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Showing 1 - 200 of 3043 Journals sorted alphabetically
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 20, SJR: 1.402, h-index: 51)
Academic Radiology     Hybrid Journal   (Followers: 18, SJR: 1.008, h-index: 75)
Accident Analysis & Prevention     Partially Free   (Followers: 83, SJR: 1.109, h-index: 94)
Accounting Forum     Hybrid Journal   (Followers: 23, SJR: 0.612, h-index: 27)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 27, 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: 332, 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: 211, 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: 9, 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: 3)
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: 8, SJR: 1.039, h-index: 5)
Additives for Polymers     Full-text available via subscription   (Followers: 20)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 129, 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: 16, 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: 10, 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: 24, 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: 10, SJR: 1.268, h-index: 45)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 28, 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 Developmental Biology     Full-text available via subscription   (Followers: 11)
Advances in Digestive Medicine     Open Access   (Followers: 4)
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: 40, SJR: 5.465, h-index: 64)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 3)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 8)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 47, SJR: 0.674, h-index: 38)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 15)
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: 21, SJR: 0.906, h-index: 24)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.497, h-index: 31)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 25)
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: 5)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 4)
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: 7, 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: 18)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 19, SJR: 1.5, h-index: 62)
Advances in Psychology     Full-text available via subscription   (Followers: 60)
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: 2, SJR: 0.1, h-index: 2)
Advances in Space Research     Full-text available via subscription   (Followers: 345, 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: 15)
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: 309, 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: 38, 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: 53, 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: 9, SJR: 0.922, h-index: 66)
Alcoholism and Drug Addiction     Open Access   (Followers: 6)
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)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 7, 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: 5)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 3)
American Heart J.     Hybrid Journal   (Followers: 48, SJR: 3.157, h-index: 153)
American J. of Cardiology     Hybrid Journal   (Followers: 45, SJR: 2.063, h-index: 186)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 38, SJR: 0.574, h-index: 65)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 6, SJR: 1.091, h-index: 45)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 16, 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: 24, SJR: 1.259, h-index: 81)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 33, SJR: 2.313, h-index: 172)
American J. of Medicine     Hybrid Journal   (Followers: 46, 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: 191, SJR: 2.255, h-index: 171)
American J. of Ophthalmology     Hybrid Journal   (Followers: 54, SJR: 2.803, h-index: 148)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 3)
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: 23, 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: 21, 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: 55, SJR: 0.124, h-index: 9)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 10)
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: 2, SJR: 2.577, h-index: 7)
Analytica Chimica Acta     Hybrid Journal   (Followers: 38, SJR: 1.548, h-index: 152)
Analytical Biochemistry     Hybrid Journal   (Followers: 162, 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: 158, 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)

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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]
  • 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)
  • 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)
  • Carbon and nitrogen environmental trade-offs of winter rye cellulosic
           biomass in the Chesapeake Watershed
    • Authors: Amanda M. Ramcharan; Tom L. Richard
      Pages: 85 - 94
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Amanda M. Ramcharan, Tom L. Richard
      Cellulosic biomass from winter crops can complement maize stover harvested from maize (Zea mays L.) – soybean (Glycine max L.) rotations. In this study, we assessed on-field environmental impacts related to carbon (C) and nitrogen (N) by modeling representative agro-ecological conditions prevalent in the mid-Atlantic region of the United States. We used the biophysical model Cycles to simulate management scenarios for maize-soybean cropping systems that included winter rye (Secale cereale L.). The model was used to quantify changes in N losses via nitrate leaching (NO3), emissions of nitrous oxide (N2O) and ammonia (NH3), changes in soil organic carbon, and carbon dioxide equivalent emissions per megajoule (CO2eq MJ−1). Including winter rye in the rotation reduced NO3 leaching over a winter fallow control (77% on average), even when the winter rye was fertilized and regardless of whether stover, winter rye, or both cellulosic feedstocks were harvested. Applying fertilizer to winter rye did however increase NO3 leaching as well as NH3 and N2O emissions. Model results consistently showed fertilizing the winter rye improved both biomass yield and soil C levels compared to unfertilized winter rye, regardless of location, soil, fertilizer type or stover harvest. While it is difficult to simultaneously reduce agricultural nitrogen losses, produce renewable energy and increase soil carbon, results can guide management of these trade-offs while tapping into an abundant energy resource and reducing greenhouse gas emissions.
