubDate: 2017-09-18T05:31:40Z
      DOI: 10.1016/j.agsy.2017.08.008
      Issue No: Vol. 158 (2017)
  • Environmental impacts along intensity gradients in Norwegian dairy
           production as evaluated by life cycle assessments
    • Authors: Anne Kjersti Bakken; Kristin Daugstad; Astrid Johansen; Anne-Grete Roer Hjelkrem; Gustav Fystro; Anders Hammer Strømman; Audun Korsaeth
      Pages: 50 - 60
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): Anne Kjersti Bakken, Kristin Daugstad, Astrid Johansen, Anne-Grete Roer Hjelkrem, Gustav Fystro, Anders Hammer Strømman, Audun Korsaeth
      The aim of the study was to explore whether and how intensification would contribute to more environmentally friendly dairy production in Norway. Three typical farms were envisaged, representing intensive production strategies with regard to milk yield both per cow and per hectare in the three most important regions for dairy production in Norway. The scores on six impact categories for produced milk and meat were compared with corresponding scores obtained with a medium production intensity at a base case farm. Further, six scenario farms were derived from the base case. They were either intensified or made more extensive with regard to management practices that were likely to be varied and implemented under northern temperate conditions. The practices covered the proportion and composition of concentrates in animal diets and the production and feeding of forages with different energy concentration. Processes from cradle to farm gate were incorporated in the assessments, including on-farm activities, capital goods, machinery and production inputs. Compared to milk produced in a base case with an annual yield of 7250kg energy corrected milk (ECM) per cow, milk from farms with yields of 9000kg ECM or higher, scored better in terms of global warming potential (GWP). The milk from intensive farms scored more favourably also for terrestrial acidification (TA), fossil depletion (FD) and freshwater eutrophication (FE). However, this was not in all cases directly related to animal yield, but rather to lower burden from forage production. Production of high yields of energy-rich forage contributed substantially to the better scores on farms with higher-yielding animals. The ranking of farms according to score on agricultural land occupation (ALO) depended upon assumptions set for land use in the production of concentrate ingredients. When the Ecoinvent procedure of weighting according to the length of the cropping period was applied, milk and meat produced on diets with a high proportion of concentrates, scored better than milk and meat based on a diet dominated by forages. With regards to terrestrial ecotoxicity (TE), the score was mainly a function of the amount of concentrates fed per functional unit produced, and not of animal yield per se. Overall, the results indicated that an intensification of dairy production by means of higher yields per animal would contribute to more environment-friendly production. For GWP this was also the case when higher yields per head also resulted in higher milk yields and higher N inputs per area of land.

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2017.09.001
      Issue No: Vol. 158 (2017)
  • An irrigated cotton farm emissions case study in NSW, Australia
    • Authors: J.W. Powell; J.M. Welsh; R.J. Eckard
      Pages: 61 - 67
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): J.W. Powell, J.M. Welsh, R.J. Eckard
      The primary source of emissions in broadacre cropping is synthetic fertiliser applied to farmland, creating nitrous oxide from chemical processes in the soil. In high yielding irrigated cotton production, nitrogen remains a key input to maintain yields and maximise crop returns. This study aims to identify immediate strategies available to broadacre irrigation to reduce emissions and maintain profitability. Four emission mitigation strategies on a large broadacre irrigation farm in Northern New South Wales producing cereals, pulse and cotton crops were modelled. The results show rotating cotton with pulse crops, instead of wheat, can achieve an 8% reduction in emissions and increase whole farm gross margin by 12%, due primarily to the current historically high chickpea price and a reduction in applied nitrogen. Combining enhanced efficiency fertilisers in cotton crops in a more comprehensive abatement strategy has shown an indicative 13% emissions reduction from the baseline scenario, with a 6% reduction in farm gross margin from the increased fertiliser cost. However, uncertainty regarding the impact of EEFs on cotton yield in vertosol soils is noted. The soil sequestration from including a tree-lot in the emissions reduction strategy reduced whole farm emissions by 11% and reduced whole farm gross margin of 3%; however, difficulty in establishment and high establishment costs can add economic risk. Combining all three emissions reduction strategies results in a significant emissions reduction of 33% and a 4% gain in whole farm gross margin. Sensitivity analysis highlights gross margins results to be particularly sensitive to chickpea price movement. With this desktop modelling in mind, the discussion draws on industry research revealing that at a field scale, carefully balanced agronomic nuances exist between cotton cropping rotations and secure economic outcomes. The addition of achieving environmental objectives simultaneously with these variables is yet another future challenge facing government emissions abatement incentive programs and broadacre cropping businesses.

      PubDate: 2017-09-30T06:05:47Z
      DOI: 10.1016/j.agsy.2017.09.005
      Issue No: Vol. 158 (2017)
  • Feedbase intervention in a cow-calf system in the flooding pampas of
           Argentina: 2. Estimation of the marginal value of additional feed
    • Authors: Horacio Berger; Franco Bilotto; Lindsay W. Bell; Claudio F. Machado
      Pages: 68 - 77
      Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158
      Author(s): Horacio Berger, Franco Bilotto, Lindsay W. Bell, Claudio F. Machado
      Temporal variability in the availability of forage reduces the production and economic performance of livestock systems. The marginal value of feed (MVF, the possible gross economic benefit of additional feed on offer during an annual cycle), was assessed under the expected variability of climate and prices in a cow-calf operation from the Flooding Pampas, Argentina. Herbage mass accumulation (HMA) was simulated on a daily basis over 20 different years with DairyMod, grouped by month and season and where the HMA was equal or below 50% of its long-term average, it was tagged as “Dry”. Typical monthly pasture growth rates were synthetically depicted for average years (Average), or with dry autumn (D-Au), winter (D-Wi), spring (D-Sp) or summer (D-Su) conditions. These pasture growth curves were incorporated into whole-farm scenarios which were modelled with SIMUGAN, a bio-economic whole-farm model. Farm scenarios were baseline (unchanged HMA) or with additional 10% of the annual HMA. This additional feed was either evenly distributed across each month of the year (all year), or the full amount provided in one of the four seasons. These scenarios were repeated in a factorial design across a range of stocking rates (SR; 0.9–1.3cows/ha) on an average year or years including one dry season (D-Au, D-Wi, D-Sp orD-Su). SIMUGAN results were fed to an ad-hoc built model to calculate production and market risk profiles. In years with average HMA, MVF were always below 0.05US$/kg DM but the presence of a dry season caused significantly higher MVF. Years with dry autumn presented the highest economic responses when the extra feed was fed during autumn or winter. MVF analyses showed a positive impact of additional forage only above 1.1head/ha and this increased with SR, whereas MVF at the low SR were mostly negative due to extra hay making costs. At 1.1 and 1.2head/ha, allocating additional feed in autumn produced a higher return (0.04 and 0.08US$/kg DM) than feed provided at other times of the year (averaging 0.02 and 0.05US$/kg DM). Otherwise, at 1.3 SR extra feed in winter always had the highest MVF (up to 0.19US$/kg DM). Bio-physical variables of livestock demand and seasonality of pasture growth were the main drivers of MVF variability. Overall, the framework developed by integrating forage, livestock and economic models “in a series” effectively identified the economic feasibility of changes to the farm feed-base under different climatic and livestock management conditions.

      PubDate: 2017-10-08T18:55:37Z
      DOI: 10.1016/j.agsy.2017.09.004
      Issue No: Vol. 158 (2017)
  • Integrating economic and environmental impact analysis: The case of
           rice-based farming in northern Thailand
    • Authors: S.J. Ramsden; P. Wilson; B. Phrommarat
      Pages: 1 - 10
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): S.J. Ramsden, P. Wilson, B. Phrommarat
      Crop production is associated with a range of potential environmental impacts, including field emissions of greenhouse gases, loss of nitrogen and phosphorous nutrients to water and toxicity effects on humans and natural ecosystems. Farmers can mitigate these environmental impacts by changing their farming systems; however these changes have implications for production and profitability. To address these trade-offs, a farm-level model was constructed to capture the elements of a rice-based production system in northern Thailand. Life Cycle Assessment (LCA) was used to generate environmental impacts, across a range of indicators, for all crops and associated production processes in the model. A baseline, profit maximising combination of crops and resource use was generated and compared with a greenhouse gas minimising scenario and an alternative inputs (fertilisers and insecticides) scenario. Greenhouse gas minimisation showed a reduction in global warming potential of 13%; other impact indicators also decreased. Associated profit foregone was 10% as measured by total gross margin. With the alternative farm inputs (ammonium sulphate, organic fertiliser and fipronil insecticide), results indicated that acidification, eutrophication, freshwater and terrestrial ecotoxicity impacts were reduced by 43, 37, 47 and 91% respectively with relatively small effects on profit.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.06.006
      Issue No: Vol. 157 (2017)
  • Variations in nitrogen utilisation on conventional and organic dairy farms
           in Norway
    • Authors: Matthias Koesling; Sissel Hansen; Marina Azzaroli Bleken
      Pages: 11 - 21
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Matthias Koesling, Sissel Hansen, Marina Azzaroli Bleken
      Reduced N-surpluses in dairy farming is a strategy to reduce the environmental pollution from this production. This study was designed to analyse the important variables influencing nitrogen (N) surplus per hectare and per unit of N in produce for dairy farms and dairy systems across 10 certified organic and 10 conventional commercial dairy farms in Møre og Romsdal County, Norway, between 2010 and 2012. The N-surplus per hectare was calculated as N-input (net N-purchase and inputs from biological N-fixation, atmospheric deposition and free rangeland) minus N in produce (sold milk and meat gain), and the N-surplus per unit of N-produce as net N-input divided by N in produce. On average, the organic farms produced milk and meat with lower N-surplus per hectare (88±25kgN·ha−1) than did conventional farms (220±56kgN·ha−1). Also, the N-surplus per unit of N-produce was on average lower on organic than on conventional farms, 4.2±1.2kgN·kgN−1 and 6.3±0.9kgN·kgN−1, respectively. All farms included both fully-cultivated land and native grassland. N-surplus was found to be higher on the fully cultivated land than on native grassland. N-fertilizers (43%) and concentrates (30%) accounted for most of the N input on conventional farms. On organic farms, biological N-fixation and concentrates contributed to 32% and 36% of the N-input (43±18N·kgN−1 and 48±11N·kgN−1), respectively. An increase in N-input per hectare increased the amount of N-produce in milk and meat per hectare, but, on average for all farms, only 11% of the N-input was utilised as N-output; however, the N-surplus per unit of N in produce (delivered milk and meat gain) was not correlated to total N-input. This surplus was calculated for the dairy system, which also included the N-surplus on the off-farm area. Only 16% and 18% of this surplus on conventional and organic farms, respectively, was attributed to surplus derived from off-farm production of purchased feed and animals. Since the dairy farm area of conventional and organic farms comprised 52% and 60% of the dairy system area, respectively, it is crucial to relate production not only to dairy farm area but also to the dairy system area. On conventional dairy farms, the N-surplus per unit of N in produce decreased with increasing milk yield per cow. Organic farms tended to have lower N-surpluses than conventional farms with no correlation between the milk yield and the N-surplus. For both dairy farm and dairy system area, N-surpluses increased with increasing use of fertilizer N per hectare, biological N-fixation, imported concentrates and roughages and decreased with higher production per area. This highlights the importance of good agronomy that well utilize available nitrogen.

