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  Subjects -> AGRICULTURE (Total: 775 journals)
    - AGRICULTURAL ECONOMICS (77 journals)
    - AGRICULTURE (528 journals)
    - CROP PRODUCTION AND SOIL (91 journals)
    - DAIRYING AND DAIRY PRODUCTS (30 journals)
    - POULTRY AND LIVESTOCK (49 journals)

AGRICULTURE (528 journals)                  1 2 3 | Last

Showing 1 - 200 of 263 Journals sorted alphabetically
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
Acta agriculturae Slovenica     Open Access   (Followers: 4)
Acta Agronomica Hungarica     Full-text available via subscription   (Followers: 2)
Acta Scientiarum. Animal Sciences     Open Access   (Followers: 2)
Acta Scientiarum. Technology     Open Access   (Followers: 2)
Acta Technologica Agriculturae     Open Access   (Followers: 1)
Acta Universitatis Sapientiae, Alimentaria     Open Access   (Followers: 1)
Advances in Agriculture     Open Access   (Followers: 6)
Advances in Agriculture & Botanics     Open Access   (Followers: 12)
Advances in Agronomy     Full-text available via subscription   (Followers: 14)
Advances in Life Science and Technology     Open Access   (Followers: 14)
AFBM Journal     Open Access  
Africa Research Bulletin: Political, Social and Cultural Series     Hybrid Journal   (Followers: 9)
African Journal of Agricultural Research     Open Access   (Followers: 3)
African Journal of Food Science     Open Access   (Followers: 4)
African Journal of Food, Agriculture, Nutrition and Development     Open Access   (Followers: 15)
African Journal of Range & Forage Science     Hybrid Journal   (Followers: 6)
Agra Europe     Full-text available via subscription   (Followers: 3)
Agribusiness : an International Journal     Hybrid Journal   (Followers: 6)
Agricultura Tecnica     Open Access   (Followers: 6)
Agricultura Tropica et Subtropica     Open Access   (Followers: 1)
Agricultura, Sociedad y Desarrollo     Open Access   (Followers: 1)
Agricultural and Food Science     Open Access   (Followers: 18)
Agricultural Commodities     Full-text available via subscription  
Agricultural Economics     Hybrid Journal   (Followers: 44)
Agricultural History Review     Full-text available via subscription   (Followers: 8)
Agricultural Research     Hybrid Journal   (Followers: 3)
Agricultural Science     Full-text available via subscription   (Followers: 4)
Agricultural Science     Open Access   (Followers: 1)
Agricultural Sciences     Open Access   (Followers: 7)
Agricultural Sciences in China     Full-text available via subscription   (Followers: 3)
Agricultural Systems     Hybrid Journal   (Followers: 28)
Agricultural Water Management     Hybrid Journal   (Followers: 34)
Agriculture     Open Access   (Followers: 6)
Agriculture & Food Security     Open Access   (Followers: 10)
Agriculture (Poľnohospodárstvo)     Open Access   (Followers: 1)
Agriculture and Agricultural Science Procedia     Open Access  
Agriculture and Food Sciences Research     Open Access   (Followers: 2)
Agriculture and Human Values     Hybrid Journal   (Followers: 12)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 48)
Agriprobe     Open Access  
Agrivita : Journal of Agricultural Science     Open Access   (Followers: 2)
Agro-Science     Full-text available via subscription  
Agroalimentaria     Open Access  
Agrociencia     Open Access   (Followers: 1)
Agrociencia Uruguay     Open Access  
Agrokémia és Talajtan     Full-text available via subscription   (Followers: 2)
Agrokreatif Jurnal Ilmiah Pengabdian kepada Masyarakat     Open Access  
Agronomía Colombiana     Open Access  
Agronomía Costarricense     Open Access   (Followers: 1)
Agronomía Mesoamericana     Open Access  
Agronomie Africaine     Full-text available via subscription  
Agronomy     Open Access   (Followers: 11)
Agrosearch     Open Access   (Followers: 1)
Akademik Ziraat Dergisi     Open Access  
Alinteri Zirai Bilimler Dergisi : Alinteri Journal of Agricultural Sciences     Open Access  
Ambiente & Agua : An Interdisciplinary Journal of Applied Science     Open Access   (Followers: 1)
American Journal of Agricultural and Biological Sciences     Open Access   (Followers: 10)
American Journal of Botany     Full-text available via subscription   (Followers: 15)
American Journal of Economics and Sociology     Hybrid Journal   (Followers: 27)
American Journal of Potato Research     Hybrid Journal   (Followers: 2)
American Journal of Rural Development     Open Access   (Followers: 3)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Annales des Sciences Agronomiques     Full-text available via subscription  
Annals of Agricultural and Environmental Medicine     Open Access   (Followers: 1)
Annals of Agricultural Sciences     Open Access   (Followers: 2)
Annals of Silvicultural Research     Open Access   (Followers: 1)
Annual Review of Resource Economics     Full-text available via subscription   (Followers: 12)
APCBEE Procedia     Partially Free   (Followers: 1)
Applied Economics Letters     Hybrid Journal   (Followers: 28)
Applied Financial Economics Letters     Hybrid Journal   (Followers: 7)
Arboricultural Journal : The International Journal of Urban Forestry     Hybrid Journal   (Followers: 6)
Archivos de Zootecnia     Open Access   (Followers: 1)
ARO. The Scientific Journal of Koya University     Open Access  
Arquivos do Instituto Biológico     Open Access   (Followers: 1)
Arthropod-Plant Interactions     Hybrid Journal   (Followers: 2)
Asian Economic Papers     Hybrid Journal   (Followers: 7)
Asian Journal of Agricultural Research     Open Access   (Followers: 4)
Asian Journal of Medical and Biological Research     Open Access   (Followers: 1)
Asian Journal of Plant Sciences     Open Access   (Followers: 2)
Australian Cottongrower, The     Full-text available via subscription   (Followers: 1)
Australian Economic Papers     Hybrid Journal   (Followers: 15)
Australian Economic Review     Hybrid Journal   (Followers: 7)
Australian Forest Grower     Full-text available via subscription   (Followers: 3)
Australian Forestry     Full-text available via subscription   (Followers: 2)
Australian Grain     Full-text available via subscription   (Followers: 3)
Australian Holstein Journal     Full-text available via subscription  
Australian Journal of Agricultural and Resource Economics     Hybrid Journal   (Followers: 3)
Australian Journal of Agricultural Engineering     Open Access   (Followers: 1)
Australian Sugarcane     Full-text available via subscription  
Avances en Investigacion Agropecuaria     Open Access   (Followers: 1)
B.E. Journal of Theoretical Economics     Full-text available via subscription  
Bangladesh Agronomy Journal     Open Access  
Bangladesh Journal of Agricultural Research     Open Access   (Followers: 2)
Bangladesh Journal of Scientific Research     Open Access   (Followers: 1)
Bioagro     Open Access   (Followers: 1)
Biocatalysis and Agricultural Biotechnology     Hybrid Journal   (Followers: 4)
Biocontrol Science and Technology     Hybrid Journal   (Followers: 5)
Biodiversity     Hybrid Journal   (Followers: 27)
Biodiversity : Research and Conservation     Open Access   (Followers: 26)
Biological Agriculture & Horticulture : An International Journal for Sustainable Production Systems     Partially Free   (Followers: 11)
Biosystems Engineering     Hybrid Journal   (Followers: 7)
Biotemas     Open Access  
Boletín Semillas Ambientales     Open Access  
Bragantia     Open Access   (Followers: 2)
Brazilian Archives of Biology and Technology     Open Access   (Followers: 3)
British Poultry Science     Hybrid Journal   (Followers: 5)
Buletin Peternakan : Bulletin of Animal Science     Open Access  
Buletin Veteriner Udayana     Open Access   (Followers: 2)
Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca : Food Science and Technology     Open Access  
Cahiers Agricultures     Open Access  
California Agriculture     Open Access   (Followers: 1)
Cambridge Journal of Economics     Hybrid Journal   (Followers: 55)
Canadian Water Resources Journal     Hybrid Journal   (Followers: 20)
Capitalism Nature Socialism     Hybrid Journal   (Followers: 11)
Ceiba     Open Access  
Cereal Chemistry     Full-text available via subscription   (Followers: 4)
CERNE     Open Access  
CESifo Economic Studies     Hybrid Journal   (Followers: 15)
Change and Adaptation in Socio-Ecological Systems     Open Access   (Followers: 1)
Chemical and Biological Technologies for Agriculture     Open Access  
Chilean Journal of Agricultural Research     Open Access   (Followers: 1)
Ciencia & Natura     Open Access  
Ciência e Agrotecnologia     Open Access  
Ciencia e investigación agraria     Open Access   (Followers: 1)
Ciência e Técnica Vitivinícola     Open Access  
Ciencia forestal en México     Open Access  
Ciência Rural     Open Access   (Followers: 2)
Ciencia y Agricultura     Open Access  
Ciencia, Tecnología y Salud     Open Access  
COCOS : The Journal of the Coconut Research Institute of Sri Lanka     Open Access   (Followers: 1)
Coffee Science     Open Access  
Cogent Food & Agriculture     Open Access   (Followers: 1)
Competition & Change     Hybrid Journal   (Followers: 10)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 4)
Contributions to Tobacco Research     Open Access   (Followers: 2)
Corps et culture     Open Access   (Followers: 6)
Cuadernos de Desarrollo Rural     Open Access   (Followers: 1)
Cultivos Tropicales     Open Access  
Cultural Geographies     Hybrid Journal   (Followers: 16)
Cultural Sociology     Hybrid Journal   (Followers: 30)
Cultural Studies - Critical Methodologies     Hybrid Journal   (Followers: 15)
Cultural Studies of Science Education     Hybrid Journal   (Followers: 6)
Cultural Trends     Hybrid Journal   (Followers: 13)
Culture & Agriculture     Hybrid Journal   (Followers: 12)
Culture, Agriculture, Food and Environment     Hybrid Journal   (Followers: 6)
Current Life Sciences     Open Access   (Followers: 3)
Current Research in Dairy Sciences     Open Access   (Followers: 5)
Derim     Open Access  
Developments in Agricultural Economics     Full-text available via subscription   (Followers: 4)
Developments in Agricultural Engineering     Full-text available via subscription   (Followers: 1)
Diatom Research     Hybrid Journal   (Followers: 2)
Die Bodenkultur : Journal of Land Management, Food and Environment     Open Access  
Dossiers Agraris     Open Access  
Ecological Applications     Full-text available via subscription   (Followers: 130)
Economic Affairs     Hybrid Journal   (Followers: 7)
Economic and Industrial Democracy     Hybrid Journal   (Followers: 9)
Economic Bulletin     Hybrid Journal   (Followers: 4)
Economic Policy     Hybrid Journal   (Followers: 41)
Economic Record     Hybrid Journal   (Followers: 6)
Empirical Economics     Hybrid Journal   (Followers: 11)
Encuentro     Open Access  
Engineering in Agriculture, Environment and Food     Hybrid Journal  
Ensaios e Ciência: Ciências Biológicas, Agrárias e da Saúde     Open Access  
Eppo Bulletin     Hybrid Journal   (Followers: 2)
Ethiopian Journal of Agricultural Sciences     Open Access  
Ethiopian Journal of Science and Technology     Open Access  
Ethology     Hybrid Journal   (Followers: 6)
EU agrarian Law     Open Access   (Followers: 4)
Euphytica     Hybrid Journal   (Followers: 7)
Eurochoices     Hybrid Journal   (Followers: 1)
European Agrophysical Journal     Open Access  
European Journal of Agronomy     Hybrid Journal   (Followers: 9)
European Journal of American Culture     Hybrid Journal   (Followers: 2)
European Journal of Health Economics     Hybrid Journal   (Followers: 19)
European Journal of Law and Economics     Hybrid Journal   (Followers: 58)
European Review of Agricultural Economics     Hybrid Journal   (Followers: 12)
EvoDevo     Open Access   (Followers: 3)
Extensão Rural     Open Access   (Followers: 1)
Farmer’s Weekly     Full-text available via subscription  
Farmlink Africa     Full-text available via subscription  
Fitosanidad     Open Access  
Folia Horticulturae     Open Access   (Followers: 2)
Food and Agricultural Immunology     Hybrid Journal   (Followers: 2)
Food and Energy Security     Open Access   (Followers: 4)
Food Biotechnology     Hybrid Journal   (Followers: 12)
Food Economics - Acta Agriculturae Scandinavica, Section C     Hybrid Journal   (Followers: 2)
Food New Zealand     Full-text available via subscription   (Followers: 3)
Food Policy     Hybrid Journal   (Followers: 30)
Forestry Chronicle     Full-text available via subscription   (Followers: 10)
Forum for Health Economics & Policy     Hybrid Journal   (Followers: 7)
Frontiers in Science     Open Access   (Followers: 1)
Frontiers of Agriculture in China     Hybrid Journal   (Followers: 2)
Future of Food : Journal on Food, Agriculture and Society     Open Access   (Followers: 3)
Geoderma     Hybrid Journal   (Followers: 9)
Global Approaches to Extension Practice : A Journal of Agricultural Extension     Full-text available via subscription   (Followers: 1)
Global Economic Review     Hybrid Journal   (Followers: 8)
Global Journal of Agricultural Sciences     Full-text available via subscription  
Gontor Agrotech Science Journal     Open Access  
Hacquetia     Open Access  