      Graphical abstract image

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.017
      Issue No: Vol. 156 (2017)
  • Lessons learned from the long-term analysis of cacao yield and stand
           structure in central Cameroonian agroforestry systems
    • Authors: Stéphane Saj; Patrick Jagoret; Louis Essola Etoa; Eltson Eteckji Fonkeng; Justin Ngala Tarla; Jean-Daniel Essobo Nieboukaho; Kenneth Mvondo Sakouma
      Pages: 95 - 104
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Stéphane Saj, Patrick Jagoret, Louis Essola Etoa, Eltson Eteckji Fonkeng, Justin Ngala Tarla, Jean-Daniel Essobo Nieboukaho, Kenneth Mvondo Sakouma
      In Sub-Saharan Africa, cacao cultivation is a major driver of deforestation and cacao-producing countries are among the poorest in the world. Two different production schemes compete today: a “land-sharing” strategy supports cacao based agroforestry systems (cAFS) while a “land-sparing” approach advocates for the intensification of these systems. Yet, we believe that a path exists between these two options which could be fruitful, sustainable and ecologically sound for the regions in which cacao is grown. To prove our point we investigated the competition balance, stand structure and accessible yields of 144 cacao-producing plots in cAFS of Central Cameroon. A 100-year chronosequence and a large array of situations, ranging from very simple systems to very complex cAFS were used. We used basal area (BA) ratios of different components of the systems to gauge interspecific competition. We found that yields were highly dependent on the age of the plot, the BA of associated tree community and the structure of the cacao stand. We found that very long-term sustainability could be achieved if the BA share of the cacao stand does not exceed 40% of the total BA of the cAFS. While interspecific competition prevailed, some associated functional groups of woody species were consistently related to higher cacao yields. This may underline putative synergistic - or less damageable - effects on yields for a given range of plantation age and interspecific competition level. The BA of the cacao stand steadily increased with age yet yields did not similarly rise. Hence, our results show that while rejuvenation and densification practices permitted the maintenance of a “baseline” production, these practices needed to be better studied and improved in order to get higher yields - especially for cAFS which are over 40years old. Finally, the high accessible yields found underlined the good production potential of cAFS that is to be reached if a better knowledge of how cAFS function is acquired and if intensification in terms of inputs and/or manpower is undertaken. Such intensification would not compulsorily include cAFS simplification and therefore would, at least partly, facilitate the preservation of the ecosystem services that cAFS support.

      PubDate: 2017-06-16T08:22:47Z
      DOI: 10.1016/j.agsy.2017.06.002
      Issue No: Vol. 156 (2017)
  • Combining environmentally and economically sustainable dairy and beef
           production in Sweden
    • Authors: Anna Hessle; Jan Bertilsson; Bo Stenberg; Karl-Ivar Kumm; Ulf Sonesson
      Pages: 105 - 114
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Anna Hessle, Jan Bertilsson, Bo Stenberg, Karl-Ivar Kumm, Ulf Sonesson
      To achieve a more sustainable food sector, a supply chain approach is needed. In this study, experts in different areas along supply chains co-operated in an interactive process to define future environmentally sustainable supply chains of milk and beef. The basis was to use existing techniques, to have production performance corresponding to the best quartile of today and to consider other sustainability aspects, such as economics. The work resulted in concrete descriptions of alternative product chains for delivered milk and beef. To also permit concrete descriptions of the latter part of the product chains, two consumer-packed end products were selected for monitoring, namely fresh milk and sirloin steak. The production systems investigated comprised cropping, livestock production, industrial processing and production, logistics, packaging and wastage and distribution, but not retailers or consumers. The study area was a Swedish county and the reference level was its production of milk and beef in 2012. The future product chains were assumed to deliver the same amounts of commodities as in 2012, but with reduced environmental impact. Primary production was required to be at least as profitable as today. Beside description of the current situation, three alternative scenarios were created, focusing on delivery of ecosystem services, plant nutrient circulation and minimising climate impact, respectively. Life cycle assessments were performed for these four scenarios (reference plus three alternative scenarios) for single-product chains and county-wide. Furthermore, production costs in primary production were calculated for the four scenarios. The results revealed great potential to reduce the negative environmental impact of Swedish dairy and beef production at current volumes, irrespective of whether ecosystem services, plant nutrient circulation or climate impact is in focus. The single most important factor for decreased environmental impact for livestock production was increased production efficiency. Measures in agriculture, especially concerning feeds, were critical, but actions in processing and distribution also contributed. All alternative scenarios resulted in lower production costs than at present. It was obvious that as dairy and beef systems are connected, the potential for their environmental improvement must be analysed together. In conclusion, increased efficiency can decrease the negative environmental impact of Swedish cattle production and also reduce costs to the farmer.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.06.004
      Issue No: Vol. 156 (2017)
  • Predicting farmer uptake of new agricultural practices: A tool for
