Subjects -> BUSINESS AND ECONOMICS (Total: 3541 journals)
    - ACCOUNTING (132 journals)
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    - BUSINESS AND ECONOMICS (1229 journals)
    - CONSUMER EDUCATION AND PROTECTION (20 journals)
    - COOPERATIVES (4 journals)
    - ECONOMIC SCIENCES: GENERAL (212 journals)
    - ECONOMIC SYSTEMS, THEORIES AND HISTORY (235 journals)
    - FASHION AND CONSUMER TRENDS (20 journals)
    - HUMAN RESOURCES (103 journals)
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    - PUBLIC FINANCE, TAXATION (37 journals)
    - TRADE AND INDUSTRIAL DIRECTORIES (2 journals)

ECONOMIC SCIENCES: GENERAL (212 journals)                  1 2     

Showing 1 - 200 of 200 Journals sorted alphabetically
ACM Transactions on Economics and Computation     Hybrid Journal  
Acta Universitatis Lodziensis : Folia Oeconomica     Open Access  
Acta Universitatis Sapientiae, Economics and Business     Open Access   (Followers: 1)
Actualidad Económica     Open Access  
Advances in Management and Applied Economics     Open Access   (Followers: 8)
AFFRIKA Journal of Politics, Economics and Society     Full-text available via subscription   (Followers: 4)
African Journal of Economic and Management Studies     Hybrid Journal   (Followers: 10)
Agricultural and Food Economics     Open Access   (Followers: 7)
AgriEngineering     Open Access  
Agrosearch     Open Access  
AL-Qadisiyah Journal For Administrative and Economic sciences     Open Access   (Followers: 2)
American Economic Review     Full-text available via subscription   (Followers: 458)
American Journal of Economics     Open Access   (Followers: 14)
Análisis Economico     Open Access  
Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia     Open Access  
Annals of Financial Economics     Hybrid Journal   (Followers: 1)
Annals of Spiru Haret University. Economic Series     Open Access  
Applied Economic Analysis     Full-text available via subscription   (Followers: 1)
Applied Economic Perspectives and Policy     Hybrid Journal   (Followers: 15)
Applied Economics and Finance     Open Access   (Followers: 9)
Arthaniti : Journal of Economic Theory and Practice     Full-text available via subscription  
Asia-Pacific Journal of Accounting & Economics     Hybrid Journal   (Followers: 6)
Asian Journal of Economics and Empirical Research     Open Access  
Baltic Journal of Economics     Open Access   (Followers: 1)
BISE : Jurnal Pendidikan Bisnis dan Ekonomi     Open Access  
Botswana Journal of Economics     Open Access   (Followers: 1)
BRICS Journal of Economics     Open Access   (Followers: 6)
BRQ Business Review Quarterly     Open Access   (Followers: 1)
Buletin Studi Ekonomi     Open Access   (Followers: 2)
Business Strategy and Development     Hybrid Journal  
Central European Economic Journal     Open Access  
China Economic Quarterly International     Open Access  
China Finance and Economic Review     Open Access   (Followers: 4)
Ciencias Económicas     Open Access  
Cliodynamics     Open Access   (Followers: 2)
Cogent Economics & Finance     Open Access   (Followers: 3)
Danube     Open Access   (Followers: 3)
Desarrollo y Sociedad     Open Access   (Followers: 1)
Divergencia     Open Access  
ECA Sinergia : Revista Especializada en Economía, Contabilidad y Administración     Open Access  
Economía     Open Access  
EconomiA     Open Access  
ECONOMÍA     Open Access  
Economia & Região     Open Access   (Followers: 1)
Economic Analysis of Law Review     Open Access   (Followers: 4)
Economic Geology     Hybrid Journal   (Followers: 7)
Económicas CUC     Open Access  
Economics : Journal for Economic Theory and Analysis     Open Access   (Followers: 4)
Economics : The Open-Access, Open-Assessment Journal     Open Access  
Economics and Culture     Open Access  
Economics and Policy of Energy and the Environment     Full-text available via subscription   (Followers: 13)
Economics of Transportation     Partially Free   (Followers: 16)
Economy     Open Access   (Followers: 1)
Economy and Sociology / Economie şi Sociologie     Open Access   (Followers: 1)
Econosains : Jurnal Online Ekonomi Dan Pendidikan     Open Access  
Edunomic Jurnal Pendidikan Ekonomi     Open Access  
EFB Bioeconomy Journal     Open Access  
Ekonomi Bilimleri Dergisi     Open Access  
Ekonomia i Zarzadzanie. Economics and Management     Open Access  
Ekonomika (Economics)     Open Access  
Ekuilibrium : Jurnal Ilmiah Bidang Ilmu Ekonomi     Open Access  
Ekuitas : Jurnal Ekonomi dan Keuangan     Open Access  
El Trimestre Económico     Open Access  
Ensayos de Política Económica     Open Access  
Environmental & Socio-economic Studies     Open Access   (Followers: 1)
Environmental Economics     Open Access   (Followers: 3)
Equilibrium : Quarterly Journal of Economics and Economic Policy     Open Access   (Followers: 1)