        1 2 3 | Last

Journal Cover Biosystems Engineering
  [SJR: 0.824]   [H-I: 77]   [7 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1537-5110 - ISSN (Online) 1537-5129
   Published by Elsevier Homepage  [3040 journals]
  • Analysis of the incipient motion of spherical particles in an open channel
           bed, using a coupled computational fluid dynamics–discrete element
           method model
    • Authors: A. Bravo-Blanco; A. Sánchez-Medina; F. Ayuga
      Pages: 68 - 76
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): A. Bravo-Blanco, A. Sánchez-Medina, F. Ayuga
      The measurement of liquid-induced erosion using CFD–DEM (computational fluid dynamics–discrete element method) models has been studied in detail, particularly in rough pipes. Some studies have provided measurements of the erosion rate in open liquid–solid systems, but there is less information on the incipient motion of individual particles since it is difficult to design test beds that can provide reliable results. This work compares the fluid flow velocity required to initiate incipient motion of a particle predicted by a coupled CFD–DEM model with measurements obtained during an experiment in an open channel under laboratory conditions. The experiment was designed to obtain a continuous flow with a slow and gradual increase in water velocity. The bed was made using two rows of spheres fixed in staggered positions, and a test sphere resting on top of the three neighbouring fixed spheres (i.e. nestling in the space between the surfaces of the fixed spheres). A 50 mm-high spillway gate was located downstream of the test sphere in order to obtain deeper water upstream, and provide more easily monitored and controllable water flows. The critical flow velocity required to initiate incipient motion in the five test spheres of different dimensions was measured by acoustic Doppler velocimetry. The difference in the results provided by the two methods was <5% (i.e. no significant difference). The coupled CFD–DEM model could therefore predict this variable and could be useful for investigating incipient erosion under other conditions.
      Graphical abstract image

      PubDate: 2017-01-06T05:49:14Z
      DOI: 10.1016/j.biosystemseng.2016.12.003
      Issue No: Vol. 155 (2017)
       
  • Optimising configuration of a hyperspectral imager for on-line field
           measurement of wheat canopy
    • Authors: Rebecca L. Whetton; Toby W. Waine; Abdul M. Mouazen
      Pages: 84 - 95
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Rebecca L. Whetton, Toby W. Waine, Abdul M. Mouazen
      There is a lack of information on optimal measurement configuration of hyperspectral imagers for on-line measurement of a wheat canopy. This paper aims at identifying this configuration using a passive sensor (400–750 nm). The individual and interaction effects of camera height and angle, sensor integration time and light source distance and height on the spectra's signal-to-noise ratio (SNR) were evaluated under laboratory scanning conditions, from which an optimal configuration was defined and tested under on-line field measurement conditions. The influences of soil total nitrogen (TN) and moisture content (MC) measured with an on-line visible and near infrared (vis-NIR) spectroscopy sensor on SNR were also studied. Analysis of variance and principal component analysis (PCA) were applied to understand the effects of the laboratory considered factors and to identify the most influencing components on SNR. Results showed that integration time and camera height and angle are highly influential factors affecting SNR. Among integration times of 10, 20 and 50 ms, the highest SNR was obtained with 1.2 m, 1.2 m and 10° values of light height, light distance and camera angle, respectively. The optimum integration time for on-line field measurement was 50 ms, obtained at an optimal camera height of 0.3 m. On-line measured soil TN and MC were found to have significant effects on the SNR with Kappa values of 0.56 and 0.75, respectively. In conclusion, an optimal configuration for a tractor mounted hyperspectral imager was established for the best quality of on-line spectra collected for wheat canopy.

      PubDate: 2017-01-06T05:49:14Z
      DOI: 10.1016/j.biosystemseng.2016.12.006
      Issue No: Vol. 155 (2017)
       
  • Rethinking environment control strategy of confined animal housing systems
           through precision livestock farming
    • Authors: Sébastien Fournel; Alain N. Rousseau; Benoit Laberge
      Pages: 96 - 123
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Sébastien Fournel, Alain N. Rousseau, Benoit Laberge
      Climate represents one of the main limiting factors of production efficiency. Thermal stress events can cause reduced performance, morbidity, and mortality, resulting in significant economic losses and animal welfare concerns. Environment control in confined animal housing systems is typically based on heat and moisture production rates at predetermined ambient temperature levels measured between 1950 and 1980. This traditional control method can fall short in meeting the true thermal needs of the animals since it does not account for factors now acknowledged as affecting the animal's productive responses to surrounding conditions, such as humidity, drafts, radiation, physiological state, and social interactions. Also, advancements in animal genetics, nutrition, and management practices have led to considerable changes in sensible and latent heat loads of modern livestock buildings. In this context, precision livestock farming technologies (sensors, detectors, cameras, microphones, etc.), enabling the automatic monitoring of environmental, physiological, and behavioural variables, can be used to continuously assess livestock performance and well-being in relation to their environment. An innovative strategy for environment control of livestock buildings could include the analysis of: (i) heat and moisture production rates using the most recent bioenergetic models; (ii) thermal stress through multi-factor animal comfort indices based on some environmental and physiological measurements; and (iii) animal behaviour as a response to changing environmental conditions. This paper presents a critical review of the state of the art of precision environment control of livestock buildings, identifying knowledge gaps, research opportunities, and technical challenges.

      PubDate: 2017-01-06T05:49:14Z
      DOI: 10.1016/j.biosystemseng.2016.12.005
      Issue No: Vol. 155 (2017)
       
  • Vis/NIR spectroscopy and chemometrics for non-destructive estimation of
           water and chlorophyll status in sunflower leaves
    • Authors: Antonio José Steidle Neto; Daniela C. Lopes; Francisco A.C. Pinto; Sérgio Zolnier
      Pages: 124 - 133
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Antonio José Steidle Neto, Daniela C. Lopes, Francisco A.C. Pinto, Sérgio Zolnier
      Vegetation biochemical and biophysical variables are important for many ecological, agronomic, and meteorological applications. Among the main variables, water and chlorophyll are essentials due to directly affect the plant photosynthetic capacity and crop productivity. The objective of this study was develop and validate models capable of estimating water and chlorophyll status in sunflower leaves under progressive water stress, based on the visible/near-infrared region (Vis/NIR) spectral reflectance and chemometric technique. The water and chlorophyll models were adjusted considering the spectral reflectance from the 500–1039 nm wavelengths by using partial least squares regressions (PLSR). In the external validation, high determination coefficient (0.8386 and 0.8097) and low mean bias error (−0.40 dry basis and 0.09 mg g−1) values for water and chlorophyll, respectively, indicating that their predictive capabilities and accuracies of the models were satisfactory. Results showed that spectrometry has potential to be applied as an alternative method in quantifying water and chlorophyll status in sunflower leaves in a non-destructive, quick, and consistent way.
      Graphical abstract image

      PubDate: 2017-01-13T06:00:01Z
      DOI: 10.1016/j.biosystemseng.2016.12.008
      Issue No: Vol. 155 (2017)
       
  • Automatic herding reduces labour and increases milking frequency in
           robotic milking
    • Authors: Uri Drach; Ilan Halachmi; Tal Pnini; Ido Izhaki; Amir Degani
      Pages: 134 - 141
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Uri Drach, Ilan Halachmi, Tal Pnini, Ido Izhaki, Amir Degani
      The motivation of cows to be milked is a key factor in the utilisation of milking robots. If a cow does not voluntarily attend a robot stall, fetching, that requires expensive labour, is required. This research suggests a new concept, herding all the cows to the milking robot using an automatic herding system (AHS). An AHS was built as a system of slow moving mobile fences controlled by an industrial controller. The AHS herds all the cows to the milking robot. The AHS was used in a commercial farm with two milking robots, and the experiment was conducted for three months. The dairy herd was divided into a reference group (43 cows) and an experimental group (38 cows). The AHS was used only with the experiment group. Milking frequency increased in the experimental group by 45.5% (1.89 milkings d−1 vs. 2.75 milkings d−1), while there was no major change in the milking frequency in the reference group 0.4% (2.38 milkings d−1 vs. 2.39 milkings d−1). Milk yield increased in the experiment group 15.7% (35.65 kg d−1 vs. 41.25 kg d−1). There was also no major change in the milk yield in reference group 4% (31 kg d−1 vs. 29.76 kg d−1). There was an 80% decrease in labour time for fetching the cows to the milking robot in the experimental group (5 h day−1 vs. 1 h day−1) while there was no change in labour for the reference group. The AHS was therefore associated with higher milking frequency, higher milk yield and labour reduction, hence economic benefits are expected for the system.

      PubDate: 2017-01-13T06:00:01Z
      DOI: 10.1016/j.biosystemseng.2016.12.010
      Issue No: Vol. 155 (2017)
       
  • A pore-scale model for predicting resistance to airflow in bulk grain
    • Authors: Rong Yue; Qiang Zhang
      Pages: 142 - 151
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Rong Yue, Qiang Zhang
      A pore-scale model was developed to predict airflow resistance through grain bulks. The model consisted of two components: simulation of pore structures and prediction of pressure drop through connected pores that formed airflow paths in the grain bulk. The discrete element method (DEM) was used to simulate the spatial arrangement (pore structure) of grain kernels in a grain bulk. The grain kernels were approximated as spherical particles in the DEM model. Based on the DEM simulations, a collection of tetrahedron units was constructed to represent local airflow paths (individual pores) and these local paths were then connected to form global airflow paths. A flow branching model was developed to predict pressure drop within each local flow path, and the total pressure drop through the grain bulk was then calculated as the sum of resistances of all local paths associated with the global path. An experiment was conducted to validate the proposed model. The results showed that the model predictions were in reasonable agreement with the experimental data. The predicted pressure drop was 12% higher than the experimental value at a low superficial air velocity of 0.013 m s−1 when the inertial effect was negligible, and 17% lower than the measured value at a high air velocity of 0.027 m s−1 when some inertial effect existed.