           research, extension and policy
    • Authors: Geoff Kuehne; Rick Llewellyn; David J. Pannell; Roger Wilkinson; Perry Dolling; Jackie Ouzman; Mike Ewing
      Pages: 115 - 125
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Geoff Kuehne, Rick Llewellyn, David J. Pannell, Roger Wilkinson, Perry Dolling, Jackie Ouzman, Mike Ewing
      There is much existing knowledge about the factors that influence adoption of new practices in agriculture but few attempts have been made to construct predictive quantitative models of adoption for use by those planning agricultural research, development, extension and policy. ADOPT (Adoption and Diffusion Outcome Prediction Tool) is the result of such an attempt, providing predictions of a practice's likely rate and peak level of adoption as well as estimating the importance of various factors influencing adoption. It employs a conceptual framework that incorporates a range of variables, including variables related to economics, risk, environmental outcomes, farmer networks, characteristics of the farm and the farmer, and the ease and convenience of the new practice. The ability to learn about the relative advantage of the practice, as influenced by characteristics of both the practice and the potential adopters, plays a central role. Users of ADOPT respond to 22 questions related to: a) characteristics of the practice that influence its relative advantage, b) characteristics of the population influencing their perceptions of the relative advantage of the practice, c) characteristics of the practice influencing the ease and speed of learning about it, and d) characteristics of the potential adopters that influence their ability to learn about the practice. ADOPT provides a prediction of the diffusion curve of the practice and sensitivity analyses of the factors influencing the speed and peak level of adoption. In this paper the model is described and its ability to predict the diffusion of agricultural practices is demonstrated using examples of new crop types, new cropping technology and grazing options. As well as providing predictions, ADOPT is designed to increase the conceptual understanding and consideration of the adoption process by those involved in agricultural research, development, extension and policy.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.06.007
      Issue No: Vol. 156 (2017)
  • Creating an enabling environment for industry-driven pest suppression: The
           case of suppressing Queensland fruit fly through area-wide management
    • Authors: Heleen Kruger
      Pages: 139 - 148
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Heleen Kruger
      Increasing concerns about pests call for the development and uptake of innovative pest management approaches. This coincides with many governments pushing for greater industry self-reliance. This paper investigates how to create a more enabling environment for local industries to suppress Queensland fruit fly (QFly) through industry-driven, area-wide management (AWM). This key recommended approach requires high technical capability and is reliant on cooperation between horticulture growers and other risk contributors, such as town residents, with QFly hosts on their properties. Agriculture Innovation Systems thinking and a functional-structural analysis are applied to the current QFly management innovation system to understand how it constrains or facilitates local industries pursuing AWM. This assists with identifying governance interventions that will support local industries to undertake AWM. Data is derived from semi-structured interviews with key informants from stakeholder groups and a grower survey in three regions where AWM has been achieved or is being attempted. Key blocking mechanisms hindering local industries to pursue AWM have been identified as a lack of local capacity; weak connections between local industries and the broader innovation system; lack of AWM investment; and reliance on voluntary cooperation. Suggestions for policy interventions include supporting intermediation; strengthening local capacity and enabling co-regulation.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.05.008
      Issue No: Vol. 156 (2017)
  • Are subsidies to weather-index insurance the best use of public funds'
           A bio-economic farm model applied to the Senegalese groundnut basin
    • Authors: Aymeric Ricome; François Affholder; Françoise Gérard; Bertrand Muller; Charlotte Poeydebat; Philippe Quirion; Moussa Sall
      Pages: 149 - 176
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Aymeric Ricome, François Affholder, Françoise Gérard, Bertrand Muller, Charlotte Poeydebat, Philippe Quirion, Moussa Sall
      While crop yields in Sub-Saharan Africa are low compared to most other parts of the world, weather-index insurance is often presented as a promising tool, which could help resource-poor farmers in developing countries to invest and adopt yield-enhancing technologies. Here, we test this hypothesis on two contrasting areas (in terms of rainfall scarcity) of the Senegalese groundnut basin through the use of a bio-economic farm model, coupling the crop growth model CELSIUS with the economic model ANDERS, both specifically designed for this purpose. We introduce a weather-index insurance whose index is currently being used for pilot projects in Senegal and West Africa. Results show that insurance leads to a welfare gain only for those farmers located in the driest area. These farmers respond to insurance mostly by increasing the amount of cow fattening, which leads to higher crop yields thanks to the larger production of manure. We also find that subsidizing insurance is not the best possible use of public funds: for a given level of public funding, reducing credit rates, subsidizing fertilizers, or just transferring cash as a lump-sum generally brings a higher expected utility to farmers and leads to a higher increase in grain production levels.