      PubDate: 2017-07-02T23:43:15Z
      DOI: 10.1016/j.agsy.2017.06.001
      Issue No: Vol. 157 (2017)
  • Carbon footprint of sheep production systems in semi-arid zone of Chile: A
           simulation-based approach of productive scenarios and precipitation
    • Authors: Paula Toro-Mujica; Claudio Aguilar; Raúl R. Vera; Fernando Bas
      Pages: 22 - 38
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Paula Toro-Mujica, Claudio Aguilar, Raúl R. Vera, Fernando Bas
      Grassland based sheep production systems in the semi-arid to sub-humid Central region of Chile are expected to improve technical and economic efficiency, while at the same time decreasing emissions of greenhouse gases (GHG). An existing empirical, stochastic simulation model of grazing sheep production was modified to allow for a cradle-to-farm-gate quantification of GHG under a large number of scenarios. The model includes pasture availability and utilization, supplementation of sheep, milk and lamb production, and carbon sequestration by forages and soils among others. Simulated scenarios included factorial combinations of a range of farm types previously typified and a range of sheep management practices, and their interaction with dry, average, or rainy years that affected grass growth. The carbon footprint (CF) was calculated for 20 runs of each case. Numerous interactions between animal outputs, forage availability and CF, as well as trade-offs, were found. Rainfall patterns had a significant effect on range and sown pastures yields when other factors were kept constant. A decrease of 32% in average rainfall for a dry year resulted in a reduction of forage production of 13%, whereas a rainy year with rainfall 36% higher than average, increased it by 12%, Forage yields had a significant effect on CF. Three different farm types showed CF of 7.4 to 13.3CO2-eq·kg−1 LW−1. Farms that used higher inputs had higher forage production and lower CF, which decreased further if soil C sequestration is accounted for. Large farms that had lower stocking rates than the rest, and that used Merino sheep with high reproductive rates, had lower CF than the smaller farms that make a more intense land use. Reproductive rates had a large and significant effect on CF as they determine the number of ewes required to maintain constant production and overall flock composition. The average CF for lamb production across all scenarios was 14.8kgCO2-eq·kgLW−1, and decreased by 2kg CO2-eq·kgLW−1 when carbon sequestration was accounted for. The simulated systems were stable in years with average rainfall, but their sustainability seems fragile if faced with a sequence of dry years. It is concluded that the abundant interactions between the rainfall pattern and management variables would be difficult to study in field experiments, and that simulation modelling is a powerful tool to assess the consequences of numerous climate and production scenarios.

      PubDate: 2017-07-02T23:43:15Z
      DOI: 10.1016/j.agsy.2017.06.012
      Issue No: Vol. 157 (2017)
  • Assessing the environmental impacts of cropping systems and cover crops:
           Life cycle assessment of FAST, a long-term arable farming field experiment
    • Authors: Ulrich E. Prechsl; Raphael Wittwer; Marcel G.A. van der Heijden; Gisela Lüscher; Philippe Jeanneret; Thomas Nemecek
      Pages: 39 - 50
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Ulrich E. Prechsl, Raphael Wittwer, Marcel G.A. van der Heijden, Gisela Lüscher, Philippe Jeanneret, Thomas Nemecek
      To reduce environmental impacts of cropping systems, various management strategies are being discussed. Long-term field experiments are particularly suitable to directly compare different management strategies and to perform a comprehensive impact assessment. To identify the key drivers of several environmental impacts, we analysed a six year crop rotation of the Farming System and Tillage Experiment (FAST) by means of the Swiss Agriculture Life Cycle Assessment method (SALCA). The following factors of the FAST experiment were considered: (1) cropping system (stockless conventional farming vs. organic farming), (2) tillage (intensive tillage vs. no or reduced tillage), and (3) cover crop. We analysed the effects of these three factors on the global warming potential (GWP), aquatic and terrestrial eutrophication, and aquatic ecotoxicity for two functional units, i.e. per product and per area. Potential impacts on biodiversity were also analysed. Our analysis revealed that there is not one superior cropping system, as the ranking depended on the environmental impact selected and on the functional unit. The cropping system had the strongest effect on most of the environmental impacts, and this was mainly driven by differences in N-fertilisation (amount and form) and yield. The global warming potential, for instance, was highest in both conventional systems compared to the organic systems, when emissions were calculated per area. In contrast, calculating emissions per product, there were no statistical differences between all four systems. On the other hand, due to higher nitrogen emissions related to the application of cattle slurry in the organic system, the terrestrial eutrophication of the organic systems was higher than the conventional systems, independent of the functional unit. The effects of tillage were much lower compared to the cropping system. No tillage, but not necessarily reduced tillage, and the cultivation of cover crops had the potential to reduce aquatic eutrophication. As N-fertilisation dominated many impact categories, we suggest improving the N-efficiency as a crucial leverage point to improve the environmental performance of arable farming systems.

      PubDate: 2017-07-12T02:03:07Z
      DOI: 10.1016/j.agsy.2017.06.011
      Issue No: Vol. 157 (2017)
  • Assessing ammonia emission abatement measures in agriculture: Farmers'
           costs and society's benefits – A case study for Lower Saxony, Germany
    • Authors: Susanne Wagner; Elisabeth Angenendt; Olga Beletskaya; Jürgen Zeddies
      Pages: 70 - 80
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Susanne Wagner, Elisabeth Angenendt, Olga Beletskaya, Jürgen Zeddies
      Ammonia (NH3) emissions have adverse impacts on the environment and, being a precursor for fine particulate matter, also on human health. About 95% of NH3 emissions in Germany originate from agriculture, mainly from livestock husbandry. This case study is aimed at presenting an approach that evaluates NH3 emission abatement measures in agriculture regarding their abatement costs for farmers and their benefits for the society in terms of avoided external costs of health damages and loss of terrestrial biodiversity. Following the impact-pathway chain, an economic-ecological farm model for estimating NH3 emission reductions and abatement costs was combined with an environmental impact assessment model for estimating the benefits for human health and biodiversity. The case study analysed a variety of manure storage cover and application techniques in Lower Saxony, a region in the north-west of Germany with the highest livestock density in Germany and high NH3 emissions. In the reference situation, the damage costs of NH3 emissions were EUR 2.7 billion. The implementation of concrete storage covers and slurry injection, the most effective measures, reduced NH3 emissions by 25% and achieved net benefits of EUR 505 million. Farmers' abatement costs averaged over all farms ranged from EUR 3.6 to 6.8 per kilogramme NH3 reduced. The abatement costs per farm type ranged from EUR 2.4 to 16.6 for floating plastic covers and from EUR 2.2 to 11.4 for concrete covers. The abatement costs for floating plastic covers were lower for grazing livestock specialists, while the abatement costs for concrete covers were lower for pig specialists, poultry specialists and mixed farms. Farm type specific abatement costs for manure application techniques ranged from EUR 4.5 to 9.6 per kilogramme NH3 reduced with little variation between trailing shoe and cultivator/injector techniques. Abatement costs for trailing shoe application were lower than for cultivator/injector application for grazing livestock specialists, poultry specialists and mixed farms. The average benefits per kilogramme NH3 reduced were EUR 14.1 for health and EUR 10.4 for biodiversity, totalling EUR 24.5. As the benefits exceed the abatement costs for all measures analysed in this study, principally, they can be recommended for implementation. However, the variation in abatement potentials and costs per farm type indicate differences in suitability. While manure covers should above all be implemented by pig specialists because of their high abatement potential, manure application techniques should be implemented by grazing livestock specialists. Among manure storage covers, floating plastic covers are more favourable for grazing livestock specialists, whereas concrete covers are more suitable for all other farm types. The analysis with the farm model was considered more appropriate than recent analyses at technical or macroeconomic level, because the abatement costs reflect differences in farm types, detailed production processes and farmers' profit-maximising behaviour. Overall, it can be concluded that an assessment of NH3 emission abatement measures should be carried out for farm types and should consider impacts of NH3 emission abatement both on human health and biodiversity. The presented modelling approach enables to estimate abatement costs for farm types and benefits for human health and biodiversity. Cost-efficient NH3 emission abatement measures tailored to farm types can be identified and farm type specific regional abatement strategies can be developed.