      PubDate: 2017-01-13T06:00:01Z
      DOI: 10.1016/j.biosystemseng.2016.12.007
      Issue No: Vol. 155 (2017)
       
  • Radio frequency irradiation treatment of dates in a single layer to
           control Carpophilus hemipterus
    • Authors: Francesco Garbati Pegna; Patrizia Sacchetti; Valentina Canuti; Serena Trapani; Carlo Bergesio; Antonio Belcari; Bruno Zanoni; Ferdinando Meggiolaro
      Pages: 1 - 11
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Francesco Garbati Pegna, Patrizia Sacchetti, Valentina Canuti, Serena Trapani, Carlo Bergesio, Antonio Belcari, Bruno Zanoni, Ferdinando Meggiolaro
      Stored dates require postharvest disinfestation treatment to prevent damage caused by insects feeding on these fruits. Fruit disinfestation can be achieved with different methods, at present fumigation, heating and refrigeration being the most common pest control methods, though there are drawbacks related to product quality, process efficiency and environmental impact. The aim of this study was to define a procedure for disinfesting dates using Radio Frequency (RF) heating. RF treatments were carried out on dates of the semi-dry Siwi variety, artificially infested with the larvae, pupae and adults of the dried fruit beetle, Carpophilus hemipterus. A pilot-scale radio frequency instrument with 3.5 kW nominal maximum power and a frequency of 27.12 MHz was used to perform the experiments. The internal temperature of the dates was measured during irradiation. An insect mortality assessment was carried out both at the end of RF treatment and on the following days. The effects of a 4-, 5- and 6-min RF treatment on different stages of C. hemipterus were evaluated, finding that a 6-min exposure ensured mortality of the larvae, pupae and adults of the pest. No significant alterations in moisture content or colour of the treated dates were evident. RF treatment appeared to be a viable technique for the disinfestation of dates, due to the short treatment time together with the possibility of continuous processing.
      Graphical abstract image

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.11.011
      Issue No: Vol. 155 (2016)
       
  • Development of an effective sampling strategy for ammonia, temperature and
           relative humidity measurement during sheep transport by ship
    • Authors: Yu Zhang; Allan T. Lisle; Clive J.C. Phillips
      Pages: 12 - 23
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Yu Zhang, Allan T. Lisle, Clive J.C. Phillips
      Ammonia, high temperature and high humidity have adverse effects on animals during long distance livestock export from Australia to the Middle East, but none of these is effectively measured currently. On the basis of data maps obtained on two voyages of live sheep export, this study determined sampling strategies for ammonia, temperature and humidity measurement on the vessel. The difference between predicted high and low ammonia sites on the shipment could be detected with approximately 5 measurement sites of each. Margins of error were determined, which suggested that dry bulb temperature could be measured with 6–8 measurement sites, but even 20 measurement sites were not sufficient to measure relative humidity. For the vessel recorded, considerably more ammonia measurement sites are required on closed decks than on open decks, with less variation for temperature measurement. The number of pens measured contributed more to the variance of ammonia and temperature measurement than the number of sampling locations within each pen on open decks. This study highlights the importance of a suitable sampling strategy to measure ammonia, temperature and relative humidity on board ship during live export.

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.11.010
      Issue No: Vol. 155 (2016)
       
  • Deoxynivalenol screening in wheat kernels using hyperspectral imaging
    • Authors: Jayme Garcia Arnal Barbedo; Casiane Salete Tibola; Maria Imaculada Pontes Lima
      Pages: 24 - 32
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Jayme Garcia Arnal Barbedo, Casiane Salete Tibola, Maria Imaculada Pontes Lima
      The use of hyperspectral imaging (HSI) for deoxynivalenol (DON) screening in wheat kernels is investigated. Experiments were carried out using a new algorithm designed to be simple to implement and computationally light, being largely based on the manipulation of a few selected spectral bands. Initial experimental results revealed that direct estimation of DON content using hyperspectral images is currently unfeasible, but they also indicated that an indirect analysis exploring the correlation between Fusarium damage and DON content may be accurate enough to improve the process of DON screening in the production chain. This motivated the adoption of a classification approach, in which an algorithm, instead of estimating a value for the DON content, classifies wheat kernel batches into two or three categories, depending on the application. The developed algorithm achieved accuracies of 72% and 81% for the three- and two-class classification schemes, respectively. The results, although not accurate enough to provide conclusive screening, indicated that the algorithm could be used for initial screening to detect wheat batches that warrant further analysis regarding their DON content.

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.12.004
      Issue No: Vol. 155 (2016)
       
  • One-pass drying of rough rice with an industrial 915 MHz microwave dryer:
           Quality and energy use consideration
    • Authors: Gbenga A. Olatunde; Griffiths G. Atungulu; Deandrae L. Smith
      Pages: 33 - 43
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Gbenga A. Olatunde, Griffiths G. Atungulu, Deandrae L. Smith
      Microwave (MW) at 915 MHz has potential to achieve one pass rough rice drying. However, optimising processing parameters to maintain the rice quality is crucial. Effects of MW treatment on rice moisture removal, milled rice characteristics, and energy requirements for continuous one pass drying operation were quantified. Freshly harvested rough rice with initial moisture content of 25% wet basis was dried in a pilot-scale 915 MHz microwave dryer. The dryer was set to transmit MW power ranging between 3 and 24 kW during 8 min of drying. During treatments, rough rice was conveyed at bed thicknesses, 0.01, 0.03, and 0.05 m; supplied specific energy was maintained at 450, 600 and 750 kJ kg−1 of rough rice. Moisture removed varied between 6% and 15% points, depending on rice bed thickness (0.01–0.05 m) and applied specific energy (450–750 kJ kg−1). Increasing rice bed thickness and specific energy reduced milling and head rice yields, increased final viscosity of milled rice, but marginally affected rice peak viscosity and surface lipid and protein contents (p < 0.05). To achieve the desired percentage point moisture content reduction (∼12% points) at specific energy of 600 kJ kg−1 and 750 kJ kg−1 of rough rice, 4574 kJ and 5986 kJ were required per kg of water removed, respectively; this translated to 13 and 16 USD per metric ton of dried rice, respectively. The study demonstrated feasibility of one pass MW drying of rough rice; 450–600 kJ kg−1 of rough rice was recommended to preserve rice quality and achieved better energy use efficiency.

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.12.001
      Issue No: Vol. 155 (2016)
       
  • Discrete element modelling of tillage forces and soil movement of a
           one-third scale mouldboard plough
    • Authors: Mustafa Ucgul; Chris Saunders; John M. Fielke
      Pages: 44 - 54
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Mustafa Ucgul, Chris Saunders, John M. Fielke
      In Australia there is renewed interest in mouldboard ploughing to improve crop yields of non-wetting sandy soils. Burying the top layer of non-wetting soil and bringing to the surface soil that has better water holding capacity is beneficial for plant growth. To improve the effectiveness of the ploughing it is essential to: (1) optimise the tillage forces and (2) understand the soil inversion and burial process. Recent studies show that Discrete Element Modelling (DEM) has the potential to predict both tillage forces and soil movement of tillage implements. In this study a one-third scale mouldboard plough was constructed and tested in a soil bin where draught force, vertical force and soil movement were measured. A comparison of the measured and simulated draught and downward vertical forces showed a close agreement. A procedure was developed to compare soil movement, percentage burial of top soil and forward soil movement of the soil bin tests and the DEM simulations. The results showed similar trends and patterns for both the percentage of the top soil buried to various tillage depths and the forward soil movement. Due to the larger than actual spherical particles used in the simulation the forward soil movement was greater for DEM. The DEM showed some particles moving below the tillage depth. This shows that further model development is needed with work recommended to look at using both clump particle shapes and smaller particle sizes to improve soil movement predictions.

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.12.002
      Issue No: Vol. 155 (2016)
       
  • Discrete element method simulation of the hulling process of Jatropha
           curcas L. fruits
    • Authors: Sebastian Romuli; Shkelqim Karaj; Joachim Müller
      Pages: 55 - 67
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): Sebastian Romuli, Shkelqim Karaj, Joachim Müller
      Hulling of Jatropha curcas fruits is an important step to isolate seeds from hulls. Physical characteristics of fruit such as length, width, thickness, geometric mean diameter, solid density, rupture force, deformation at rupture point, Poisson's ratio and shear modulus as well as interaction properties such as coefficient of restitution, static and rolling friction were measured. A prototype of a motor-driven huller was developed based on discrete element method (DEM) simulation by applying the Hertz–Mindlin contact model. Optimum upper and lower concave clearance were studied in terms of compressive force occurring in the system. Rotor torque and specific energy input ranged from 60 to 110 Nm and 0.013 to 0.021 kWh kg−1, respectively. The maximum throughput of fruits was 1152 kg h−1. The highest hulling efficiency of 98.8% was achieved at a throughput of 477 kg h−1. Grading of J. curcas fruits to achieve size homogeneity and the removal of stones and sand are suggested as further improvements in the hulling process.
      Graphical abstract image

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.11.009
      Issue No: Vol. 155 (2016)
       
  • Frequency response of late-season ‘Valencia’ orange to
           selective harvesting by vibration for juice industry
    • Authors: S. Castro-Garcia; G.L. Blanco-Roldán; Louise Ferguson; E.J. González-Sánchez; J.A. Gil-Ribes
      Pages: 77 - 83
      Abstract: Publication date: March 2017
      Source:Biosystems Engineering, Volume 155
      Author(s): S. Castro-Garcia, G.L. Blanco-Roldán, Louise Ferguson, E.J. González-Sánchez, J.A. Gil-Ribes
      Citrus mechanical harvesting has been investigated since the 1960's. Even though mechanical harvesting could significantly lower production costs, the implementation by the private sector has been slow. The current harvesting technologies detach the fruits with trunk, canopy or branch vibration. For late-season sweet orange varieties which simultaneously bear mature fruit, immature fruitlets and flowers, shaker harvesting decreases the subsequent year's yield. This study, investigated the frequency response of mature fruits and immature fruitlets to determine the optimum frequency range for an efficient and selective harvest. Laboratory vibration transmission tests were conducted with 14 branches bearing 76 mature fruits and 151 immature ‘Valencia’ fruitlets. The fruit and branch response to the forced vibration was measured by several sets of five triaxial accelerometers with a dynamic signal analyser. Three frequency ranges with the highest vibration transmission values were identified for mechanical harvesting lower than 10 Hz. The first frequency range (1.5–2.5 Hz) corresponded best with the most efficient vibration transmission, involving more than 90% of fruit. The second frequency range (4.5–5 Hz) successfully discriminated between mature fruit and immature fruitlets. In this frequency range, 53.4% of mature fruit amplified the acceleration a mean value of 2.2 times, while only 7.3% of immature fruitlets amplified the acceleration with a mean value of 4.4 times. The third frequency range (7–8 Hz) had the lowest vibration transmission value. The frequency response of mature citrus fruits, and their markedly higher fruit mass, were significant factors in efficient selective mechanical harvesting.
      Graphical abstract image

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.11.012
      Issue No: Vol. 155 (2016)
       
  • Performance analysis of a novel cyclone-type pneumatic rice polisher
    • Authors: Ch. Someswararao; Swati Mahato; Lobzang Namgial; Muhammed Sirajul Huda; Susanta Kumar Das
      Pages: 1 - 11
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Ch. Someswararao, Swati Mahato, Lobzang Namgial, Muhammed Sirajul Huda, Susanta Kumar Das
      Energy intensive commercial abrasive-friction rice polishing systems with heavy moving parts induces considerable breakage of rice. Jet polishing, used for metals with high speed air-abrasive particles, could be adopted to develop a simple pneumatic rice polishing system without any moving parts. Its construction is similar to a gas-cyclone system. The effect of four abrasive surfaces, viz., coarse (CR, 483 μm), medium (MD, 254 μm), fine (FN,122 μm) and very fine (VF, 89 μm) on degree of polishing (DP) and broken yield (Br) was studied. Particle-trajectory, particle-abrasive surface interaction, grain rotation pattern and progress of bran removal were also studied. DP and Br increased linearly with number of passes for all the abrasive surfaces. Higher DP (8.49 ± 0.2 and 8.49 ± 0.3%) with CR and MD was attributed to removal of bran layer along with endosperm fractions while FN and VF removed proportionally more bran layer (DP, 6.27 ± 0.3 and 8.31 ± 0.4%) with negligible endosperm fraction. Br was least (24.13 ± 0.5%) with VF and highest (34.0 ± 2.2%) with CR.