      PubDate: 2017-07-02T23:43:15Z
      DOI: 10.1016/j.agsy.2017.05.015
      Issue No: Vol. 156 (2017)
  • Freshwater use in livestock production—To be used for food crops or
           livestock feed?
    • Authors: Ylva Ran; Corina E. van Middelaar; Mats Lannerstad; Mario Herrero; Imke J.M. de Boer
      Pages: 1 - 8
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Ylva Ran, Corina E. van Middelaar, Mats Lannerstad, Mario Herrero, Imke J.M. de Boer
      Current approaches to estimate freshwater use in livestock production systems generally fail to consider the competition for water resources with alternative uses, such as production of food crops food or other ecosystem services. This article presents a new method to account for the competition for freshwater use between food crops and animal feed, while assessing freshwater use in livestock production systems. The developed water use ratio (WUR) is defined as the maximum amount of human digestible protein (HDP) derived from food crops from the consumptive water use (CWU) appropriated to produce 1kg of animal-source food (ASF) over the amount of HDP in that 1kg of ASF. The CWU for livestock production is first categorized according to the land over which it is consumed, based on the suitability of that land to produce food crops. Then, the method assesses food-feed competition by determining the amount of HDP that could have been produced from food crops, using the same CWU currently used to produce ASF. The method enables identification of livestock production systems that contribute to global food supply without competing significantly over water resources with food production, based on their CWU. Three beef production systems in Uruguay are used to illustrate the method. During the backgrounding and the finishing stages, which are analyzed in this study, cattle can be kept on natural pasture (NP), seeded pasture (SP) or in feedlots (FL). The following three systems were analysed: i) NP-NP, ii) SP-SP and iii) SP-FL. Results show that the NP-NP system uses the largest amount of water per kg of beef output. However, results also show that the SP-SP and SP-FL systems can potentially produce more HDP by growing food crops than by producing beef. Based on the traditional measure for water productivity, i.e. the quantity of CWU per kilo of beef produced, we would conclude that the NP-NP system is least efficient, whereas based on the WUR the NP-NP system is the only system producing HDP more efficiently than food crops. Sustainable intensification not only implies improving agriculture and livestock productivity per unit of resource used, but also improving the number of human beings nourished. Results from this study illustrate the importance of considering competition and trade-offs with other uses when evaluating water use efficiency of livestock systems to promote sustainable intensification.

      PubDate: 2017-04-11T18:44:05Z
      DOI: 10.1016/j.agsy.2017.03.008
      Issue No: Vol. 155 (2017)
  • Management options for dairy farms under climate change: Effects of
           intensification, adaptation and simplification on pastures, milk
           production and profitability
    • Authors: Matthew T. Harrison; Brendan R. Cullen; Dan Armstrong
      Pages: 19 - 32
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Matthew T. Harrison, Brendan R. Cullen, Dan Armstrong
      There are few holistic analyses of agricultural systems that inclusively consider how the combination of gradual climate change and increased frequencies of extreme climatic events influence biophysical variables as well as economic returns. Here we examine how climate change to 2040 influences pasture growth rates, grazed pasture harvested (PH) and profitability of three case study (baseline) farms in southern Australia. We applied ‘development options’ (or adaptations) to baseline farms in each region that either intensified, simplified or modified the seasonal distribution of feed supply (Intensify, Simplify or Adapt, respectively) by manipulating several components of the farm system simultaneously, including herd size, liveweight and farm assets. In general, climate change reduced annual pasture produced. On dryland farms, hotter, drier conditions reduced growing durations through later autumn breaks and earlier finishes to spring growth, although winter growth rates were enhanced. On irrigated farms, the magnitude and inter-annual variability of PH was less influenced by climate change. Overall, climate change reduced milk production and income, and increased costs due to additional fodder conservation and more purchased feed. Current climate variability caused far greater inter-annual variation in PH and profit compared with the long-term impacts of climate change. This suggests that farm outcomes may be improved by tactically managing for short-term climatic variability, rather than by making long-term strategic changes in preparation for climate change. Future work on adapting dairy businesses to climate change should examine development options that help maintain or extend growing season length and/or harness the additional winter growth. Our study indicates that climate change impacts on dairy systems will be regionally-specific; no individual development option was universally effective in reducing pasture losses to climate change across regions and development options, and no option consistently increased or decreased PH across sites. Future adaptation strategies should thus take into account not only local climate variability as well as climate change, but also the existing farming systems already operating at each site.