      PubDate: 2017-07-24T08:52:51Z
      DOI: 10.1016/j.agsy.2017.06.008
      Issue No: Vol. 157 (2017)
  • Climate change impacts on crop yields, land use and environment in
           response to crop sowing dates and thermal time requirements
    • Authors: Andrea Zimmermann; Heidi Webber; Gang Zhao; Frank Ewert; Johannes Kros; Joost Wolf; Wolfgang Britz; Wim de Vries
      Pages: 81 - 92
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Andrea Zimmermann, Heidi Webber, Gang Zhao, Frank Ewert, Johannes Kros, Joost Wolf, Wolfgang Britz, Wim de Vries
      Impacts of climate change on European agricultural production, land use and the environment depend on its impact on crop yields. However, many impact studies assume that crop management remains unchanged in future scenarios, while farmers may adapt their sowing dates and cultivar thermal time requirements to minimize yield losses or realize yield gains. The main objective of this study was to investigate the sensitivity of climate change impacts on European crop yields, land use, production and environmental variables to adaptations in crops sowing dates and varieties' thermal time requirements. A crop, economic and environmental model were coupled in an integrated assessment modelling approach for six important crops, for 27 countries of the European Union (EU27) to assess results of three SRES climate change scenarios to 2050. Crop yields under climate change were simulated considering three different management cases; (i) no change in crop management from baseline conditions (NoAd), (ii) adaptation of sowing date and thermal time requirements to give highest yields to 2050 (Opt) and (iii) a more conservative adaptation of sowing date and thermal time requirements (Act). Averaged across EU27, relative changes in water-limited crop yields due to climate change and increased CO2 varied between −6 and +21% considering NoAd management, whereas impacts with Opt management varied between +12 and +53%, and those under Act management between −2 and +27%. However, relative yield increases under climate change increased to +17 and +51% when technology progress was also considered. Importantly, the sensitivity to crop management assumptions of land use, production and environmental impacts were less pronounced than for crop yields due to the influence of corresponding market, farm resource and land allocation adjustments along the model chain acting via economic optimization of yields. We conclude that assumptions about crop sowing dates and thermal time requirements affect impact variables but to a different extent and generally decreasing for variables affected by economic drivers.

      PubDate: 2017-07-24T08:52:51Z
      DOI: 10.1016/j.agsy.2017.07.007
      Issue No: Vol. 157 (2017)
  • Integrated modelling of efficient crop management strategies in response
           to economic damage potentials of the Western Corn Rootworm in Austria
    • Authors: Elisabeth Feusthuber; Hermine Mitter; Martin Schönhart; Erwin Schmid
      Pages: 93 - 106
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Elisabeth Feusthuber, Hermine Mitter, Martin Schönhart, Erwin Schmid
      The spread of the Western Corn Rootworm (WCR; Diabrotica virgifera virgifera) challenges farmers in intensive maize production regions. We model efficient crop management strategies in response to economic damage potentials of the invasive WCR in Austria. A spatially explicit integrated modelling framework has been developed to calculate economic damage potentials from maize yield losses for a past (1975–2005) and a future (2010–2040) period with climate change. The economic damage potentials determine the choice of efficient crop management strategies considering insecticide applications, crop rotations with gradual maize limitations, fertilization intensities and irrigation. The integrated modelling framework includes the crop rotation model CropRota, the bio-physical process model EPIC, and the non-linear land use optimization model BiomAT. Typical crop rotations are simulated by CropRota at the municipality level. They are input to EPIC to simulate crop yields at the 1km pixel resolution, which are part of the gross margin calculations entering BiomAT. Results of economic damage potentials with a 10% maize yield loss range between 3€/ha and 180€/ha, depending on the location, and increase to between 14€/ha and 903€/ha at 50% maize yield loss. The analysis of economic damage potentials shows a high regional variability. Moreover, the model results show that a decrease in maize shares combined with moderate fertilization levels is more efficient for WCR control than insecticide use. However, further crop management strategies have to be developed in order to reduce maize yield and economic losses.