      PubDate: 2016-11-17T10:35:41Z
      DOI: 10.1016/j.biosystemseng.2016.10.020
      Issue No: Vol. 153 (2016)
       
  • Comparison of statistical regression and data-mining techniques in
           estimating soil water retention of tropical delta soils
    • Authors: Phuong M. Nguyen; Amir Haghverdi; Jan de Pue; Yves-Dady Botula; Khoa V. Le; Willem Waegeman; Wim M. Cornelis
      Pages: 12 - 27
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Phuong M. Nguyen, Amir Haghverdi, Jan de Pue, Yves-Dady Botula, Khoa V. Le, Willem Waegeman, Wim M. Cornelis
      Although a great number of studies have been devoted to develop and evaluate pedotransfer functions (PTFs), several questions still are to be addressed, particularly pertaining to tropical delta soils which received very little attention. One such question relates to the optimal structural dependency between basic soil properties and soil water retention characteristics (SWRC), which could be formulated by various regression methods. It is hypothesised that data mining techniques provide more accurate SWRC-PTFs than statistical linear regression. However, data-mining techniques are often proven as highly data-demanding techniques. The aim of this study was, therefore, to verify that hypothesis for a limited data set of tropical delta soils by comparing the predictive capabilities of point PTFs and pseudo-continuous (PC) PTFs developed by Multiple Linear Regression (MLR), Artificial Neural Networks (ANN), Support Vector Machine for Regression (SVR), and k-Nearest Neighbours (kNN) methods. The results show that point-PTFs derived from data-mining techniques (i.e. ANN, SVR, kNN) offer accurate and reliable estimation of soil water content at several matric potentials. In case of PC-PTFs, ANN and kNN models outperformed SVR and MLR PTFs in validation phase (RMSE of ANN and kNN PTFs were around 0.05 m3 m−3, while those of SVR PTFs and MLR PTFs rose up to 0.068 and 0.066 m3 m−3). Our findings confirm the superiority of data-mining approaches in modelling the complex system of soil and water, even when a limited data set is available. The non-parametric kNN method, though being constrained in estimating SWRC in pseudo-continuous manner, has great benefits due to its flexibility, simplicity, accuracy and capacity to append new observations.

      PubDate: 2016-11-17T10:35:41Z
      DOI: 10.1016/j.biosystemseng.2016.10.013
      Issue No: Vol. 153 (2016)
       
  • Reference trajectory planning under constraints and path tracking using
           linear time-varying model predictive control for agricultural machines
    • Authors: Mogens M. Graf Plessen; Alberto Bemporad
      Pages: 28 - 41
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Mogens M. Graf Plessen, Alberto Bemporad
      A method for the control of autonomously and slowly moving agricultural machinery is presented. Special emphasis is on offline reference trajectory generation tailored for high-precision closed-loop tracking within agricultural fields using linear time-varying model predictive control. When optimisation is carried out, high-level logistical processing can result in edgy reference paths for field coverage. Subsequent trajectory smoothing can consider specific actuator rate constraints and field geometry. The latter step is the subject of this paper. Focussing on forward motion only, the role of non-convexly shaped field geometry, repressed area minimisation and spraying gap avoidance is analysed. Three design methods for generating smooth reference trajectories are discussed: circle-segments, generalised elementary paths, and bi-elementary paths.

      PubDate: 2016-11-23T12:45:10Z
      DOI: 10.1016/j.biosystemseng.2016.10.019
      Issue No: Vol. 153 (2016)
       
  • Effect of rainfall and swath density on dry matter and composition change
           during drying of switchgrass and corn stover
    • Authors: Amit Khanchi; Stuart J. Birrell
      Pages: 42 - 51
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Amit Khanchi, Stuart J. Birrell
      During field drying, crops can be subjected to rainfall losses due to leaching, respiration and mechanical treatments. The objective of this study was to measure the impact of rainfall amount (8–75 mm) and crop density (0.8–2.6 (corn stover), 1 to 3.2 (switchgrass) kg [DM] m−2) on dry matter and composition change of corn stover (CS) and switchgrass. CS and switchgrass lost 0.3–4.7% and 0.2–2.8% as leaching loss from 8 to 75 mm of rainfall, respectively. After the incubation period of 48 h, the dry matter loss increased to 7.2–9.8% (CS) and 2.6–6.1% (switchgrass) from 8 to 75 mm of rainfall, respectively. Water soluble portion of CS and switchgrass was more severely affected than the fibre portion. Corn stover, being more exposed to rainfall in low density (LD) swaths, lost 56.7% ash content, compared to 19% in high density (HD) swaths. In CS, a significant decrease of K (10.2–63.8%) and Mg (5.6–41.7%) was observed with greater reductions in LD swaths compared to HD swaths. Similarly, a significant decrease in K (6.2–23.0%) and Mg (5.1–17%) content was observed in switchgrass but it was less prominent than CS.

      PubDate: 2016-11-23T12:45:10Z
      DOI: 10.1016/j.biosystemseng.2016.10.022
      Issue No: Vol. 153 (2016)
       
  • Reducing nitrogen contamination from agricultural subsurface drainage with
           denitrification bioreactors and controlled drainage
    • Authors: Barry R. Husk; Bruce C. Anderson; Joann K. Whalen; Juan S. Sanchez
      Pages: 52 - 62
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Barry R. Husk, Bruce C. Anderson, Joann K. Whalen, Juan S. Sanchez
      Reactive nitrogen leaving agricultural fields through subsurface drainage systems enters aquatic systems and contributes to eutrophication, habitat degradation and loss of biodiversity. Denitrification bioreactors, in combination with controlled drainage, are proposed as a means of reducing nitrogen emitted through subsurface agricultural drainage systems, but their suitability in colder climates where soils and drainage systems freeze during winter is poorly understood. This study presents the first field-scale evaluation of denitrification bioreactors under cold climate conditions during a three-year period in Quebec, Canada. Under a three-year crop rotation, about 55% of the total annual subsurface drainage water passed through bioreactors, which significantly lowered the total-nitrogen (72%) and nitrate-nitrogen (99%) median concentrations in the subsurface drainage outflows. Loadings of nitrate-nitrogen from the test fields to surface drainage ditches were reduced by 99%, equivalent to about 11 kg nitrate-nitrogen ha−1 year−1 removal in the test area and approximately 7 g nitrate-nitrogen removal m−3 bioreactor volume d−1. Aquatic environmental criteria non-compliance events declined by 96% for nitrate-nitrogen and by 50% for total-nitrogen during the three-year study. This study demonstrates that denitrification bioreactors, combined with controlled drainage, are an effective in-field technology for nitrogen removal from agricultural subsurface drainage water that will improve water quality under cold climate conditions.

      PubDate: 2016-11-23T12:45:10Z
      DOI: 10.1016/j.biosystemseng.2016.10.021
      Issue No: Vol. 153 (2016)
       
  • Early and non-intrusive lameness detection in dairy cows using
           3-dimensional video
    • Authors: K. Abdul Jabbar; Mark F. Hansen; Melvyn L. Smith; Lyndon N. Smith
      Pages: 63 - 69
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): K. Abdul Jabbar, Mark F. Hansen, Melvyn L. Smith, Lyndon N. Smith
      Lameness is a major issue in dairy herds and its early and automated detection offers animal welfare benefits together with potentially high commercial savings for farmers. Current advancements in automated detection have not achieved a sensitive measure for classifying early lameness. A novel proxy for lameness using 3-dimensional (3D) depth video data to analyse the animal's gait asymmetry is introduced. This dynamic proxy is derived from the height variations in the hip joint during walking. The video capture setup is completely covert and it facilitates an automated process. The animals are recorded using an overhead 3D depth camera as they walk freely in single file after the milking session. A 3D depth image of the cow's body is used to automatically track key regions such as the hooks and the spine. The height movements are calculated from these regions to form the locomotion signals of this study, which are analysed using a Hilbert transform. Our results using a 1–5 locomotion scoring (LS) system on 22 Holstein Friesian dairy cows, a threshold could be identified between LS 1 and 2 (and above). This boundary is important as it represents the earliest point in time at which a cow is considered lame, and its early detection could improve intervention outcome thereby minimising losses and reducing animal suffering. Using a linear Support Vector Machine (SVM) binary classification model, the threshold achieved an accuracy of 95.7% with a 100% sensitivity (detecting lame cows) and 75% specificity (detecting non-lame cows).

      PubDate: 2016-11-29T02:50:31Z
      DOI: 10.1016/j.biosystemseng.2016.09.017
      Issue No: Vol. 153 (2016)
       
  • Wireless sensor networks for greenhouse climate and plant condition
           assessment
    • Authors: Konstantinos P. Ferentinos; Nikolaos Katsoulas; Antonis Tzounis; Thomas Bartzanas; Constantinos Kittas
      Pages: 70 - 81
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Konstantinos P. Ferentinos, Nikolaos Katsoulas, Antonis Tzounis, Thomas Bartzanas, Constantinos Kittas
      Spatially distributed environmental measurements at plant level can be used to create a precise and detailed representation of the climate at various regions inside a greenhouse. Climatic heterogeneity can cause significant differences in terms of yield, productivity, quantitative and qualitative characteristics of the plants, as well as the development of various diseases. This work presents: i) the assessment of wireless sensor networks (WSNs) operation reliability and accuracy in actual greenhouse conditions, ii) the development of a distributed monitoring system using a WSN in a commercial greenhouse, and iii) the analysis of the collected spatially distributed data for the investigation of possible problematic situations for the growing plants caused by climatic heterogeneity inside the greenhouse. A prototype WSN was initially developed in order to investigate the effects of the environmental conditions to the operation reliability of the network and assess its performance and the feasibility of its operation in a commercial greenhouse. The enhanced WSN was then installed in a commercial greenhouse to investigate the spatial variation of the existing environmental conditions. Analysis based on WSN measurements showed significant spatial variability in temperature and humidity with average differences up to 3.3 °C and 9% relative humidity and transpiration, with the greatest variability occurring during daytime in the summer period. There were conditions that favoured condensation on leaf surfaces and other problematic situations.