      PubDate: 2017-04-26T00:01:49Z
      DOI: 10.1016/j.agsy.2017.04.003
      Issue No: Vol. 155 (2017)
  • Environmental footprint of the integrated France–Italy beef production
           system assessed through a multi-indicator approach
    • Authors: Marco Berton; Jacques Agabriel; Luigi Gallo; Michel Lherm; Maurizio Ramanzin; Enrico Sturaro
      Pages: 33 - 42
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Marco Berton, Jacques Agabriel, Luigi Gallo, Michel Lherm, Maurizio Ramanzin, Enrico Sturaro
      This study aims to evaluate the environmental footprint of the integrated France–Italy beef production system (extensive grassland-based suckler cow-calf farms in France with intensive cereal-based fattening farms in northeastern Italy) using a multi-indicator approach, which combines environmental impact categories computed with a cradle-to-farm gate Life Cycle Assessment, and food-related indicators based on the conversion of gross energy and protein of feedstuffs into raw boneless beef. The system boundaries were set from the calves' birth to their sale to the slaughterhouse, including the herd management, on- and off-farm feed production and materials used on the farms. One kilogram of body weight (BW) sold was used as the functional unit. The study involved 73 Charolais batches (i.e., a group of animals homogenous for age, finishing period and fattening farm), kept at 14 Italian farms. Data from 40 farms originating from the Charolais Network database (INRA) were used to characterize the French farm types, which were matched to the fattening batches according to the results of a cluster analysis. The impact categories assessed were as follows (mean±SD per kg BW): global warming potential (GWP, 13.0±0.7kg CO2-eq, reduced to 9.9±0.7kg CO2-eq when considering the carbon sequestration due to French suckler cow-calf system permanent grassland), acidification potential (AP, 193±13g SO2-eq), eutrophication potential (EP, 57±4g PO4-eq), cumulative energy demand (CED, 36±5MJ), and land occupation (LO, 18.7±0.8m2/year). The on-farm impacts outweighed those of the off-farm activities, except in the case of CED. On average, 41MJ and 16.7kg of dietary feed gross energy and protein were required to provide 1MJ or 1kg of protein of raw boneless beef, respectively, but nearly 85% and 80%, respectively, were derived from feedstuffs not suitable for human consumption. Emission-related (GWP, AP, EP) and resource utilization categories (CED, LO) were positively correlated. Food-related indicators showed positive correlations with emission-related indicators when the overall feedstuffs of the diet were considered but negative correlations when only the potentially human-edible portions of the beef diets were considered. In conclusion, the integration of the pasture-based France suckler cow-calf system with the cereal-based Italian fattening farms allows for the exploitation of the resources available, increasing the share of non-human-edible feedstuffs while maintaining good livestock productive efficiency. Combining indicators of impact categories with indicators of feed net supply may improve the assessment of the environmental footprint of livestock systems.

      PubDate: 2017-04-26T00:01:49Z
      DOI: 10.1016/j.agsy.2017.04.005
      Issue No: Vol. 155 (2017)
  • Yield gap analyses to estimate attainable bovine milk yields and evaluate
           options to increase production in Ethiopia and India
    • Authors: Dianne Mayberry; Andrew Ash; Di Prestwidge; Cécile M. Godde; Ben Henderson; Alan Duncan; Michael Blummel; Y. Ramana Reddy; Mario Herrero
      Pages: 43 - 51
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Dianne Mayberry, Andrew Ash, Di Prestwidge, Cécile M. Godde, Ben Henderson, Alan Duncan, Michael Blummel, Y. Ramana Reddy, Mario Herrero
      Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields.