      PubDate: 2017-07-24T08:52:51Z
      DOI: 10.1016/j.agsy.2017.07.011
      Issue No: Vol. 157 (2017)
  • A retrospective analysis of the United States poultry industry: 1965
           compared with 2010
    • Authors: Ben Putman; Greg Thoma; Jasmina Burek; Marty Matlock
      Pages: 107 - 117
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Ben Putman, Greg Thoma, Jasmina Burek, Marty Matlock
      The U.S. poultry industry requires a comprehensive understanding of the driving forces behind the changes in the environmental performance of poultry meat production in order to implement an effective sustainability strategy. This life cycle assessment (LCA) evaluates those changes over the past 45years so that the industry can prioritize improvements to aspects of production that will have the greatest effect on the environmental impacts associated with poultry production. The LCA included material and energy flows associated with crop production and live poultry operations, beginning with one day old baby chicks in the grandparent generation, continuing through the parent generation, and ending with live market-weight broilers and culled hens at the farm gate. The results indicated that improvements in background systems and bird performance were the primary drivers behind a reduction in environmental impacts and decreased resource requirements in U.S. poultry meat production in 2010, as compared to 1965. Climate change, acidification, and eutrophication impacts associated with poultry production decreased by 36%, 29%, and 25% per 1000kg poultry meat produced, respectively, from 1965 to 2010. Furthermore, resource-related impacts decreased in the categories of fossil energy use (39%), water depletion (58%), and agricultural land occupation (72%) per 1000kg of poultry meat produced. This study provides the first retrospective analysis of poultry meat production in the United States, and the only U.S. poultry LCA that incorporates spent hen meat destined for human consumption and successive breeding generations into an analysis of broiler production. These methodological considerations provide greater insight into the impacts associated with U.S. poultry supply chains than was previously available, which will allow the U.S. poultry industry to make more informed decisions regarding an effective sustainability strategy and will increase publicly-available LCI data with contributions to the National Agricultural Library's LCA Commons.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.008
      Issue No: Vol. 157 (2017)
  • Sustainability assessment of agricultural systems: The validity of expert
           opinion and robustness of a multi-criteria analysis
    • Authors: Farahnaz Pashaei Kamali; João A.R. Borges; Miranda P.M. Meuwissen; Imke J.M. de Boer; Alfons G.J.M. Oude Lansink
      Pages: 118 - 128
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Farahnaz Pashaei Kamali, João A.R. Borges, Miranda P.M. Meuwissen, Imke J.M. de Boer, Alfons G.J.M. Oude Lansink
      Sustainability assessment of agricultural systems is frequently hampered by data availability. Elicitation of expert opinions combined with multi-criteria assessment (MCA) could be a useful approach for sustainability assessments in data-scarce situations. To our knowledge, the validity of expert opinion used to score sustainability performance of agricultural systems, however, has not been addressed. Also, robustness of the overall outcome of MCA to uncertainty about scores obtained from expert elicitation and weights used to aggregate scores is generally not addressed. The objectives of this study were to evaluate the validity of expert opinion, and to evaluate the robustness of the overall MCA outcome to uncertainty about scores and weights. The case study considers three soybean agricultural systems in Latin America: conventional agricultural system, with either genetically modified (GM) or non-genetically modified (non-GM) soybeans, and organic agricultural system. The validation was carried out by comparing the sustainability scores of experts with values from scientific studies. The robustness of the overall outcome of the MCA to uncertainty about scores and weights was assessed using Monte Carlo simulation. The comparison of expert opinion with reviewed studies showed that expert opinions are a potential alternative to extensive data-rich methods. The validity of expert opinions can be increased by considering a larger group of experts, with a high level of knowledge about agricultural systems and sustainability issues. With regard to robustness, the overall outcome of the MCA showed higher variation for organic soybean agricultural systems compared with GM and non-GM, in both Brazil and Argentina.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.013
      Issue No: Vol. 157 (2017)
  • Bringing farmers into the game. Strengthening farmers' role in the
           innovation process through a simulation game, a case from Tunisia
    • Authors: Aleksandra Dolinska
      Pages: 129 - 139
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Aleksandra Dolinska
      While farmers are recognized as equally weighing sources of innovation in the Agricultural Innovation Systems (AIS) framework, their participation in knowledge co-production within multi-stakeholder settings such as innovation platforms is still often limited. Farmers participate more in implementing than in designing innovations or in shaping innovation process. Drawing on the companion modeling approach and critical companion posture, we designed a simulation game based method that we tested with dairy farmers in the irrigation scheme in the North-West Tunisia. The objectives were to engage farmers in a research project as equal knowledge producers, to support the process of collective construction of improved farm strategies and to create conditions for farmers to get empowered to pursue their innovation ambitions. The LAITCONOMIE game, based on the self-design principle, creates conditions for farmers to mobilize their knowledge and knowledge of others to respond to their local innovation needs. Despite a modest scale, the game experiment brought results in terms of knowledge co-production and of change in farming practice of the participants.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.002
      Issue No: Vol. 157 (2017)
  • Carbon footprint in the ethanol feedstocks cultivation –
           Agricultural CO2 emission assessment
    • Authors: Karina Scurupa Machado; Robson Seleme; Marcel M. Maceno; Izabel C. Zattar
      Pages: 140 - 145
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Karina Scurupa Machado, Robson Seleme, Marcel M. Maceno, Izabel C. Zattar
      CO2 emission is a current global concern and has progressively increased due fossil fuel use, leading to climatic changes. As a workaround to this problem low carbon fuel use has been the key to mitigate it in several countries. Brazil is a leader in ethanol sugarcane production and has a high demand expected for this biofuel, which means that large areas will be cultivated to supply this demand. Although biofuels help to reduce carbon emissions, agriculture is highlighted in the emission of CO2 to the atmosphere as from the soil. Considering that the amount of soil carbon lost to the atmosphere is tightly coupled to the vegetation type, soil properties and climate conditions, the main objective of this study was to estimate and compare the CO2 emission in the agricultural phase of ethanol production, as from its main feedstocks. A model based on carbon flux of the soil-plant-atmosphere system, was used. From the five crops assessed (sugarcane, sugar-beet, corn, rice and cassava), sugarcane and corn crops presented, the less CO2 emission at nowadays and over the next 30years, in opposite of the sugar-beet crop, which was the less sustainable feedstock for ethanol production in terms of CO2 emission. The outcomes of this study contribute to develop scenarios to better understand the impact of ethanol production in the GEEs emission, both in nowadays and in the future, considering the increasing demand for biofuel. Also is presented in this study a detailed discussion regarding important environmental issues of sugarcane and corn ethanol production, which are essential to be considered in the ethanol-policy decision. To our knowledge this is the first study that compares the CO2 emitted from the main ethanol feedstocks based on field tests, under the same conditions of soil and climate.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.015
      Issue No: Vol. 157 (2017)
  • Assessing both ecological and engineering resilience of a steppe
           agroecosystem using the viability theory
    • Authors: R. Sabatier; F. Joly; B. Hubert
      Pages: 146 - 156
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): R. Sabatier, F. Joly, B. Hubert
      The high dependence of rangeland-based livestock farming systems to environmental uncertainty makes the resilience of these systems as important as production. Quantification of resilience is however difficult to conduct in real systems due to their low reproducibility. In this study, we develop a modeling approach to quantify both engineering resilience (return time after a perturbation) and ecological resilience (magnitude of a perturbation that a system can bear) of a mixed herd livestock farming system in Mongolian steppes. The model, build within the framework of the viability theory, captures the dynamics of the herd and its management. The system has the particularity to be impacted by agro-climatic events called dzuds that induce massive mortalities when harsh climatic condition and high stocking densities are met. Results show that (i) resilience non-linearly depends on herd composition and the level of underground biomass of the system, (ii) contrasted management strategies may be followed to cope with the risk of dzud and (iii) according to their herd composition most herders of the area can absorb climate shocks unless they compete for forage with other herders. Results are discussed regarding the impact of forage resource sharing on the resilience of these grazing systems.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.009
      Issue No: Vol. 157 (2017)
  • Combining models to estimate the impacts of future climate scenarios on
           feed supply, greenhouse gas emissions and economic performance on dairy
           farms in Norway
    • Authors: Şeyda Özkan Gülzari; Bente Aspeholen Åby; Tomas Persson; Mats Höglind; Klaus Mittenzwei
      Pages: 157 - 169
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Şeyda Özkan Gülzari, Bente Aspeholen Åby, Tomas Persson, Mats Höglind, Klaus Mittenzwei
      There is a scientific consensus that the future climate change will affect grass and crop dry matter (DM) yields. Such yield changes may entail alterations to farm management practices to fulfill the feed requirements and reduce the farm greenhouse gas (GHG) emissions from dairy farms. While a large number of studies have focused on the impacts of projected climate change on a single farm output (e.g. GHG emissions or economic performance), several attempts have been made to combine bio-economic systems models with GHG accounting frameworks. In this study, we aimed to determine the physical impacts of future climate scenarios on grass and wheat DM yields, and demonstrate the effects such changes in future feed supply may have on farm GHG emissions and decision-making processes. For this purpose, we combined four models: BASGRA and CSM-CERES-Wheat models for simulating forage grass DM and wheat DM grain yields respectively; HolosNor for estimating the farm GHG emissions; and JORDMOD for calculating the impacts of changes in the climate and management on land use and farm economics. Four locations, with varying climate and soil conditions were included in the study: south-east Norway, south-west Norway, central Norway and northern Norway. Simulations were carried out for baseline (1961–1990) and future (2046–2065) climate conditions (projections based on two global climate models and the Special Report on Emissions Scenarios (SRES) A1B GHG emission scenario), and for production conditions with and without a milk quota. The GHG emissions intensities (kilogram carbon dioxide equivalent: kgCO2e emissions per kg fat and protein corrected milk: FPCM) varied between 0.8kg and 1.23kgCO2e(kgFPCM)−1, with the lowest and highest emissions found in central Norway and south-east Norway, respectively. Emission intensities were generally lower under future compared to baseline conditions due mainly to higher future milk yields and to some extent to higher crop yields. The median seasonal above-ground timothy grass yield varied between 11,000kg and 16,000kgDMha−1 and was higher in all projected future climate conditions than in the baseline. The spring wheat grain DM yields simulated for the same weather conditions within each climate projection varied between 2200kg and 6800kgDMha−1. Similarly, the farm profitability as expressed by total national land rents varied between 1900 million Norwegian krone (NOK) for median yields under baseline climate conditions up to 3900 million NOK for median yield under future projected climate conditions.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.004
      Issue No: Vol. 157 (2017)
  • Efficient crop model parameter estimation and site characterization using
           large breeding trial data sets
    • Authors: Abhishes Lamsal; S.M. Welch; J.W. Jones; K.J. Boote; Antonio Asebedo; Jared Crain; Xu Wang; Will Boyer; Anju Giri; Elizabeth Frink; Xuan Xu; Garrison Gundy; Junjun Ou; Pabodha Galgamuwe Arachchige
      Pages: 170 - 184
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Abhishes Lamsal, S.M. Welch, J.W. Jones, K.J. Boote, Antonio Asebedo, Jared Crain, Xu Wang, Will Boyer, Anju Giri, Elizabeth Frink, Xuan Xu, Garrison Gundy, Junjun Ou, Pabodha Galgamuwe Arachchige
      Scientists have estimated that global crop production needs to double by 2050 to supply the demand for food, feed, and fuel. To reach this goal, novel methods are needed to increase breeding potential yield rates of gain as well as on-farm yields through enhanced management strategies. Both of these tasks require the ability to predict plant performance in multiple, dynamic environments based on a knowledge of cultivar characteristics (critical short day lengths, maximum leaf photosynthetic rates, pod fill durations, etc.) that are ultimately linked to genetics. Because of this linkage, we refer to such traits as genotype-specific parameters (GSP's). Using industry-provided yield and weather data from 353 site-years, we estimated seven primary CROPGRO-Soybean GSP's for each of 182 varieties. The data set had two shortcomings. First, no planting dates were supplied, rendering unknowable the environment actually experienced by the crop. Second, soil data were provided only for the top 20cm, which is inadequate to specify the root environment and water supply availability. Therefore, additional edaphic information was acquired. A novel optimization algorithm was developed that simultaneously estimates GSP's and planting dates, while tuning layered soil water-holding properties. The optimizer, which we have named the holographic genetic algorithm (HGA), uses both externally supplied constraints and its own analysis of data structure to reduce what would otherwise be a search over 2000 dimensions to a much smaller number of overlapping 1- to 3-D problems. Two types of runs were performed. The first was preceded by an independent component analysis (ICA) of published GSP's. The subsequent training sought good component scores rather than the GSP's themselves. The second, separate factor (SF) approach allowed all GSP's to vary separately. This makes parameters unconstrained and more evenly distributed. Results showed that HGA works quite well with the CROPGRO-Soybean model to estimate the cultivar and site-specific parameters from breeding trial data. The quality of the calibrations and evaluations were similar across both run types with RMSE values being ca. 5.6% of the maximum yields. Moreover, the GSP's for a variety can be used to predict its yield in trials not used in that cultivar's calibration. Finally, despite high dimensionality, the GSP's, planting dates, and soil properties for all lines and sites converged concurrently in <58 iterations, demonstrating great utility for use with big data sets.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.016
      Issue No: Vol. 157 (2017)
  • Spatial evaluation of maize yield in Malawi
    • Authors: Lin Liu; Bruno Basso
      Pages: 185 - 192
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Lin Liu, Bruno Basso
      The objective of this research was to quantify the effects of climate, soil, and management on spatial and temporal variation of maize yields across Malawi. We simulated four different nitrogen (N) management strategies to evaluate the impact of mineral and organic N amendments on maize yield across the agricultural lands of Malawi. Maize yield increased when the crop was grown with pigeonpea, or if mineral N fertilizer was added, but yield improvements under these management strategies varied spatially as result of different soil biophysical and chemical properties, weather, and their interactions with management. The increased yield from N addition showed that a significant increase in food production could be achieved in Malawi to reduce food insecurity.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.014
      Issue No: Vol. 157 (2017)
  • What prospective scenarios for 2035 will be compatible with reduced impact
           of French beef and dairy farm on climate change'
    • Authors: Claire Mosnier; Anne Duclos; Jacques Agabriel; Armelle Gac
      Pages: 193 - 201
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Claire Mosnier, Anne Duclos, Jacques Agabriel, Armelle Gac
      The agricultural sector is being called upon to reduce its greenhouse gas emissions (GHG). A scenario approach was developed to explore the plausible futures of the French bovine sector and their impact on climate change. These scenarios encompass a Business As Usual scenario (S1-BAU) and alternative contrasting scenarios: (S2) cattle production increase to meet a high global demand under a liberal policy, (S3) refocus on internal demand within France, with an upmarket move to ‘green’ products, (S4) committed public policy to reduce GHG emissions. This paper analyses how key drivers of these scenarios (e.g. subsidies on investment, reduction of market risks, carbon tax, limitation of concentrate feed in animal diets) affect the evolution of production, economics, and environmental impact on climate change of typical French suckler cow and dairy farms, by means of simulations performed with a bio-economic model. To adapt their farming systems to the scenarios, farms can opt for variably intensive/integrated practices per animal and per unit land area. Some technological progress in animal production, crop production, and farm equipment is also modeled. Results show that in S1-BAU, milk production, net income and impact on climate change of dairy farms rise. Beef production and impact on climate change decrease slightly in suckler cow farms. Impact on climate change per unit of product decreases owing to higher productivity per animal and to a more integrated management of crop production. Alternative scenarios underline that reorienting public support toward farm investment would further intensify dairy farms and increase their income, but would reduce production and income of suckler cow farms and favor crop production (S2). Climate change impact per unit of product is more strongly reduced in S3 (organic farming with low feed concentrate) than in S2, but with a reduced production, particularly for milk. A carbon tax decreases emissions, but to the detriment of cattle production, especially suckler cow farms.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.006
      Issue No: Vol. 157 (2017)
  • Orfee: A bio-economic model to simulate integrated and intensive
           management of mixed crop-livestock farms and their greenhouse gas
    • Authors: Claire Mosnier; Anne Duclos; Jacques Agabriel; Armelle Gac
      Pages: 202 - 215
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Claire Mosnier, Anne Duclos, Jacques Agabriel, Armelle Gac
      How do we plan future sustainable livestock farming systems' Some argue that intensive, specialized systems are more efficient and emit fewer pollutants; others claim that integrated, diversified farming systems are more beneficial to both society and the environment. Bio-economic farm models can help decision-makers and researchers analyze the trade-offs among the numerous possibilities, and direct future livestock production toward greater sustainability. The Orfee model described and evaluated here was developed with this aim. It covers a broad range of beef and dairy systems and forage and crop production alternatives that may be managed with varying levels of intensity (breed, production objective, crop operations, etc.) and integration (crop rotation, organic fertilization, calving period, animal diets, etc.). Capital is also included in the optimization process, with trade-offs between production, labor, machinery and buildings. Environmental impact is assessed through potential impact on climate change.