      PubDate: 2016-11-29T02:50:31Z
      DOI: 10.1016/j.biosystemseng.2016.11.005
      Issue No: Vol. 153 (2016)
       
  • A smart-vision algorithm for counting whiteflies and thrips on sticky
           traps using two-dimensional Fourier transform spectrum
    • Authors: Yurui Sun; Hong Cheng; Qiang Cheng; Haiyang Zhou; Menghua Li; Youheng Fan; Guilin Shan; Lutz Damerow; Peter Schulze Lammers; Scott B. Jones
      Pages: 82 - 88
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Yurui Sun, Hong Cheng, Qiang Cheng, Haiyang Zhou, Menghua Li, Youheng Fan, Guilin Shan, Lutz Damerow, Peter Schulze Lammers, Scott B. Jones
      Although sticky traps are reliable indicators of pest population dynamics but pest counting by humans is time-consuming and menial labour. A novel smart vision algorithm based on two-dimensional Fourier transform (2DFT) spectrum is presented. Rather than directly counting the pests captured on the traps, the novel concept is to treat trapped pests as noise in a two-dimensional (2D) image with 2DFT serving as a specific noise collector. The research objectives included comparing human and 2DFT counting in two proof-of-principle tests: (i) simulated pests with various quantities and distributions arrayed on two series of templates using both ordered and random patterns; (ii) sweet potato whiteflies [Bemisia tabaci (Gennadius), Hemiptera: Aleyrodidae] on yellow sticky traps (YSTs) and western flower thrips [Frankliniella occidentalis (Pergande), Thysanoptera: Thripidae] on blue sticky traps (BSTs). Tests of simulated pests (2–512) on eight templates verified that the 2DFT-based index provides accurate estimates of pests captured on the traps (R2 = 1), independent of pest distribution pattern. High correlations were obtained from count results of whiteflies on 34 YSTs (R2 = 0.9994) and thrips on 33 BSTs (R2 = 0.9989). Measurement errors were addressed.

      PubDate: 2016-11-29T02:50:31Z
      DOI: 10.1016/j.biosystemseng.2016.11.001
      Issue No: Vol. 153 (2016)
       
  • Heat transfer finite element model of fresh fruit salad insulating
           packages in non-refrigerated conditions
    • Authors: Chiara Cevoli; Angelo Fabbri
      Pages: 89 - 98
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Chiara Cevoli, Angelo Fabbri
      The quality of many foods is significantly affected by temperature fluctuations that can occur during distribution and transport. Packaging materials can help to shield the product from temperature variation by increasing the heat transfer resistance. Thermal insulation power is influenced by several factors, such as material, geometry, and degree of contact between materials. To maintain the cool chain of fruit salad with syrup during the transportation (temperature less than 5 °C), thermal insulation effect of different packaging materials was investigated. A parametric analysis using a finite element model able to describe the heat transfer inside the containers, on varying packaging material (expanded polystyrene: EPS, and air), geometry, dimension, and boundary conditions, was developed and validated. Good agreement was obtained between numerical and experimental results (R2 up to 0.98). The effectiveness of the insulation configurations was evaluated by determining the time taken for the temperature to rise the critical value of 5 °C. Results showed that insulating performance of the air is better than EPS. This is realistic only taking into account insulation layer less than 0.013 m. From a practical point of view, an EPS packaging could result stronger compared to a packaging characterised by an insulating air layer. For the same EPS insulation thickness, product temperature exponentially decreases with the volumetric capacity (R2 = 0.99).

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.11.002
      Issue No: Vol. 153 (2016)
       
  • A threshold-based algorithm for the development of inertial sensor-based
           systems to perform real-time cow step counting in free-stall barns
    • Authors: Claudia Arcidiacono; Simona M.C. Porto; Massimo Mancino; Giovanni Cascone
      Pages: 99 - 109
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Claudia Arcidiacono, Simona M.C. Porto, Massimo Mancino, Giovanni Cascone
      Innovative systems and automated computational procedures, such as those based on computer vision or inertial wearable sensors, have recently been adopted to provide effective and accurate monitoring and analysis of cow behaviour and respond to different issues related to cow health and welfare. In this study, a new and open source algorithm, characterised by a linear computational time, was defined and implemented with the aim to improve real-time monitoring and analysis of walking behaviour of dairy cows. It was applied to a novel inertial sensor-based system composed of low-cost devices, including wearable sensors, open source software, operating with a 4-Hz sampling frequency. The algorithm computed the number of steps of each cow from accelerometer data by making use of statistically defined thresholds. Two vector variables were considered to study the accelerometer signals, i.e., Signal Vector Magnitude and Signal Magnitude Area. Algorithm accuracy was carried out by comparing total error (E) and Relative Measurement Error (RME), and a sensitivity analysis on the parameters of the computed thresholds was carried out to analyse the variation of the error made by the algorithm. The results showed that the algorithm produced an E equal to 9.5%, and a RME between 2.4% and 4.8%. The sensitivity analysis confirmed that the proposed thresholds provided the minimum errors and that RME is less suitable than E for measuring the accuracy of the step counter. In fact, the underestimated and overestimated numbers of steps counted by the algorithm tended to compensate each other in RME computation.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.11.003
      Issue No: Vol. 153 (2016)
       
  • Agricultural robots for field operations. Part 2: Operations and systems
    • Authors: Avital Bechar; Clément Vigneault
      Pages: 110 - 128
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Avital Bechar, Clément Vigneault
      This part of our review of the research, developments and innovation in agricultural robots for field operations, focuses on characteristics, performance measures, agricultural tasks and operations. The application of robots to a variety of field operations has been widely demonstrated. A key feature of agricultural robots is that they must operate in unstructured environments without impairing the quality of work currently achieved. Designs, developments and evaluations of agricultural robots are diverse in terms of objectives, structures, methods, techniques, and sensors. Standardisation of terms, system-performance measures and methodologies, and adequacy of technological requirements are vital for comparing robot performance and technical progress. Factors limiting commercialisation and assimilation of agricultural autonomous robot systems are unique to each system and to each task. However, some common gaps need to be filled to suit unstructured, dynamic environments; e.g. poor detection performance, inappropriate decision-making and low action success rate. Research and development of versatile and adaptive algorithms, integrated into multi-sensor platforms, is required. Cycle time must be reduced and production rate increased to justify economic use. Improved wholeness or integration of all sub-systems will enable sustainable performance and complete task operation. Research must focus on each of these gaps and factors that limit commercialisation of agricultural robotics. Research needs to focus on the field use of autonomous or human–robot systems, the latter being a reasonable step toward fully autonomous robots. More robust, reliable information-acquisition systems, including sensor-fusion algorithms and data analysis, should be suited to the dynamic conditions of unstructured agricultural environments.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.11.004
      Issue No: Vol. 153 (2016)
       
  • Methods to estimate daily evapotranspiration from hourly
           evapotranspiration
    • Authors: Baozhong Zhang; He Chen; Di Xu; Fusheng Li
      Pages: 129 - 139
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Baozhong Zhang, He Chen, Di Xu, Fusheng Li
      Remote sensing provides an effective way for the estimation of regional evapotranspiration, therefore, a reliable scaling-up method from instantaneous evapotranspiration (ET) to daily ET is of great importance. In this paper, five commonly used scaling-up methods estimating daily ET from hourly latent heat measurements were compared under different energy and crop growing conditions. Field data collected during the whole growing season at 1.0 h intervals by eddy covariance system in North China were used. Evaporative fraction (EF), reference evaporative fraction (K c ), crop coefficient (modified-K c ) and surface resistance (r c ) varied slightly during the daytime, which gave a solid theoretical basis for the scaling-up methods based on the constant value of these parameters. In most cases, the EF and K c methods performed better than the others, the relative bias from 9:00–16:00 for the two methods ranged from −11.2% to 5.9% and −6.6% to 4.8%, respectively. The EF method was applicable when surface energy was limited, when R n was less than 50 W m−2; the average modified coefficient of efficiency of EF method during the daytime from 9 am to 5 pm was 0.68, which is around twice that of the second best method. The K c and the modified-K c methods were applicable when surface energy was relatively large. The performance of the five methods didn't seem sensitive to variation of leaf area. Overall, the K c and EF methods performed better, especially between 11:00 and 15:00. The results of this paper could be useful for optimisation of ET models.

      PubDate: 2016-12-12T06:02:09Z
      DOI: 10.1016/j.biosystemseng.2016.11.008
      Issue No: Vol. 153 (2016)
       
  • Developing universal models for the prediction of physical quality in
           citrus fruits analysed on-tree using portable NIRS sensors
    • Authors: Irina Torres; Dolores Pérez-Marín; María-José De la Haba; María-Teresa Sánchez
      Pages: 140 - 148
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Irina Torres, Dolores Pérez-Marín, María-José De la Haba, María-Teresa Sánchez
      The citrus sector seeks rapid, economical, environmentally-friendly and non-destructive technologies for monitoring external and internal changes in physical quality taking place in fruit during on-tree growth, thus allowing fruit quality to be evaluated at any stage of fruit development. The use of portable near-infrared spectroscopy (NIRS) sensors based on micro-electro-mechanical system (MEMS) technology, in conjunction with chemometric data treatment models, has already been studied for quality-control purposes in two citrus species: oranges and mandarins. The critical challenge is to develop robust and accurate universal models based on hundreds of highly heterogeneous citrus samples in order to design quality prediction models applicable to all fruits belonging to the genus Citrus, rather than models that can only be applied successfully to a single citrus species. This study evaluated and compared the performance of Modified Partial Least Squares (MPLS) and LOCAL regression algorithms for the prediction of major physical-quality parameters in all citrus fruits. Results showed that, while models developed using both linear (MPLS) and non-linear regression techniques (LOCAL) yielded promising results for the on-tree quality evaluation of citrus fruits, the LOCAL algorithm additionally increased the predictive capacity of models constructed for all the main parameters tested. These findings confirm that NIRS technology, used in conjunction with large databases and local regression strategies, increases the robustness of models for the on-tree prediction of citrus fruit quality; this will undoubtedly be of benefit to the citrus industry.

      PubDate: 2016-12-12T06:02:09Z
      DOI: 10.1016/j.biosystemseng.2016.11.007
      Issue No: Vol. 153 (2016)
       
  • Route planning evaluation of a prototype optimised infield route planner
           for neutral material flow agricultural operations
    • Authors: Gareth T.C. Edwards; Jørgen Hinge; Nick Skou-Nielsen; Andrés Villa-Henriksen; Claus Aage Grøn Sørensen; Ole Green
      Pages: 149 - 157
      Abstract: Publication date: January 2017
      Source:Biosystems Engineering, Volume 153
      Author(s): Gareth T.C. Edwards, Jørgen Hinge, Nick Skou-Nielsen, Andrés Villa-Henriksen, Claus Aage Grøn Sørensen, Ole Green
      The need to decrease unit production costs has led agricultural industries to develop larger and consequently heavier machinery. While this has increased the productivity of single machines, it has also caused significant soil compaction, which may cause reduced crop yield and crop quality. Therefore, mechanisation solutions that have both lower unit costs and reduce the risk of soil compaction are needed. Optimising infield routes will reduce labour costs, fuel consumption and field trafficking intensity, providing important benefits for infield operations. In this paper, a prototype of an optimised infield route planning tool for neutral material flow operations is evaluated. The evaluation parameters focused on distance and traffic intensity reductions, comparing the routes proposed by the tool prototype and the routes followed by a professional operator during mowing operations. The tool requires some minimum inputs: field boundaries, field gates, working width and minimum turning radius, in order to provide an optimised route. Twelve fields were recorded by a Global Positioning System (GPS) during mowing operations and later compared with the routes proposed by the tool. In all fields, the operator's normal route was longer in distance than the route proposed by the tool, being up to 18.4% longer. In total, 9.2 km of infield distance was saved, i.e. 7.5%. The traffic intensity was reduced in all fields, except for two of the smallest fields, where it equalled that of the normal route. Specifically, the traffic intensity was reduced in the working areas, as the tool confined all non-working distance to the headlands.