      PubDate: 2017-04-26T00:01:49Z
      DOI: 10.1016/j.agsy.2017.04.007
      Issue No: Vol. 155 (2017)
  • Adoption of agroforestry and the impact on household food security among
           farmers in Malawi
    • Authors: Jeanne Y. Coulibaly; Brian Chiputwa; Tebila Nakelse; Godfrey Kundhlande
      Pages: 52 - 69
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Jeanne Y. Coulibaly, Brian Chiputwa, Tebila Nakelse, Godfrey Kundhlande
      Agroforestry is increasingly regarded as an important adaptation and mitigation strategy against climate change. In particular, the use of fertilizer trees has been promoted as a practice that contributes to improved soil fertility through nitrogen fixation, by increasing supply of nutrients for crop production. While a lot of the evidence on the impact of fertilizer trees relies on on-farm experiments and correlational analysis, there is a paucity of rigorous evidence under actual smallholder farming conditions. This paper analyzes the impacts of adopting fertilizer trees such as Gliricidia sepium and Faidherbia albida on household food security. We draw on survey data of 338 farmers in Malawi and use an endogenous switching regression to rigorously analyze adoption impacts. Econometric results show that use of fertilizer tree adoption increases the value of food crops by 35%. Disaggregation of the impacts through stratification by land ownership further reveal that farmers with smaller farms of up to 2 acres realize the highest gains. Furthermore, fertilizer tree use in conjunction with improved maize seed also significantly increased value of food crops. This study offers preliminary insights that contribute to an emerging field of research on quantitative assessment of agricultural interventions such as agroforestry practices using novel analytical approaches. We provide some policy insights and recommend the need for future research to be designed around development initiatives that consider fine-scale variation in social, economic and ecological context of farmers to improve uptake and adaptation to realize the full potential of agroforestry in improving soil fertility and household food security.

      PubDate: 2017-05-03T00:18:45Z
      DOI: 10.1016/j.agsy.2017.03.017
      Issue No: Vol. 155 (2017)
  • Next generation agricultural system data, models and knowledge products:
    • Authors: John M. Antle; James W. Jones; Cynthia E. Rosenzweig
      Pages: 186 - 190
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): John M. Antle, James W. Jones, Cynthia E. Rosenzweig
      Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research investments initially made 30–40years ago, and many of the major advances in data, information and communication technology (ICT) of the past decade have not been fully exploited. The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. The Special Issue is based on a “NextGen” study led by the Agricultural Model Intercomparison and Improvement Project (AgMIP) with support from the Bill and Melinda Gates Foundation.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.003
  • Next generation data systems and knowledge products to support
           agricultural producers and science-based policy decision making
    • Authors: Susan M. Capalbo; John M. Antle; Clark Seavert
      Pages: 191 - 199
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Susan M. Capalbo, John M. Antle, Clark Seavert
      Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa, which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.10.009
  • Towards a new generation of agricultural system data, models and knowledge
           products: Information and communication technology
    • Authors: Sander J.C. Janssen; Cheryl H. Porter; Andrew D. Moore; Ioannis N. Athanasiadis; Ian Foster; James W. Jones; John M. Antle
      Pages: 200 - 212
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Sander J.C. Janssen, Cheryl H. Porter, Andrew D. Moore, Ioannis N. Athanasiadis, Ian Foster, James W. Jones, John M. Antle
      Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner. Our qualitative evaluation suggests that as an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This will enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.017
  • Modelling the impacts of pests and diseases on agricultural systems
    • Authors: M. Donatelli; R.D. Magarey; S. Bregaglio; L. Willocquet; J.P.M. Whish; S. Savary
      Pages: 213 - 224
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): M. Donatelli, R.D. Magarey, S. Bregaglio, L. Willocquet, J.P.M. Whish, S. Savary
      The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.01.019
  • Next generation crop models: A modular approach to model early vegetative
           and reproductive development of the common bean (Phaseolus vulgaris L)
    • Authors: C. Hwang; M.J. Correll; S.A. Gezan; L. Zhang; M.S. Bhakta; C.E. Vallejos; K.J. Boote; J.A. Clavijo-Michelangeli; J.W. Jones
      Pages: 225 - 239
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): C. Hwang, M.J. Correll, S.A. Gezan, L. Zhang, M.S. Bhakta, C.E. Vallejos, K.J. Boote, J.A. Clavijo-Michelangeli, J.W. Jones