      PubDate: 2017-08-28T02:14:18Z
      DOI: 10.1016/j.agsy.2017.07.005
      Issue No: Vol. 157 (2017)
  • Assessing local and regional economic impacts of climatic extremes and
           feasibility of adaptation measures in Dutch arable farming systems
    • Authors: V. Diogo; P. Reidsma; B. Schaap; B.P.J. Andree; E. Koomen
      Pages: 216 - 229
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): V. Diogo, P. Reidsma, B. Schaap, B.P.J. Andree, E. Koomen
      We propose a method that combines local productivity factors, economic factors, crop-specific sensitivity to climatic extremes, and future climate change scenarios, to assess potential impacts of extreme weather events on agricultural production systems. Our assessment is spatially explicit and uses discounted time series of cash flows taking into account expected future impacts on yield and crop quality, to estimate changes in the expected net present value (NPV) of agricultural systems. We assess the economic feasibility of a portfolio of adaptation measures by considering their initial investments, annual costs, and effectiveness in reducing crop damage. We apply the method to investigate potential economic impacts of extreme weather events in arable farming systems in the Netherlands around 2050. We find that the expected increase in extreme weather events frequency can severely affect future productivity potential. Particularly, heat waves, warm winters, and high intensity rainfall are expected to substantially undermine the future economic viability of Dutch arable farming systems. The results indicate considerable differences between regions in terms of vulnerability to climatic extremes: while some regions are severely impacted by all climatic extremes, other regions consistently demonstrate high resilience to increases in extreme event frequency. The findings are robust to a wide range of scenarios and suggest that the interactions between economic factors and management practices (particularly, crop specialisation) are decisive drivers of the economic viability of agricultural systems under more frequent climatic extremes. However, the exact magnitude of the impacts remains highly uncertain, as we do not consider endogenous interactions in market conditions resulting from climate change and socio-economic developments. Nevertheless, crop adaptation measures should be regarded as no-regret strategies, since they alleviate both economic impacts and uncertainty around impact magnitude. The proposed method provides insights in region-specific threats and opportunities that are relevant for stakeholders and policy-makers. This information improves communication on main climate risks at the local and regional levels and contributes to prioritising adaptation strategies.

      PubDate: 2017-08-28T02:14:18Z
      DOI: 10.1016/j.agsy.2017.06.013
      Issue No: Vol. 157 (2017)
  • Expert based model building to quantify risk factors in a combined
           aquaculture-agriculture system
    • Authors: Ben Stewart-Koster; Nguyen Dieu Anh; Michele A. Burford; Jason Condon; Nguyen Van Qui; Le Huu Hiep; Doan Van Bay; Jesmond Sammut
      Pages: 230 - 240
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Ben Stewart-Koster, Nguyen Dieu Anh, Michele A. Burford, Jason Condon, Nguyen Van Qui, Le Huu Hiep, Doan Van Bay, Jesmond Sammut
      In recent years, across tropical regions of the world, there has been an expansion of integrated farming systems that combine rice and shrimp production. While these systems were developed as a form of crop-rotation – growing rice in the wet season and shrimp in the dry season – some farmers grow both rice and brackish-water shrimp simultaneously during the wet season. Climatic variability has resulted in considerable crop losses in this system across many regions. Research has yet to identify the complete array of key risk factors, and their potential interactions, for integrated rice-shrimp farming. Consequently, different farming practices and environmental factors that may affect crop production need to be clarified to guide research efforts. We applied a staged, iterative process to develop a probabilistic Bayesian belief network based on expert knowledge that describes the relationships that contribute to the risk of failure of both crops in integrated rice-shrimp farming systems during the wet season. We applied the approach in the Southern Mekong Delta, Vietnam, in the context of a broader research program into the sustainability of the rice-shrimp farming system. The resulting network represents the experts' perceptions of the key risk factors to production and the interactions among them. While both farmers and extension officers contributed to the identification of the processes included in the network, the farmers alone provided estimates of the probability of the relationships among them. The network identified the challenges to minimise the risk of failure for both crops, and the steps farmers can take to mitigate some of them. Overall, farmers perceived they have a better chance to minimise risk of failure for shrimp rather than rice crops, and limited opportunities appear to exist for successful production of both. By engaging the farmers in this process of model development, we were able to identify additional research questions for the broader research team and to identify simple steps the farmers could take to reduce the risk of crop failure. Integrating additional empirical data into this network, as it becomes available, will help identify clear opportunities for improvements in farming practices which should reduce the risk of crop failure into the future.

      PubDate: 2017-08-28T02:14:18Z
      DOI: 10.1016/j.agsy.2017.08.001
      Issue No: Vol. 157 (2017)
  • Projected impact of future climate conditions on the agronomic and
           environmental performance of Canadian dairy farms
    • Authors: Marie-Noëlle Thivierge; Guillaume Jégo; Gilles Bélanger; Martin H. Chantigny; C. Alan Rotz; Édith Charbonneau; Vern S. Baron; Budong Qian
      Pages: 241 - 257
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Marie-Noëlle Thivierge, Guillaume Jégo, Gilles Bélanger, Martin H. Chantigny, C. Alan Rotz, Édith Charbonneau, Vern S. Baron, Budong Qian
      Climate change is expected to increase agricultural productivity in Canada and in other northern countries but this increase will likely affect the environmental performance of dairy farms, one of the most important agricultural sectors in Canada. The objective of this study was to project the impact of climate change on the agronomic and environmental performance of a virtual dairy farm in each of three climatically contrasting areas of Canada through near future (2020–2049) and distant future (2050–2079) periods, using the Integrated Farm System Model (IFSM) and three climate models (CanESM2, CanRCM4, and HadGEM2). Under future climate conditions and relative to a reference period (1971–2000), projected yields of perennial forages and warm-season crops increased, whereas those of small-grain cereals decreased slightly. Projected ammonia emissions increased on virtual farms of the three areas and in all future scenarios (+18% to +54%). Methane emissions from manure storage increased (+26% to +120%), whereas those from enteric fermentation and field manure application decreased. Projected farm N2O emissions changed only slightly relative to the reference period. Fossil fuel CO2 emissions related to field operations increased slightly, due to a larger number of forage cuts per year in future scenarios, but CO2 emissions related to grain drying decreased substantially. Projected losses of P increased on virtual farms of the three areas. The projected reactive N footprint of dairy farms in future scenarios varied more (−15% to +46%) relative to the reference period than the C footprint (−5% to +9%). Although greenhouse gas mitigation should be a priority for dairy farms under future climate conditions, it should not overshadow the need for strategies to reduce reactive N losses.