      PubDate: 2016-12-12T06:02:09Z
      DOI: 10.1016/j.biosystemseng.2016.10.007
      Issue No: Vol. 153 (2016)
       
  • Sensing soil condition and functions
    • Authors: Abdul M. Mouazen; Zhou Shi; Marc Van Meirvenne
      Pages: 1 - 2
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Abdul M. Mouazen, Zhou Shi, Marc Van Meirvenne


      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.10.006
      Issue No: Vol. 152 (2016)
       
  • Using electromagnetic induction method to reveal dynamics of soil water
           and salt during continual rainfall events
    • Authors: Zhi-Yun Jiang; Xiao-Yan Li; Hua-Wu Wu; Xiong Xiao; Hui-Ying Chen; Jun-Qi Wei
      Pages: 3 - 13
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Zhi-Yun Jiang, Xiao-Yan Li, Hua-Wu Wu, Xiong Xiao, Hui-Ying Chen, Jun-Qi Wei
      The spatial patterns and dynamics of soil water and salt at the field scale between rainfall events are not well understood due to a lack of appropriate instruments for measurements. In this study, we conducted time series EMI surveys and then mapped apparent electrical conductivity (ECa) to estimate the relative changes in soil water and salt in an Achnatherum splendens steppe ecosystem in Qinghai Lake watershed, China. The results indicated that ECa could be used as a surrogate for interpreting changes of water and salt content in soil. The ECa images clearly showed that ECa values increased rapidly after rainfall events, and the increased amplitudes of ECa values in soils under A. splendens (AS) were obviously greater than that of soil in the interspaces between A. splendens tussocks (IAS). This demonstrated that rainwater infiltrated faster and in greater quantity into the soils under AS because of their coarse-textured surface soils with greater macroporosity and higher hydraulic conductivity as compared to the interspace soils. Moreover, the increasing salinity in AS and decreasing salinity in IAS after rainfall events suggested that overland flow might perhaps have occurred from the interspaces into A. splendens areas. The temporal stability of ECa maps demonstrated that there was great soil variability at the study plot, especially in soil salt. This study highlighted that the time series ECa images could qualitatively capture dynamics of soil water and salt at the field scale after rainfall events, and it linked the dynamics of soil water and salt to vegetation variability.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.03.011
      Issue No: Vol. 152 (2016)
       
  • Assessment of soil properties in situ using a prototype portable MIR
           spectrometer in two agricultural fields
    • Authors: Wenjun Ji; Viacheslav I. Adamchuk; Asim Biswas; Nandkishor M. Dhawale; Bharath Sudarsan; Yakun Zhang; Raphael A. Viscarra Rossel; Zhou Shi
      Pages: 14 - 27
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Wenjun Ji, Viacheslav I. Adamchuk, Asim Biswas, Nandkishor M. Dhawale, Bharath Sudarsan, Yakun Zhang, Raphael A. Viscarra Rossel, Zhou Shi
      Mid-infrared (MIR) soil spectroscopy has shown applicability to predict selected properties through various laboratory studies. However, reports on the successful use of MIR instruments in field conditions (in situ) have been limited. In this study, a small portable prototype MIR (898–1811 cm−1) spectrometer was used to collect soil spectra from two agricultural fields (predominantly organic and mineral soils). Both fields were located at Macdonald Campus of McGill University in Ste-Anne-de-Bellevue, Quebec, Canada. In each of the 120 predefined field locations, in situ spectroscopic measurements were repeated three times and one representative soil sample was analyzed following conventional laboratory procedures. For every soil property, a field-specific partial least squares regression (PLSR) model was developed and evaluated using a leave-one-out cross-validation routine. Each soil property was evaluated in terms of the accuracy and reproducibility of model predictions. Among tested soil properties, soil organic matter, water content, bulk density, cation exchange capacity (CEC), Ca and Mg yielded higher model performance indicators (R2 > 0.50 and RPD > 1.40) as compared to soil pH, Fe, Cu, phosphorus, nitrate-nitrogen, K or Na. In most instances, the error estimate representing the prediction reproducibility was found to be as high as 50% of the overall prediction error. This was due to the combination of optical and electrical noise and soil micro-variability causing soil spectra representing the same field location to yield different predictions.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.06.005
      Issue No: Vol. 152 (2016)
       
  • Use of geophysical data for assessing 3D soil variation in a durum wheat
           field and their association with crop yield
    • Authors: Giovanni Cavallo; Daniela De Benedetto; Annamaria Castrignanò; Ruggiero Quarto; Alessandro Vittorio Vonella; Gabriele Buttafuoco
      Pages: 28 - 40
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Giovanni Cavallo, Daniela De Benedetto, Annamaria Castrignanò, Ruggiero Quarto, Alessandro Vittorio Vonella, Gabriele Buttafuoco
      From the perspective of Precision Agriculture, the delineation of management zones in agricultural fields to optimise the use of soil and water resources and increase farmer's profitability requires knowledge of fine-scale variability. The objective of this paper is to delineate management zones in terms of yield performance verifying the suitability of Ground Penetrating Radar (GPR) to assess spatial variation of soil properties. In a durum wheat field in southern Italy, yield data were recorded and a GPR survey carried out after harvesting. On the basis of spatial distribution of the yield, the field was split into four management zones (MZs) and the expected values and standard deviations of GPR signal amplitude data were estimated using polygon kriging for each MZ. In order to interpret the results and assess the resistivity of the soil, the total sand content and bulk electrical conductivity from an electromagnetic induction (EMI) sensor were estimated by polygon kriging. The acquisition of very fine-scale soil information with GPR allowed 3D variability in the field to be imaged. Further, the study has shown the existence of a physically-based relationship between the yield of the wheat and the structural properties of the soil detected by GPR.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.07.002
      Issue No: Vol. 152 (2016)
       
  • Microscope-based computer vision to characterize soil texture and soil
           organic matter
    • Authors: Bharath Sudarsan; Wenjun Ji; Asim Biswas; Viacheslav Adamchuk
      Pages: 41 - 50
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Bharath Sudarsan, Wenjun Ji, Asim Biswas, Viacheslav Adamchuk
      Characterization and quantification of soil properties are important for the optimum use and management our soil. While Soil texture is an important factor for decision making in agriculture, civil engineering and other industries, soil organic matter (SOM) is the backbone of soil health and quality and also affects a range of other soil properties and processes. Traditional methods for estimating these soil properties are time consuming and laborious. This paper discloses the design and development of a new cost effective in situ computer vision-based sensor system to estimate soil texture and SOM. A small and inexpensive hand-held microscope was used to develop an image acquisition system. Images acquired in laboratory with variable texture and SOM were processed using means of geospatial data analysis based computer vision algorithm. Simple linear regression predictive relationships were developed to estimate soil texture and SOM using various computed parameters of acquired imagery. Predicted sand (coefficients of determination, R2 = 0.63) and SOM (R2 = 0.83) were in good agreement with the laboratory measurement. These correspond to root mean square error of 84.7 g sand kg−1 of soil and 0.11 log (SOM %) for soils exhibiting the range of % sand from 3.4 to 59.3 and % SOM from 5.5 to 72.8, respectively. Low cost and the portability of the acquisition system and the computer vision algorithm developed in this study suggested suitability for its use in both laboratory and field conditions and shows promise as a proximal soil sensor.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.06.006
      Issue No: Vol. 152 (2016)
       
  • Assessment of laboratory VIS-NIR-SWIR setups with different spectroscopy
           accessories for characterisation of soils from wildfire burns
    • Authors: Olga A. Rosero-Vlasova ​; Fernando Pérez-Cabello; Raquel Montorio Llovería; Lidia Vlassova
      Pages: 51 - 67
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Olga A. Rosero-Vlasova ​, Fernando Pérez-Cabello, Raquel Montorio Llovería, Lidia Vlassova
      Thousands of hectares of Mediterranean forests are burned every year. Fires affect all the landscape components. They trigger erosion processes, which can have catastrophic consequences. Thus, detection and post-fire monitoring of soil properties is of great importance. Changes in soil caused by the fire can be detected by proximal soil sensing. In this context, the study evaluates the applicability of laboratory experimental setups for spectral analysis of burnt soils. Three setups of Analytical Spectral Device (ASD) FieldSpec®4 spectroradiometer with different spectroscopy accessories (external integrating sphere, illuminator lamp and contact probe) were used for measurement of reflectance spectra and evaluation of soil organic matter (SOM) in 82 soil samples from wildfire burns in Aragon, Northern Spain. No statistically significant differences were detected between values obtained by different setups. Lower reflectances registered with integrating sphere are probably due to the fact that the internal cavity of the device is not perfectly spherical because of the existence of multiple port windows. Measurements with Illuminator lamp and contact probe were more stable and corresponding calibration models for SOM built using partial least square regression combined with step-down variable selection algorithm (SA-PLSR) demonstrated acceptable predictive ability (0.75 ≤ R2 V ≤ 0.81; 2.00 ≤ RPD ≤ 2.55). The coefficients are ∼10% higher than those obtained with the integrating sphere. The study demonstrated feasibility of using Visible – Near InfraRed – Short Wave InfraRed (VIS-NIR-SWIR) spectroscopy for monitoring post-fire evolution of burnt soils and showed that the choice of the appropriate accessory (e.g., Illuminator lamp) improves the reliability of SOM estimations.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.06.011
      Issue No: Vol. 152 (2016)
       
  • Soil physical property estimation from soil strength and apparent
           electrical conductivity sensor data
    • Authors: Yongjin Cho; Kenneth A. Sudduth; Sun-Ok Chung
      Pages: 68 - 78
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Yongjin Cho, Kenneth A. Sudduth, Sun-Ok Chung
      Proximal soil sensing is an attractive approach for quantifying soil properties, but many currently available sensors do not respond to a single soil property. For example, soil strength and apparent electrical conductivity (ECa) sensor measurements are significantly affected by soil texture, bulk density (BD), and water content (WC). The objective of this study was to explore the potential for estimating soil texture, BD, and WC using combinations of sensor-based soil strength and ECa data obtained from sites with varying soil physical properties. Data collected from three research sites in Missouri included on-the-go horizontal soil strength at five depths up to 0.5 m on a 0.1-m interval, cone index measurements at the same depths, ECa measured by a Veris 3100, and depth-dependent, laboratory-determined soil properties. An ECa model inversion approach was used to generate layer EC values corresponding to the depth increments of the other variables. Fits of models using EC to estimate WC were variable (R2 = 0.31–0.79). Best fitting BD estimation models (R2 = 0.11–0.55) generally included EC, but soil strength was included in fewer than half of the models. BD model fits were improved considerably by adding lab-measured WC to the model (R2 = 0.30–0.86), suggesting the need for a WC sensor. Soil clay texture fraction models based on EC and WC fit well (R2 = 0.80–0.93). This study showed the potential of combining data from multiple mobile proximal sensors to estimate important soil physical properties.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.07.003
      Issue No: Vol. 152 (2016)
       