      The next generation of gene-based crop models offers the potential of predicting crop vegetative and reproductive development based on genotype and weather data as inputs. Here, we illustrate an approach for developing a dynamic modular gene-based model to simulate changes in main stem node numbers, time to first anthesis, and final node number on the main stem of common bean (Phaseolus vulgaris L.). In the modules, these crop characteristics are functions of relevant genes (quantitative trait loci (QTL)), the environment (E), and QTL×E interactions. The model was based on data from 187 recombinant inbred (RI) genotypes and the two parents grown at five sites (Citra, FL; Palmira, Colombia; Popayan, Colombia; Isabela Puerto Rico; and Prosper, North Dakota). The model consists of three dynamic QTL effect models for node addition rate (NAR, No. d−1), daily rate of progress from emergence toward flowering (RF), and daily maximum main stem node number (MSNODmax), that were integrated to simulate main stem node number vs. time, and date of first flower using daily time steps. Model evaluation with genotypes not used in model development showed reliable predictions across all sites for time to first anthesis (R2 =0.75) and main stem node numbers during the linear phase of node addition (R2 =0.93), while prediction of the final main stem node number was less reliable (R2 =0.27). The use of mixed-effects models to analyze multi-environment data from a wide range of genotypes holds considerable promise for assisting development of dynamic QTL effect models capable of simulating vegetative and reproductive development.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.10.010
  • Brief history of agricultural systems modeling
    • Authors: James W. Jones; John M. Antle; Bruno Basso; Kenneth J. Boote; Richard T. Conant; Ian Foster; H. Charles J. Godfray; Mario Herrero; Richard E. Howitt; Sander Janssen; Brian A. Keating; Rafael Munoz-Carpena; Cheryl H. Porter; Cynthia Rosenzweig; Tim R. Wheeler
      Pages: 240 - 254
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): James W. Jones, John M. Antle, Bruno Basso, Kenneth J. Boote, Richard T. Conant, Ian Foster, H. Charles J. Godfray, Mario Herrero, Richard E. Howitt, Sander Janssen, Brian A. Keating, Rafael Munoz-Carpena, Cheryl H. Porter, Cynthia Rosenzweig, Tim R. Wheeler
      Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the “next generation” models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.05.014
  • Towards a new generation of agricultural system data, models and knowledge
           products: Design and improvement
    • Authors: James W. Jones; John M. Antle; Bruno Basso; Kenneth J. Boote; Richard T. Conant; Ian Foster; H. Charles J. Godfray; Mario Herrero; Richard E. Howitt; Sander Janssen; Brian A. Keating; Rafael Munoz-Carpena; Cheryl H. Porter; Cynthia Rosenzweig; Tim R. Wheeler
      Pages: 269 - 288
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): John M Antle, Bruno Basso, Richard T Conant, H Charles J Godfray, James W Jones, Mario Herrero, Richard E Howitt, Brian A Keating, Rafael Munoz-Carpena, Cynthia Rosenzweig, Pablo Tittonell, Tim R Wheeler
      This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a “pre-competitive” space for model development to a “competitive space” for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.021
  • Toward a new generation of agricultural system data, models, and knowledge
           products: State of agricultural systems science
    • Authors: James W. Jones; John M. Antle; Bruno Basso; Kenneth J. Boote; Richard T. Conant; Ian Foster; H. Charles J. Godfray; Mario Herrero; Richard E. Howitt; Sander Janssen; Brian A. Keating; Rafael Munoz-Carpena; Cheryl H. Porter; Cynthia Rosenzweig; Tim R. Wheeler
      Pages: 269 - 288
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): James W. Jones, John M. Antle, Bruno Basso, Kenneth J. Boote, Richard T. Conant, Ian Foster, H. Charles J. Godfray, Mario Herrero, Richard E. Howitt, Sander Janssen, Brian A. Keating, Rafael Munoz-Carpena, Cheryl H. Porter, Cynthia Rosenzweig, Tim R. Wheeler
      We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.021
  • Inside Front Cover - Editorial Board Page
    • Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156

      PubDate: 2017-08-03T13:33:44Z
  • Characterizing agricultural impacts of recent large-scale US droughts and
           changing technology and management
    • Authors: Joshua Elliott; Michael Glotter; Alex C. Ruane; Kenneth J. Boote; Jerry L. Hatfield; James W. Jones; Cynthia Rosenzweig; Leonard A. Smith; Ian Foster
      Abstract: Publication date: Available online 24 July 2017
      Source:Agricultural Systems
      Author(s): Joshua Elliott, Michael Glotter, Alex C. Ruane, Kenneth J. Boote, Jerry L. Hatfield, James W. Jones, Cynthia Rosenzweig, Leonard A. Smith, Ian Foster
      Process-based agricultural models, applied in novel ways, can reproduce historical crop yield anomalies in the US, with median absolute deviation from observations of 6.7% at national-level and 11% at state-level. In seasons for which drought is the overriding factor, performance is further improved. Historical counterfactual scenarios for the 1988 and 2012 droughts show that changes in agricultural technologies and management have reduced system-level drought sensitivity in US maize production by about 25% in the intervening years. Finally, we estimate the economic costs of the two droughts in terms of insured and uninsured crop losses in each US county (for a total, adjusted for inflation, of $9 billion in 1988 and $21.6 billion in 2012). We compare these with cost estimates from the counterfactual scenarios and with crop indemnity data where available. Model-based measures are capable of accurately reproducing the direct agro-economic losses associated with extreme drought and can be used to characterize and compare events that occurred under very different conditions. This work suggests new approaches to modeling, monitoring, forecasting, and evaluating drought impacts on agriculture, as well as evaluating technological changes to inform adaptation strategies for future climate change and extreme events.