      PubDate: 2017-08-28T02:14:18Z
      DOI: 10.1016/j.agsy.2017.07.003
      Issue No: Vol. 157 (2017)
  • Introduction to the Farming Systems Design Special Issue
    • Authors: Jacques Wery
      First page: 269
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Jacques Wery

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2017.09.003
      Issue No: Vol. 157 (2017)
  • Replacing silage maize for biogas production by sugar beet – A system
           analysis with ecological and economical approaches
    • Authors: Anna Jacobs; Sebastian Auburger; Enno Bahrs; Wiebke Brauer-Siebrecht; Olaf Christen; Philipp Götze; Heinz-Josef Koch; Oliver Mußhoff; Jan Rücknagel; Bernward Märländer
      Pages: 270 - 278
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Anna Jacobs, Sebastian Auburger, Enno Bahrs, Wiebke Brauer-Siebrecht, Olaf Christen, Philipp Götze, Heinz-Josef Koch, Oliver Mußhoff, Jan Rücknagel, Bernward Märländer
      In a holistic methodological approach, we linked field trial data with different modeling approaches to answer the question if sugar beet roots offer an ecological and economical efficient alternative to silage maize as a substrate for biogas production. Field trials were conducted at highly productive sites in Germany, representative for Central Europe, and tested both biomass crops in continuous cultivation and in crop rotations with winter wheat. In these trials, estimated methane yield of silage maize was generally higher (6837 to 8782Nm3 ha−1 a−1) than of sugar beet roots (3206 to 7861Nm3 ha−1 a−1) and both biomass crops reached highest yield in crop rotations. Under the nonobservance of technical effects, substrate production costs (€ per Nm3 methane) were higher for sugar beet roots and a nationwide modeling showed that, in most of the German districts, it would need to be reduced by 10 to 25% in order to reach economical competitiveness with silage maize. However, at a farm level, sugar beet for biogas production was economically advantageous when introduced with a share of 10 to 16% into the individual farm's cultivation program mainly due to high yield stability reducing the economical risk. However, a decrease in gross margin (€ ha−1) was likely to occur. In the field trials, different ecological impacts of crop cultivation were assessed but did not highlight one of the two biomass crops in comparison. However, it was evident that cultivating them in three years long crop rotations with two years of winter wheat provoked lower risks of loss of soil organic matter (−122 to −20kg humus-C ha−1 a−1) or N-leaching (40 to 62kgNha−1 in three years) than in continuous cultivation. In contrast, the continuous cultivation of silage maize and sugar beet showed lower greenhouse gas emission (7652 to 11,074kg C-dioxide-equivalents ha−1 in three years) than the crop rotations with winter wheat. Overall, we conclude that sugar beet roots can offer an efficient alternative to silage maize as a substrate for biogas production. However, to raise sugar beet's competitiveness, dry matter yields should be increased without increasing production costs and ecological impacts.

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2016.10.004
      Issue No: Vol. 157 (2017)
  • Adaptive and dynamic decision-making processes: A conceptual model of
           production systems on Indian farms
    • Authors: Marion Robert; Alban Thomas; Muddu Sekhar; Shrinivas Badiger; Laurent Ruiz; Hélène Raynal; Jacques-Eric Bergez
      Pages: 279 - 291
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Marion Robert, Alban Thomas, Muddu Sekhar, Shrinivas Badiger, Laurent Ruiz, Hélène Raynal, Jacques-Eric Bergez
      Farming systems are complex structures with several dimensions interacting in a dynamic and continuous manner around farmers' management strategies. This complexity peaks in semi-arid regions of India, where small farms encounter a highly competitive environment for markets and resources, especially unreliable access to water from rainfall and irrigation. To represent such strategies, we propose the conceptual model NAMASTE, which was conceived and based on data collected in the Berambadi watershed in southern India. The most relevant and novel aspects of NAMASTE are i) the system-based representation of farm production systems, ii) the description of dynamic processes through management flexibility and adaptation, and iii) the representation of steps in farmers' decision-making processes at various temporal and spatial scales. Since NAMASTE was designed in an extreme case of highly vulnerable agriculture, its generic framework and formalisms can be used to conceptually represent many other farm production systems.

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2016.08.001
      Issue No: Vol. 157 (2017)
  • Trade-offs in soil fertility management on arable farms
    • Authors: Jules F.F.P. Bos; Hein F.M. ten Berge; Jan Verhagen; Martin K. van Ittersum
      Pages: 292 - 302
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Jules F.F.P. Bos, Hein F.M. ten Berge, Jan Verhagen, Martin K. van Ittersum
      Crop production and soil fertility management implies a multitude of decisions and activities on crop choice, rotation design and nutrient management. In practice, the choices to be made and the resulting outcomes are subject to a wide range of objectives and constraints. Objectives are economic as well as environmental, for instance sequestering carbon in agricultural soils or reducing nitrogen losses. Constraints originate from biophysical and institutional conditions that may restrict the possibilities for choosing crops or using specific cultivation and fertilization practices. To explore the consequences of management interventions to increase the supply of organic C to the soil on income and N losses, we developed the linear programming model NutMatch. The novelty of the model is the coherent description of mutual interdependencies amongst a broad range of sustainability indicators related to soil fertility management in arable cropping, enabling the quantification of synergies and trade-offs between objectives. NutMatch was applied to four different crop rotations subjected to four fertiliser strategies differing in the use of the organic fertilisers cattle slurry, pig slurry or compost, next to mineral fertiliser. Each combination of rotation and fertiliser strategy contributed differently to financial return, N emissions and organic matter inputs into the soil. Our model calculations show that, at the rotational level, crop residues, cattle slurry and compost each substantially contributed to SOC accumulation (range 200-450 kg C ha-1 yr-1), while contributions of pig slurry and cover crops were small (20-50 kg C ha-1 yr-1). The use of compost and pig slurry resulted in increases of 0.61-0.73 and 3.15-3.38 kg N2O-N per 100 kg extra SOC accumulated, respectively, with the other fertilizers taking an intermediate position. From a GHG emission perspective, the maximum acceptable increase is 0.75 kg N2O-N per 100 kg extra SOC accumulated, which was only met by compost. Doubling the winter wheat area combined with the cultivation of cover crops to increase SOC accumulation resulted in a net GHG emission benefit, but was associated with a financial trade-off of 2.30-3.30 euro per kg SOC gained. Our model calculations suggest that trade-offs between C inputs and emissions of greenhouse gases (notably N2O) or other pollutants (NO3, NH3) can be substantial. Due to the many data from a large variety of sources incorporated in the model, the trade-offs are uncertain. Our model-based explorations provide insight in soil carbon sequestration options and their limitations vis-a-vis other objectives.

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2016.09.013
      Issue No: Vol. 157 (2017)
  • Spatial modelling of agro-ecosystem dynamics across scales: A case in the
           cotton region of West-Burkina Faso
    • Authors: Camille Jahel; Christian Baron; Eric Vall; Medina Karambiri; Mathieu Castets; Kalifa Coulibaly; Agnès Bégué; Danny Lo Seen
      Pages: 303 - 315
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Camille Jahel, Christian Baron, Eric Vall, Medina Karambiri, Mathieu Castets, Kalifa Coulibaly, Agnès Bégué, Danny Lo Seen
      Models are increasingly being used to investigate agro-ecosystems dynamics, although processes interacting at different scales remain difficult to consider. When upscaled or downscaled based on aggregation or disaggregation methods, information is generally distorted. This study explores agro-ecosystem modelling using an interaction graph-based modelling approach that explicitly link elements at different scales without up or downscaling. The study area/time frame is the cotton region of West Burkina Faso over the last fifteen years. Field, plot, farm and climate entities are linked in graphs that evolve according to functions computed along different time steps. Three main processes and their interrelations are simulated, occurring at different spatial and temporal scales: crop area expansion, crop rotation and crop production. Three simulation examples are presented to illustrate the analytical possibilities allowed by the approach. These examples test i) the geographical distribution of plots as a means to face climatic risks, ii) the effect of fallowing practice in a spatially constrained cotton dominated landscape and iii) the consequences of reduced access to credit for farmers to buy fertilizers. Model outputs enable quantifying and mapping the respective effects of processes at different scales. Results show that modelling across scales is achievable without resorting to methods of aggregation or disaggregation, which opens new perspectives in multi-scalar analyses of agro-ecosystems that link land production and land use and land cover.

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2016.05.016
      Issue No: Vol. 157 (2017)
  • A framework for designing multi-functional agricultural landscapes:
           Application to Guadeloupe Island
    • Authors: Pierre Chopin; Jean-Marc Blazy; Loïc Guindé; Jacques Wery; Thierry Doré
      Pages: 316 - 329
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Pierre Chopin, Jean-Marc Blazy, Loïc Guindé, Jacques Wery, Thierry Doré
      To improve agriculture faced with regional sustainability issues, agricultural landscapes providing a diversity and high level of ecosystem services are necessary. We have developed and tested the MOSAICA-f framework to build innovative multi-functional agricultural landscapes that can consider explicitly: 1) the performance of cropping systems at the field scale, 2) farmers' decision processes on the adoption of cropping systems, and 3) possible scenarios for innovations and policy changes at the regional scale. This framework is based on a scenario approach that encompasses normative, exploratory and optimized scenarios to assess the relevance of combinations of new agricultural policies, changes to the external context (market and regulations) and innovations in cropping systems. The impacts of these changes on sustainability issues are simulated using the regional bioeconomic model MOSAICA for farmers' decision processes regarding the adoption of cropping systems at the field scale throughout a region. Applied in Guadeloupe (French West Indies), the MOSAICA-f framework enabled the design of a scenario increasing agricultural added value, food and energy self-sufficiency, employment and the quality of water bodies and reducing greenhouse gas emissions. This sustainable scenario combines new cropping systems tuned to farm types with a reorientation of subsidies, an increased workforce and banning food crop production on polluted soils. It can be used to understand the potential contribution of agriculture to sustainability issues and to help local decision makers define policies that will account for the spatial diversities of farms and fields in a landscape. Beyond the design of such a win-win scenario, MOSAICA-f has revealed trade-offs in the provision of services by agriculture.