  • Prediction of soil cation exchange capacity using visible and near
           infrared spectroscopy
    • Authors: Yahya Ulusoy; Yücel Tekin; Zeynal Tümsavaş; Abdul M. Mouazen
      Pages: 79 - 93
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Yahya Ulusoy, Yücel Tekin, Zeynal Tümsavaş, Abdul M. Mouazen
      This study was undertaken to investigate the application of visible and near infrared (vis–NIR) spectroscopy for determining soil cation exchange capacity (CEC) under laboratory and on-line field conditions. Measurements were conducted in two fields with clay texture in field 1 (F1) and clay-loam texture in field 2 (F2) both in Turkey. Partial least squares (PLS) regression analyses with full cross-validation were carried out to establish CEC models using three datasets of F1, F2 and F1 + F2. Analytically-measured, laboratory vis–NIR and on-line vis–NIR predicted maps were produced and compared statistically by kappa coefficient. Results of the CEC prediction using laboratory vis–NIR data gave good prediction results, with averaged r 2 values of 0.92 and 0.72, root mean squared errors of prediction (RMSEP) of 1.89 and 1.54 cmol kg−1 and residual prediction deviations (RPD) of 3.69 and 1.89 for F1 and F2, respectively. Less successful predictions were obtained for the on-line measurement with r 2 of 0.75 and 0.7, RMSEP of 4.79 and 1.76 cmol kg−1 and RPD of 1.45 and 1.56 for F1 and F2, respectively. Comparisons using kappa statistics test indicated a significant agreement (κ = 0.69) between analytically-measured and laboratory vis–NIR predicted CEC maps of F1, while poorer agreement was found for F2 (κ = 0.43). A moderate spatial similarity was also found between analytically-measured and on-line vis–NIR predicted CEC maps in F1 (κ = 0.50) and F2 (κ = 0.49). This study suggests that soil CEC can be satisfactorily analysed using vis–NIR spectroscopy under laboratory conditions and with somewhat less precision under on-line scanning conditions.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.03.005
      Issue No: Vol. 152 (2016)
       
  • Predicting total dissolved salts and soluble ion concentrations in
           agricultural soils using portable visible near-infrared and mid-infrared
           spectrometers
    • Authors: Jie Peng; Wenjun Ji; Ziqiang Ma; Shuo Li; Songchao Chen; Lianqing Zhou; Zhou Shi
      Pages: 94 - 103
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Jie Peng, Wenjun Ji, Ziqiang Ma, Shuo Li, Songchao Chen, Lianqing Zhou, Zhou Shi
      Soil salinization is the primary obstacle to sustainable agricultural development in arid regions. Because total dissolved salts and soluble ion content are the primary indicators of the degree of soil salinization, their accurate estimation is essential to the determination of appropriate soil salinization remediation techniques, irrigation regimes, and the agricultural distribution layout. A total of 261 soil samples were collected from agricultural fields in the province of Xinjiang, China. A portable Fourier transform (FT) mid-infrared (MIR) spectrometer (4000–600 cm−1) and a visible near-infrared (VNIR) field spectrometer (350–2500 nm) were used to obtain soil spectra. We subsequently used partial least-square regression (PLSR) and support vector machine (SVM) algorithms to establish models in VNIR, MIR, and VNIR–MIR regions. The main objectives of this study are (i) to investigate the possibility of using spectroscopic techniques to predict total dissolved salts and soluble ion content; (ii) to compare the prediction accuracy of these soil properties in the VNIR, MIR, and VNIR–MIR spectral regions; (3) to compare the prediction accuracy with linear and nonlinear algorithms. Our findings demonstrated that spectroscopic techniques are a promising way to predict total dissolved salts and soluble ion content. Good predictions were obtained for total dissolved salts content, HCO 3 − , SO 4 2 − and Ca2+, satisfactory for Mg2+, Cl−, and Na+, but poor for K+. This work demonstrates the potential of portable VNIR and MIR spectrometers as proximal soil sensors for more efficient soil analysis and acquisition of soil salinity information.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.04.015
      Issue No: Vol. 152 (2016)
       
  • Machine learning based prediction of soil total nitrogen, organic carbon
           and moisture content by using VIS-NIR spectroscopy
    • Authors: Antonios Morellos; Xanthoula-Eirini Pantazi; Dimitrios Moshou; Thomas Alexandridis; Rebecca Whetton; Georgios Tziotzios; Jens Wiebensohn; Ralf Bill; Abdul M. Mouazen
      Pages: 104 - 116
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Antonios Morellos, Xanthoula-Eirini Pantazi, Dimitrios Moshou, Thomas Alexandridis, Rebecca Whetton, Georgios Tziotzios, Jens Wiebensohn, Ralf Bill, Abdul M. Mouazen
      It is widely known that the visible and near infrared (VIS-NIR) spectroscopy has the potential of estimating soil total nitrogen (TN), organic carbon (OC) and moisture content (MC) due to the direct spectral responses these properties have in the near infrared (NIR) region. However, improving the prediction accuracy requires advanced modelling techniques, particularly when measurement is planned for fresh (wet and un-processed) soil samples. The aim of this work is to compare the predictive performance of two linear multivariate and two machine learning methods for TN, OC and MC. The two multivariate methods investigated included principal component regression (PCR) and partial least squares regression (PLSR), whereas the machine learning methods included least squares support vector machines (LS-SVM), and Cubist. A mobile, fibre type, VIS-NIR spectrophotometer was utilised to collect soil spectra (305–2200 nm) in diffuse reflectance mode from 140 wet soil samples collected from one field in Germany. The results indicate that machine learning methods are capable of tackling non-linear problems in the dataset. LS-SVMs and the Cubist method out-performed the linear multivariate methods for the prediction of all three soil properties studied. LS-SVM provided the best prediction for MC (root mean square error of prediction (RMSEP) = 0.457% and residual prediction deviation (RPD) = 2.24) and OC (RMSEP = 0.062% and RPD = 2.20), whereas the Cubist method provided the best prediction for TN (RMSEP = 0.071 and RPD = 1.96).

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.04.018
      Issue No: Vol. 152 (2016)
       
  • How well can VNIR spectroscopy distinguish soil classes?
    • Authors: Rong Zeng; Gan-Lin Zhang; De-Cheng Li; David G. Rossiter; Yu-Guo Zhao
      Pages: 117 - 125
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Rong Zeng, Gan-Lin Zhang, De-Cheng Li, David G. Rossiter, Yu-Guo Zhao
      Visible near-infrared (VNIR) spectra can provide rich information on soil physical and chemical properties, which implies the possibility of using soil spectra to aid in the discrimination of soil types. Pedological soil classification systems use a selected set of soil properties to identify diagnostic horizons and features, and to build a classification key. This research explored the application of VNIR spectra to classify typical soil profiles collected in Anhui province, China. The 279 soil profiles used are classified into five orders (Cambosols, Vertosols, Argosols, Primosols and Anthrosols), six suborders and 21 groups according to Chinese Soil Taxonomy. Soil spectra were collected within 350–2500 nm and principal component analysis (PCA) was applied to reduce data dimension. These principal components were used as independent variables in multinomial logistic regression for soil classification. Topsoil spectra, subsoil spectra and their combination were compared for prediction accuracy. Accuracy achieved at the level of suborder using spectra of topsoil, subsoil and combined horizons were 76.3%, 71.3% and 70.3% respectively, while the results for the level of soil group using the topsoil horizon was 40.5%. Since topsoil spectra alone achieved a prediction accuracy of more than 75%, reflectance spectroscopy can be judged a promising tool for soil classification. Taxonomic distances between classes calculated on the basis of physio-chemical properties and spectra were quite different, showing that the concept of distance between classes in feature space depends on the features chosen for evaluation. Taxonomic distances can serve as a supplement for better selection and evaluation of prediction models.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.04.019
      Issue No: Vol. 152 (2016)
       
  • Improving spatial estimation of soil organic matter in a subtropical hilly
           area using covariate derived from vis-NIR spectroscopy
    • Authors: Xian-Li Xie; An-Bo Li
      Pages: 126 - 137
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Xian-Li Xie, An-Bo Li
      Spatial variability of soil properties is complex in the hilly areas of subtropical China that are heavily influenced by human activities. Large datasets are needed for achieving accurate spatial estimates of soil properties in these areas, and it can be difficult due to the budget and time restrictions. Soil diffuse reflectance contains the integrated information of soil properties, thus can provide useful auxiliary variables to improve the spatial estimation of soil properties. This study aimed to improve the spatial estimation of soil organic matter (OM) in a typical subtropical hilly area of China, with principal component (PC) extracted from soil visible and near-infrared (vis-NIR) reflectance spectroscopy used as co-variable. Spatial estimation was performed using ordinary kriging (OK) and co-kriging (CK). A set of 125 samples collected from soil surface layer was used. To simulate the under-sampling situation of target variable, a subset was constructed by randomly sampling 50% of the total samples. The results showed that compared to OK, CK provided the decreased root mean square error (RMSE) by about 45% in cross validations and improved estimation map with much lower estimation variances. This study indicates that for the soil properties and functional attributes that are well correlated with soil reflectance and are sparsely sampled, combined use of soil reflectance spectroscopy technique and multivariate geostatistical method will provide a powerful solution for accurate spatial estimation of soil OM.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.06.007
      Issue No: Vol. 152 (2016)
       
  • Can subsurface soil salinity be predicted from surface spectral
           information? – From the perspective of structural equation modelling
    • Authors: Ya Liu; Xianzhang Pan; Changkun Wang; Yanli Li; Rongjie Shi
      Pages: 138 - 147
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Ya Liu, Xianzhang Pan, Changkun Wang, Yanli Li, Rongjie Shi
      An efficient and reliable method for detecting soil salinity in deep saline soils using remote sensing is required to better manage soil salinization. In this study, a laboratory evaporation experiment was conducted to determine how subsurface soil salinity can be determined using soil surface spectra. Ten soil columns were observed, and measurements were taken at specific time intervals to monitor the variations in soil salinity and moisture content at depths of 5 cm and 15 cm relative to soil surface spectra during the evaporation process. The structural equation modelling (SEM) method was used to analyse the relationships between the spectral reflectance data and the salt content in the subsurface soil (15 cm). The results showed significant correlations (standard path coefficient = −0.37, t = −6.00) between the spectral reflectance of the soil surface and the subsurface soil salinity and between different types of multispectral data, such as the Landsat Thematic Mapper (TM) data, and the subsurface soil salinity. Overall, the results implied that surface soil spectral information can be used to capture some subsurface soil properties and that remote sensing images could provide an alternative method for monitoring changes in deeper soils.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.06.008
      Issue No: Vol. 152 (2016)
       
  • Estimation of wet aggregation indices using soil properties and diffuse
           reflectance near infrared spectroscopy: An application of classification
           and regression tree analysis
    • Authors: Bernard K. Waruru; Keith D. Shepherd; George M. Ndegwa; Andrew M. Sila
      Pages: 148 - 164
      Abstract: Publication date: December 2016
      Source:Biosystems Engineering, Volume 152
      Author(s): Bernard K. Waruru, Keith D. Shepherd, George M. Ndegwa, Andrew M. Sila
      Soil aggregation is critical for assessing soil health; however, conventional aggregation measurement is laborious and expensive. The performance of near infrared diffuse reflectance spectroscopy (NIR) and basic soil properties for estimation of wet aggregation indices was investigated. Two samples sets representing different soils from across Lake Victoria Basin in Kenya were used for the study. A model calibration set (n = 136) was obtained following a conditioned Latin hypercube sampling, and validation set (n = 120) using a spatially stratified random sampling strategy. Spectral measurements were obtained for air-dried (<2 mm) soil using a Fourier-transform NIR spectrometer. Soil laboratory reference data were also obtained for wet aggregation indices (WSA): macro, micro and unstable fractions using two different wet-sieving pretreatments. Soil properties were screened as candidate predictors of WSA using Classification and Regression Tree (CART regression) analysis. WSA were calibrated to soil predictors and to smoothed first derivative NIR spectra using partial least squares (PLS) regression. Key soil predictors were: soil organic carbon and pH water (macro), water dispersible clay (WDC) (micro) and exchangeable sodium (unstable). Full cross validation of NIR PLS prediction of stable macro, micro, unstable aggregates, and for WDC gave RPD (ratio of prediction deviation) of 1.4–2.0. Independent testing of NIR PLS gave RPD = 1.4 for macro and RPD = 1.2–1.0 for unstable and soil predictors. NIR could estimate macro and unstable fractions with moderate reliability, and; NIR was superior over soil properties for stability pedotransfer purposes. Further efforts should widely test performance for a wider range of soil types and calibration strategies for improved geographic transferability of models.