      PubDate: 2017-08-03T13:33:44Z
      DOI: 10.1016/j.agsy.2017.07.012
  • Mitigating nitrous oxide and manure-derived methane emissions by removing
           cows in response to wet soil conditions
    • Authors: T.J. van; der Weerden Laurenson Vogeler P.C. Beukes S.M. Thomas
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): T.J. van der Weerden, S. Laurenson, I. Vogeler, P.C. Beukes, S.M. Thomas, R.M. Rees, C.F.E. Topp, G. Lanigan, C.A.M. de Klein
      In pasture-based grazing systems, urine deposition is the major source of the greenhouse gas nitrous oxide (N2O). Livestock treading damage and high soil water contents increase the risk of N2O emissions. Duration controlled grazing (DCG) practices that are implemented in response to soil water conditions above a threshold may therefore provide an effective means of reducing greenhouse gas (GHG) emissions from dairy farms. The objective of this study was to evaluate the potential decrease in GHG emissions from dairy farms when implementing DCG when soil water content is above a specific threshold (akin to ‘wet’ days). We used the DairyNZ Whole Farm Model and APSIM model to assess the cost-benefit of implementing DCG to reduce total N2O and manure-derived CH4 emissions from dairy farms. We modelled scenarios on poorly drained or imperfectly drained soils in four regions of New Zealand including Waikato, Manawatu, Canterbury and Southland, where the grazing time on wet days was 0, 13, 17 or 21h per day. Emissions were estimated using a refined version of New Zealand's current national greenhouse gas inventory methodology. Our analysis suggested that reducing the grazing time from 21h to 0, 13 or 17h per day when soils were wet could reduce annual N2O and manure-derived CH4 emissions by up to, respectively, 12, 9 or 5% on farms with poorly drained soils. The 13h per day grazing duration was the least costly, particularly if there were >150 ‘wet’ days per year. In contrast, for dairy farms on imperfectly-drained soils, DCG increased emissions, suggesting this management approach for reducing GHG emissions is not suitable for these soils.

      PubDate: 2017-06-22T08:35:16Z
  • Inside Front Cover - Editorial Board Page/Cover image legend if applicable
    • Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155

      PubDate: 2017-06-22T08:35:16Z
  • Next generation agricultural system models and knowledge products:
           Synthesis and strategy
    • Authors: John M. Antle; James W. Jones; Cynthia Rosenzweig
      Abstract: Publication date: Available online 2 June 2017
      Source:Agricultural Systems
      Author(s): John M. Antle, James W. Jones, Cynthia Rosenzweig
      The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. In the Introduction to this Special Issue, we described a vision for accelerating the rate of agricultural innovation and meeting the growing global need for food and fiber. In this concluding article of the NextGen Special Issue we synthesize insights and formulate a strategy to advance data, models, and knowledge products that are consistent with this vision. This strategy is designed to facilitate a transition from the current, primarily supply-driven approach toward a more demand-driven approach that would address key Use Cases where better data, models and knowledge products are seen by end-users as essential to meet their needs.

      PubDate: 2017-06-07T07:54:56Z
      DOI: 10.1016/j.agsy.2017.05.006
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