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2016.10.003
      Issue No: Vol. 157 (2017)
  • Designing coupled innovations for the sustainability transition of
           agrifood systems
    • Authors: Jean-Marc Meynard; Marie-Hélène Jeuffroy; Marianne Le Bail; Amélie Lefèvre; Marie-Benoit Magrini; Camille Michon
      Pages: 330 - 339
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): Jean-Marc Meynard, Marie-Hélène Jeuffroy, Marianne Le Bail, Amélie Lefèvre, Marie-Benoit Magrini, Camille Michon
      Numerous signs underline an urgent need for innovation in the current agriculture and food industries. However, even though the components of the agrifood systems are all strongly interconnected, the design processes to improve their sustainabilities are still mostly managed separately. This frequently leads to innovating in one domain in order to adapt to the constraints or specifications of the other, such as tweaking the farming systems to address processing issues, or the other way round. The objectives of this paper are first to show the limits of such an organization, and second to provide a heuristic framework to organize the design of coupled innovations, by reconnecting the dynamics of innovation in agriculture and food, with a view to improving the whole agrifood system. Our framework highlights that working at this level requires designing in raw production, exchange, processing, and consumption, while taking into account synergies or antagonisms between upstream and downstream. Thus, the innovations are not only technological – e.g. concerning cropping systems or processing – but also organizational and institutional. Based on several examples, in the cereal, linseed, legume, and market-gardening productions, at the junction of agriculture and food sciences, we also show that this perspective of designing coupled innovations calls for a renewed research agenda. Three main domains are thus questioned. First, coupling requires an innovative design process for radical innovations, challenging the coordination of exploration in both domains. Second, the development of “innovation niches” outside the dominant sociotechnical regime, in order to bypass the lock-in from the dominant system, faces the difficulty of favoring the building of renewed networks of actors, which were used to working separately so far. Third, the necessity to share expectations and knowledge, and to design together innovations that suit all sides, leads to making several recommendations for the governance of the design process. Finally, we conclude that the need for innovation in the agrifood systems requires going beyond the historical specialization of skills, and the usual forms of coordination between designers.

      PubDate: 2017-09-23T05:41:12Z
      DOI: 10.1016/j.agsy.2016.08.002
      Issue No: Vol. 157 (2017)
  • Environmental impact assessment of double- and relay-cropping with winter
           camelina in the northern Great Plains, USA
    • Authors: Marisol Berti; Burton Johnson; David Ripplinger; Russ Gesch; Alfredo Aponte
      Pages: 1 - 12
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Marisol Berti, Burton Johnson, David Ripplinger, Russ Gesch, Alfredo Aponte
      Recent findings indicate that double- or relay-cropping winter camelina (Camelina sativa L. Crantz.) with, forage, or food crops can increase yield per area, improve energy balance, and provide several ecosystem services. Double-cropping can help balance food and energy production. The objective of this study was to determine the environmental impact of double- and relay-cropping systems as compared with monocultured maize (Zea mays L.) and soybean [Glycine max (L.) Merr.] in the Midwest, USA. Ten crop sequences composed of double- and relay-cropped forage sorghum [Sorghum bicolor (L.) Moench.] and soybean with winter camelina were evaluated and compared with their monoculture counterparts. The environmental aspects evaluated included global warming potential (GWP), abiotic depletion, acidification, eutrophication, ecotoxicity, and human toxicity. Additionally, provisioning and regulating ecosystem services were estimated, including: primary aboveground productivity, soil erosion, and biodiversity in each crop sequence. The analysis was conducted from ‘cradle-to-gate’, including only the agricultural phase. Global warming potential estimated by three different methods indicated that winter camelina as a monocrop had a GWP of 579 to 922kgCO2e ha−1. Maize in monoculture had higher GWP than all other double- and relay-cropping systems studied. The higher emissions of double- and relay-cropping systems and maize can be explained by higher N fertilizer application, which led to greater field N2O emissions. Also, the additional sowing and harvesting of the double- or relay-crop increased CO2 emissions due to increased diesel use. Winter camelina as a monocrop had the lowest values in all impact categories, indicating camelina agricultural production phase has low environmental impact compared with maize and soybean in monoculture. Double- and relay- cropping systems increased primary productivity per unit area and biodiversity and reduced soil erosion potential. Increasing productivity with the additional environmental benefits of these systems may encourage more farmers to adopt sustainable agricultural practices.

      PubDate: 2017-06-02T15:54:20Z
      DOI: 10.1016/j.agsy.2017.05.012
      Issue No: Vol. 156 (2017)
  • A quantitative value chain analysis of policy options for the beef sector
           in Botswana
    • Authors: Kanar Dizyee; Derek Baker; Karl M. Rich
      Pages: 13 - 24
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Kanar Dizyee, Derek Baker, Karl M. Rich
      The liberalization of beef exports in Botswana is hotly debated among policy makers and relevant value chain actors. While some policy makers argue that such a move might increase prices for producers and make beef unaffordable for consumers, others suggest an open market would reduce the profitability of the beef sector in Botswana. At the same time, these impacts will be mediated by the presence of animal disease and the availability of sufficient feed and water. In this paper, we constructed an integrated system dynamics (SD) model that captures the feedbacks between the biological dynamics of cattle production, the economics of animal and meat marketing and trade, and the impacts that environmental pressures such as rainfall and animal disease have on the system. We used this model to run a series of scenarios associated with market liberalization and animal health shocks to quantify their impacts throughout the value chain, taking into account the feedbacks between biology, markets, and environment on the value chain itself. This approach allows for a holistic evaluation of policy options on different chain actors and whole chain performance, and provides a knowledge base for prioritizing interventions. Model results suggested that although disease control policies benefit all value chain actors, gains from market liberalization come at the expense of substantial losses to Botswana Meat Commission (BMC) and its contracted feedlots. They also suggest that combining market liberalization policy reforms with better animal disease controls greatly improved the financial performance of all value chain actors.

      PubDate: 2017-06-02T15:54:20Z
      DOI: 10.1016/j.agsy.2017.05.007
      Issue No: Vol. 156 (2017)
  • Benchmarking nutrient use efficiency of dairy farms: The effect of
           epistemic uncertainty
    • Authors: W. Mu; E.A. Groen; C.E. van Middelaar; E.A.M. Bokkers; S. Hennart; D. Stilmant; I.J.M. de Boer
      Pages: 25 - 33
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): W. Mu, E.A. Groen, C.E. van Middelaar, E.A.M. Bokkers, S. Hennart, D. Stilmant, I.J.M. de Boer
      The nutrient use efficiency (NUE) of a system, generally computed as the amount of nutrients in valuable outputs over the amount of nutrients in all inputs, is commonly used to benchmark the environmental performance of dairy farms. Benchmarking the NUE of farms, however, may lead to biased conclusions because of differences in major decisive characteristics between farms, such as soil type and production intensity, and because of epistemic uncertainty of input parameters caused by errors in measurement devices or observations. This study aimed to benchmark the nitrogen use efficiency (NUEN; calculated as N output per unit of N input) of farm clusters with similar characteristics while including epistemic uncertainty, using Monte Carlo simulation. Subsequently, the uncertainty of the parameters explaining most of the output variance was reduced to examine if this would improve benchmarking results. Farms in cluster 1 (n=15) were located on sandy soils and farms in cluster 2 (n=17) on loamy soils. Cluster 1 farms were more intensive in terms of milk production per hectare and per cow, had less grazing hours, and fed more concentrates compared to farms in cluster 2. The mean NUEN of farm in cluster 1 was 43%, while in cluster 2 it was 26%. Input parameters that explained most of the output variance differed between clusters. For cluster 1, input of feed and output of roughage were most important, whereas for cluster 2, the input of mineral fertilizer (or fixation) was most important. For both clusters, the output of milk was relatively important. Including the epistemic uncertainty of input parameters showed that only 37% of the farms in cluster 1 (out of 105 mutual comparisons) differed significantly in terms of their NUEN, whereas in cluster 2 this was 82% (out of 120 comparisons). Therefore, benchmarking NUEN of farms in cluster 1 was no longer possible, whereas farms in cluster 2 could still be ranked when uncertainty was included. After reducing the uncertainties of the most important parameters, 72% of the farms in cluster 1 differed significantly in terms of their NUEN, and in cluster 2 this was 87%. Results indicate that reducing epistemic uncertainty of input parameters can significantly improve benchmarking results. The method presented in this study, therefore, can be used to draw more reliable conclusions regarding benchmarking the NUE of farms, and to identify the parameters that require more precision to do so.