      PubDate: 2016-12-05T10:45:58Z
      DOI: 10.1016/j.biosystemseng.2016.08.003
      Issue No: Vol. 152 (2016)
       
  • Mechanisms of natural ventilation in livestock buildings: Perspectives on
           past achievements and future challenges
    • Authors: Li Rong; Bjarne Bjerg; Thomas Batzanas; Guoqiang Zhang
      Pages: 200 - 217
      Abstract: Publication date: November 2016
      Source:Biosystems Engineering, Volume 151
      Author(s): Li Rong, Bjarne Bjerg, Thomas Batzanas, Guoqiang Zhang
      Studies on the mechanisms of natural ventilation in livestock buildings are reviewed and influences on discharge and pressure coefficients are discussed. Compared to studies conducted on buildings for human occupation and industrial buildings which focus on thermal comfort, ventilation systems, indoor air quality, building physics and energy etc., our understanding of the mechanisms involved in natural ventilation of livestock buildings are still limited to the application of the orifice equation. It has been observed that the assumptions made for application of the orifice equation are not valid for wind-induced cross ventilation through large openings. This review identifies that the power balance model, the concept of stream tube and the local dynamic similarity model has helped in the fundamental understanding of wind-induced natural ventilation in buildings for human occupation and industrial buildings. These concepts have distinguished the flow through large openings from that of ‘cracks’ (i.e. small openings), which is where the orifice equation is normally used for prediction of airflow rate. More field measurements on the effect of wind turbulence on ventilation rate need to be encouraged, particularly under conditions where the mean pressure differences through building openings are much lower than the fluctuations of pressure differences. Research on bidirectional flow that occurs at openings is also limited.

      PubDate: 2016-11-17T10:35:41Z
      DOI: 10.1016/j.biosystemseng.2016.09.004
      Issue No: Vol. 151 (2016)
       
  • Crop reflectance monitoring as a tool for water stress detection in
           greenhouses: A review
    • Authors: Nikolaos Katsoulas; Angeliki Elvanidi; Konstantinos P. Ferentinos; Murat Kacira; Thomas Bartzanas; Constantinos Kittas
      Pages: 374 - 398
      Abstract: Publication date: November 2016
      Source:Biosystems Engineering, Volume 151
      Author(s): Nikolaos Katsoulas, Angeliki Elvanidi, Konstantinos P. Ferentinos, Murat Kacira, Thomas Bartzanas, Constantinos Kittas
      Multisensory platforms for remote sensing measurements offer the possibility to monitor in real-time the crop health status without affecting the crop and environmental conditions. The concept of the speaking plant approach, and plant response based sensing in general, could be valuable providing a better understanding of the interactions between the microclimate and the physical conditions of the plants. Early detection of plant stress is critical, especially in intensive production systems, in order to minimise both acute and chronic loss of productivity. Non-contact and non-destructive sensing techniques can continuously monitor plants and enable automated sensing and control capabilities. This paper reviews past research and recent advances regarding the sensors and approaches used for crop reflectance measurements and the indices used for crop water and nutrient status detection. The most practical and effective indices are those based on ground reflectance sensors data which are evaluated in terms of their efficiency in detecting plant water status under greenhouse conditions. Some possible applications of this approach are summarised. Although crop reflectance measurements have been widely used under open field conditions, there are several factors that limit the application of reflectance measurements under greenhouse conditions. The most promising type of sensors and indices for early stress detection in greenhouse crops are presented and discussed. Future research should focus on real time data analysis and detection of plant water stress using advanced data analysis techniques and to the development of indices that may not be affected by plant microclimate.

      PubDate: 2016-11-17T10:35:41Z
      DOI: 10.1016/j.biosystemseng.2016.10.003
      Issue No: Vol. 151 (2016)
       
  • Multiscaling properties of soil images
    • Authors: Iván G. Torre; Juan C. Losada; Ana M. Tarquis
      Abstract: Publication date: Available online 21 December 2016
      Source:Biosystems Engineering
      Author(s): Iván G. Torre, Juan C. Losada, Ana M. Tarquis
      Soil structure may be defined as the spatial arrangement of soil particles, aggregates and pores. The geometry of each one of these elements and their spatial arrangement has a great influence on the transport of fluids and solutes through the soil. Soil thin sections (STS) have been widely used to characterise them and more recently computed tomography (CT) has provided an alternative for observing intact soil structure in 3D. Both types of images are grey-scale, normally with 8 bit depth. In this work we propose to quantify the structural complexity of their spatial arrangement by applying multifractal analysis (MFA) to the original grey images no previous binarisation and compare the results in 2D and 3D. Their singularities (α) and f(α) spectra calculated have been used for this comparison. With this purpose, an original CT-scan image of 256 × 256 × 256 voxel-thick slices of a soil was used. Three 2D subsamples were extracted in three different directions to analyse and compare with the 3D structure. All images analysed presented a multiscaling character, in 2D and 3D, pointing out that the lower grey values are mainly influencing the scaling behaviour. The multifractal parameters were influenced by 2D slice position and direction and their values were lower than the ones obtained in the 3D image analysis. Therefore, in order to compare soil structures based on grey images, a 3D volume is desirable. The multiscaling nature of these images suggests using these algorithms as a basis to create synthetic images for testing thresholding algorithms.

      PubDate: 2016-12-26T15:33:15Z
      DOI: 10.1016/j.biosystemseng.2016.11.006
       
  • Field-crop-sprayer potential drift measured using test bench: Effects of
           boom height and nozzle type
    • Authors: Paolo Balsari; Emilio Gil; Paolo Marucco; Jan C. van de Zande; David Nuyttens; Andreas Herbst; Montserrat Gallart
      Abstract: Publication date: Available online 2 November 2016
      Source:Biosystems Engineering
      Author(s): Paolo Balsari, Emilio Gil, Paolo Marucco, Jan C. van de Zande, David Nuyttens, Andreas Herbst, Montserrat Gallart
      Because of variations in environmental conditions, spray-drift field measurements following ISO 22866:2005 involve complicated and time-consuming experiments often with low repeatability. Therefore, simple, repeatable, and precise alternative drift assessment methods that are complementary to the official standards are required. One of the alternatives is the use of a drift test bench for field crop sprayers. Previous studies have demonstrated that the drift test bench can be considered an adequate complement to existing standard protocols for field drift measurements. In this study, in order to further improve the methodology and to evaluate the possibility of classifying different field-crop-sprayer settings according to drift risk using a test bench, a series of tests were performed in a test hall. A conventional mounted Delvano HD3 crop sprayer (Delvano, Kuurne, Belgium) equipped with an 800-l spray tank and a 15-m-wide stainless steel spray boom was used. Eight different sprayer setups were tested, involving three nozzle types (TeeJet XR 110 04, Agrotop TDXL 110 04 and Micron Micromax 3) and three boom heights (0.30, 0.50, and 0.70 m). For the drift classification, the reference sprayer drift behaviour was defined as that obtained using conventional flat fan TeeJet XR 110 04 nozzles operated at 0.30 MPa and at a boom height of 0.50 m. The different sprayer setups were successfully assigned to different drift reduction classes, and the results underlined the effects of nozzle type and boom height on the potential drift. The feasibility of the test-bench methodology for classifying field-crop-sprayer drift according to ISO 22369-1:2006 was demonstrated.

      PubDate: 2016-11-17T10:35:41Z
      DOI: 10.1016/j.biosystemseng.2016.10.015
       
  • Assessment of spray drift from pesticide applications in soybean crops
    • Authors: Mariana R. Bueno; João Paulo A. R. da Cunha; Denise G. de Santana
      Abstract: Publication date: Available online 12 November 2016
      Source:Biosystems Engineering
      Author(s): Mariana R. Bueno, João Paulo A. R. da Cunha, Denise G. de Santana
      Determining the downwind behaviour of sprays generated by different equipment is fundamental in managing pesticide applications. The objective of this study was to establish spray drift curves for soybean crops (Glycine max) in Brazilian meteorological conditions using different spray nozzles and to compare them with the model coefficients generated in European conditions. The study was conducted in Uberlândia, MG, Brazil, in a completely randomised block design with a split plot arrangement (4 × 20), with 10 replications. The study measured ground spray drift deposits by applications with a spray volume of 150 l ha−1 and four nozzle types: flat-fan standard and venturi – XR (fine spray) and AIXR (coarse spray); wide angle standard flat-fan and venturi – TT (medium spray) and TTI (very coarse spray), at 20 different sampling distances downwind, parallel to the crop line outside the target area, spaced 2.5 m apart. The deposits on filter paper placed on the soil were evaluated using a fluorescent tracer added to the tank of a boom sprayer and quantified by fluorimetry. Three drift prediction models were obtained for the soybean crop, considering the 90th percentile, for the nozzles XR, TT and AIXR, with exponential tendencies for four parameter regression models. The coefficients obtained were statistically different from those of the Dutch Drift Model for cereal cultivation and from those of the German Drift Model for field crops. Drift was reduced by increasing the size of the droplets produced particularly close to the cropping zones.

      PubDate: 2016-11-17T10:35:41Z
      DOI: 10.1016/j.biosystemseng.2016.10.017
       
  • Development and validation of a 3D CFD model of drift and its application
           to air-assisted orchard sprayers
    • Authors: Ashenafi T. Duga; Mulugeta A. Delele; Kris Ruysen; Donald Dekeyser; David Nuyttens; Dany Bylemans; Bart M. Nicolai; Pieter Verboven
      Abstract: Publication date: Available online 5 November 2016
      Source:Biosystems Engineering
      Author(s): Ashenafi T. Duga, Mulugeta A. Delele, Kris Ruysen, Donald Dekeyser, David Nuyttens, Dany Bylemans, Bart M. Nicolai, Pieter Verboven
      Pesticides play an important role in providing high crop yields by minimising the risks associated with pests but some of the sprayed product may move beyond the intended target and result in drift. Modelling approaches can help understand the behaviour of spray drift using computer simulations. However, modelling drift from orchard spraying presents particular challenges: (1) the moving spray interacts with the canopy before drifting outside the target area; (2) the vertical wind profile in the orchard is different to neighbouring fields where there is different vegetation; (3) the moving air jet from the air-assistance cannot be ignored because the airspeed of the fan is usually higher than the wind speed. This work presents a three-dimensional (3D) computational fluid dynamics (CFD) model of spray drift from orchard sprayers that considers tree architecture, canopy wind flow and the movement of the sprayer to calculate sedimenting and airborne drift; thus tackling the challenges listed above. The model was validated against drift measurements from an apple orchard with different nozzles arrangements. The model was then used to evaluate the effect of drift reducing nozzles and fan airspeed on drift. The model predicted that drift reducing nozzles reduced the drifting distance by 50%, but increased near-tree ground deposition. This increase in ground deposition can be avoided whilst retaining the reduction in the drifting distance, by using a combination of drift reducing and standard nozzles. A reduced sprayer airflow can further reduce drift.

      PubDate: 2016-11-17T10:35:41Z
      DOI: 10.1016/j.biosystemseng.2016.10.010
       
 
 
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