      PubDate: 2017-06-02T15:54:20Z
      DOI: 10.1016/j.agsy.2017.04.001
      Issue No: Vol. 156 (2017)
  • Low-input dairy farming in Europe: Exploring a context-specific notion
    • Authors: J. Bijttebier; J. Hamerlinck; S. Moakes; N. Scollan; J. Van Meensel; L. Lauwers
      Pages: 43 - 51
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): J. Bijttebier, J. Hamerlinck, S. Moakes, N. Scollan, J. Van Meensel, L. Lauwers
      Frequently acknowledged as coming forward to environmental issues by reducing external input use, low input (LI) dairy farming is gaining attention. The absence of a clearly delineated description of LI dairying, however, hampers identification and analysis of these farming systems. This paper aims at empirically examining, EU wide, the farm structure, production intensity and productivity of LI with respect to their high input (HI) conventional counterpart and to organic dairying (ORG). A pragmatic quartiles-based categorization of farms from the Farm Accountancy Data Network of 20 important EU dairy countries, with the value of external input costs per grazing livestock unit (GLU) is used as prior discriminating indicator between LI and HI. LI dairy farms are smaller than HI dairy farms, in particular when farm size is expressed as total farm capital. Other variables that differentiate between LI and HI in most countries are number of dairy cows per GLU and area of forage and grassland on total agricultural area. Partial productivities in HI farms exceed those in LI farms, most apparent is milk production per cow. Differentiation of forage production between LI and HI is less uniform throughout Europe. A pairwise matching of differentiation profiles between countries indicates that differentiation between LI and HI is country specific. A similar diversity in country-specific differentiation between ORG and LI farming is found.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.016
      Issue No: Vol. 156 (2017)
  • Climate change impacts on EU agriculture: A regionalized perspective
           taking into account market-driven adjustments
    • Authors: María Blanco; Fabien Ramos; Benjamin Van Doorslaer; Pilar Martínez; Davide Fumagalli; Andrej Ceglar; Francisco J. Fernández
      Pages: 52 - 66
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): María Blanco, Fabien Ramos, Benjamin Van Doorslaer, Pilar Martínez, Davide Fumagalli, Andrej Ceglar, Francisco J. Fernández
      The biophysical and economic consequences of climate change for agriculture are surrounded by uncertainties. The evaluation of climate change impacts on global and regional agriculture has been studied at length. In most cases, however, global and regional impacts are examined separately. Here we present a regionalized assessment – for the 2030 time horizon – covering the whole European Union while accounting for market feedback through international markets. To account for uncertainty on climate effects, we defined several simulation scenarios that differ as to climate projections and assumptions on the degree of carbon fertilization. Biophysical simulations show that crop productivity effects are largely determined by the degree of carbon fertilization, leading to decreased productivity in the absence of carbon fertilization and increased productivity otherwise. The magnitude of those effects differs across regions and crops, with maize being one of the most negatively affected in the EU. Economic simulations show that, while, on the whole, crop price effects attenuate the global impacts of climate change, aggregate results conceal significant regional disparities and their related trade adjustment. These results suggest that a multi-scale perspective is helpful for assessing climate change impacts on agriculture, as it will improve understanding of how regional and global agrifood markets respond to climate change and how these responses interact with each other.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.013
      Issue No: Vol. 156 (2017)
  • The role of soils in the analysis of potential agricultural production: A
           case study in Lebanon
    • Authors: A. Bonfante; M.H. Sellami; M.T. Abi Saab; R. Albrizio; A. Basile; S. Fahed; P. Giorio; G. Langella; E. Monaco; J. Bouma
      Pages: 67 - 75
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): A. Bonfante, M.H. Sellami, M.T. Abi Saab, R. Albrizio, A. Basile, S. Fahed, P. Giorio, G. Langella, E. Monaco, J. Bouma
      Maintaining cereal production in the Bekaa valley in Lebanon presents a serious challenge. Lack of water is the driving force of agricultural research which is mainly focused on introduction of drought resistant cultivars, application of conservation tillage and supplemental irrigation. In this context forty-eight experimental plots were laid out for three years in a statistical split plot design. The statistical analyses showed that aboveground biomass and yield were significantly affected by irrigation for barley but not for the yield of durum wheat. Effects of soil tillage practices and introduction of new cultivares were not significant. A soil survey indicated that the implicit assumption of soil homogeneity of the agronomic design was correct for surface soil but that two different soil types (Cambisols and Fluvisols) had to be distinguished considering subsoil conditions and corresponding rooting patterns. Therefore, the main objective of this paper was to determine the effects of different soil types on crop response and, in addition, to assess how physically-based modeling can predict future effects of climate change on crops and soils. Simulation model SWAP was validated for local conditions using measurements of soil water contents, aboveground biomass and yield of wheat. Considering two rather than one soil type for the experimental area resulted in different conclusions for both crops as to the effectivity of both conservation tillage and irrigation, demonstrating that a distinction of only one soil type results in misleading results. The validated model was applied to estimate yields considering climate change, focusing on the application of supplemental irrigation. Yields for “Mikii3” a durum wheat cultivar are expected to increase by appr. 14% in both soils due to climate change. More importantly, only 3 supplemental irrigations would be needed for the deep soil requiring 5% more water as compared with current climate trend, while the shallow soil needs 13 irrigations, corresponding with a need for 35% more water. This is highly significant from an economic point of view and supports the relevance of distinguishing two soil types. It was demonstrated the synergy of joint research by the agronomic and soil science community and the need for executing a soil survey in future when planning agronomic experiments, including a hydrological soil characterisation.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.018
      Issue No: Vol. 156 (2017)
  • Mapping regional risks from climate change for rainfed rice cultivation in
    • Authors: Kuntal Singh; Colin J. McClean; Patrick Büker; Sue E. Hartley; Jane K. Hill
      Pages: 76 - 84
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Kuntal Singh, Colin J. McClean, Patrick Büker, Sue E. Hartley, Jane K. Hill
      Global warming is predicted to increase in the future, with detrimental consequences for rainfed crops that are dependent on natural rainfall (i.e. non-irrigated). Given that many crops grown under rainfed conditions support the livelihoods of low-income farmers, it is important to highlight the vulnerability of rainfed areas to climate change in order to anticipate potential risks to food security. In this paper, we focus on India, where ~50% of rice is grown under rainfed conditions, and we employ statistical models (climate envelope models (CEMs) and boosted regression trees (BRTs)) to map changes in climate suitability for rainfed rice cultivation at a regional level (~18×18km cell resolution) under projected future (2050) climate change (IPCC RCPs 2.6 and 8.5, using three GCMs: BCC-CSM1.1, MIROC-ESM-CHEM, and HadGEM2-ES). We quantify the occurrence of rice (whether or not rainfed rice is commonly grown, using CEMs) and rice extent (area under cultivation, using BRTs) during the summer monsoon in relation to four climate variables that affect rice growth and yield namely ratio of precipitation to evapotranspiration (PER), maximum and minimum temperatures (T max and T min ), and total rainfall during harvesting. Our models described the occurrence and extent of rice very well (CEMs for occurrence, ensemble AUC=0.92; BRTs for extent, Pearson's r=0.87). PER was the most important predictor of rainfed rice occurrence, and it was positively related to rainfed rice area, but all four climate variables were important for determining the extent of rice cultivation. Our models project that 15%–40% of current rainfed rice growing areas will be at risk (i.e. decline in climate suitability or become completely unsuitable). However, our models project considerable variation across India in the impact of future climate change: eastern and northern India are the locations most at risk, but parts of central and western India may benefit from increased precipitation. Hence our CEM and BRT models agree on the locations most at risk, but there is less consensus about the degree of risk at these locations. Our results help to identify locations where livelihoods of low-income farmers and regional food security may be threatened in the next few decades by climate changes. The use of more drought-resilient rice varieties and better irrigation infrastructure in these regions may help to reduce these impacts and reduce the vulnerability of farmers dependent on rainfed cropping.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.009
      Issue No: Vol. 156 (2017)
  • Inside Front Cover - Editorial Board Page
    • Abstract: Publication date: November 2017
      Source:Agricultural Systems, Volume 158

      PubDate: 2017-10-13T19:09:21Z
  • Inside Front Cover - Editorial Board Page
    • Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157

      PubDate: 2017-09-23T05:41:12Z
  • Classifying multi-model wheat yield impact response surfaces showing
           sensitivity to temperature and precipitation change
    • Authors: Stefan Fronzek; Nina Pirttioja; Timothy R. Carter; Marco Bindi; Holger Hoffmann; Taru Palosuo; Margarita Ruiz-Ramos; Fulu Tao; Miroslav Trnka; Marco Acutis; Senthold Asseng; Piotr Baranowski; Bruno Basso; Per Bodin; Samuel Buis; Davide Cammarano; Paola Deligios; Marie-France Destain; Benjamin Dumont; Frank Ewert; Roberto Ferrise; Louis François; Thomas Gaiser; Petr Hlavinka; Ingrid Jacquemin; Kurt Christian Kersebaum; Chris Kollas; Jaromir Krzyszczak; Ignacio J. Lorite; Julien Minet; M. Ines Minguez; Manuel Montesino; Marco Moriondo; Christoph Müller; Claas Nendel; Isik Öztürk; Alessia Perego; Alfredo Rodríguez; Alex C. Ruane; Françoise Ruget; Mattia Sanna; Mikhail A. Semenov; Cezary Slawinski; Pierre Stratonovitch; Iwan Supit; Katharina Waha; Enli Wang; Lianhai Wu; Zhigan Zhao; Reimund P. Rötter
      Abstract: Publication date: Available online 5 September 2017
      Source:Agricultural Systems
      Author(s): Stefan Fronzek, Nina Pirttioja, Timothy R. Carter, Marco Bindi, Holger Hoffmann, Taru Palosuo, Margarita Ruiz-Ramos, Fulu Tao, Miroslav Trnka, Marco Acutis, Senthold Asseng, Piotr Baranowski, Bruno Basso, Per Bodin, Samuel Buis, Davide Cammarano, Paola Deligios, Marie-France Destain, Benjamin Dumont, Frank Ewert, Roberto Ferrise, Louis François, Thomas Gaiser, Petr Hlavinka, Ingrid Jacquemin, Kurt Christian Kersebaum, Chris Kollas, Jaromir Krzyszczak, Ignacio J. Lorite, Julien Minet, M. Ines Minguez, Manuel Montesino, Marco Moriondo, Christoph Müller, Claas Nendel, Isik Öztürk, Alessia Perego, Alfredo Rodríguez, Alex C. Ruane, Françoise Ruget, Mattia Sanna, Mikhail A. Semenov, Cezary Slawinski, Pierre Stratonovitch, Iwan Supit, Katharina Waha, Enli Wang, Lianhai Wu, Zhigan Zhao, Reimund P. Rötter
      Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

      PubDate: 2017-09-06T11:04:08Z
      DOI: 10.1016/j.agsy.2017.08.004
  • Inside Front Cover - Editorial Board Page
    • Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156

      PubDate: 2017-08-03T13:33:44Z
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
Home (Search)
Subjects A-Z
Publishers A-Z
Your IP address:
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2016