Espacio Abierto     Open Access  
Estudios de Economia Aplicada / Studies of Applied Economics     Open Access   (Followers: 1)
Estudios Economicos     Open Access  
Expert Journal of Economics     Open Access  
Expresión Económica : Revista de Análisis     Open Access  
Global Business Perspectives     Hybrid Journal   (Followers: 3)
Health Economics Review     Open Access   (Followers: 9)
IMF Economic Review     Hybrid Journal   (Followers: 44)
Indian Growth and Development Review     Hybrid Journal  
Informe Econômico     Open Access   (Followers: 3)
Insight on Africa     Hybrid Journal   (Followers: 3)
Intellectual Economics     Open Access  
Interfaces Brasil/Canadá     Open Access   (Followers: 1)
International Journal of Applied Behavioral Economics     Full-text available via subscription   (Followers: 19)
International Journal of Ecological Economics and Statistics     Full-text available via subscription   (Followers: 5)
International Journal of Economics and Finance     Open Access   (Followers: 12)
International Journal of Economics and Financial Issues     Open Access   (Followers: 10)
International Journal of Energy Economics and Policy     Open Access   (Followers: 11)
International Journal of Management and Economics     Open Access   (Followers: 2)
International Journal of Regional Development     Open Access   (Followers: 1)
International Quarterly for Asian Studies     Open Access   (Followers: 2)
International Review of Economics Education     Hybrid Journal   (Followers: 2)
IQTISHODUNA     Open Access  
Istanbul Journal of Economics     Open Access  
Italian Economic Journal     Hybrid Journal   (Followers: 34)
JEJAK : Jurnal Ekonomi dan Kebijakan     Open Access  
JEKPEND : Jurnal Ekonomi dan Pendidikan     Open Access  
Journal for Labour Market Research     Open Access   (Followers: 11)
Journal of Accounting and Finance in Emerging Economies     Open Access  
Journal of Advanced Research in Law and Economics     Open Access   (Followers: 1)
Journal of Advanced Studies in Finance     Open Access   (Followers: 3)
Journal of Business Economics and Management     Open Access   (Followers: 2)
Journal of Business-to-Business Marketing     Hybrid Journal   (Followers: 13)
Journal of Developing Economies     Open Access   (Followers: 4)
Journal of Development Policy and Practice     Hybrid Journal   (Followers: 3)
Journal of Economic and Financial Sciences     Open Access   (Followers: 1)
Journal of Economic Asymmetries     Open Access  
Journal of Economic Development Policy     Open Access   (Followers: 7)
Journal of Economics and International Finance     Open Access   (Followers: 1)
Journal of Economics and Sustainable Development     Open Access   (Followers: 14)
Journal of Economics Bibliography     Open Access  
Journal of Economics Library     Open Access   (Followers: 8)
Journal of Economics, Finance and Administrative Science     Open Access  
Journal of Economics, Race, and Policy     Hybrid Journal   (Followers: 3)
Journal of Economy Culture and Society     Open Access  
Journal of Entrepreneurship and Public Policy     Hybrid Journal   (Followers: 7)
Journal of Finance and Economics     Open Access   (Followers: 13)
Journal of Financial and Quantitative Analysis     Full-text available via subscription   (Followers: 55)
Journal of Financial Economic Policy     Hybrid Journal   (Followers: 1)
Journal of Government and Economics     Open Access  
Journal of Interdisciplinary Economics     Hybrid Journal   (Followers: 1)
Journal of Life Economics     Open Access   (Followers: 2)
Journal of Management Control     Hybrid Journal   (Followers: 3)
Journal of Management for Global Sustainability     Open Access   (Followers: 1)
Journal of Markets & Morality     Partially Free  
Journal of Poverty and Social Justice     Hybrid Journal   (Followers: 33)
Journal of Research in Economics     Open Access   (Followers: 2)
Journal of Reviews on Global Economics     Open Access  
Journal of the Economic Science Association     Hybrid Journal   (Followers: 1)
Journal of the Economics of Ageing     Hybrid Journal   (Followers: 1)
Jurnal Ekonomi dan Studi Pembangunan     Open Access  
Jurnal Ekonomi KIAT     Open Access  
Jurnal Ekonomi Modernisasi     Open Access   (Followers: 1)
Jurnal Ekonomi Pembangunan     Open Access  
Jurnal Manajemen dan Kewirausahaan     Open Access  
Jurnal Pendidikan Ekonomi     Open Access  
Klinik Einkauf     Hybrid Journal  
Korea : Politik, Wirtschaft, Gesellschaft     Open Access  
L'Actualité économique     Full-text available via subscription   (Followers: 2)
Latin American Journal of Economics     Open Access   (Followers: 1)
Lecturas de Economía     Open Access  
Liberal Arts and Social Sciences International Journal (LASSIJ)     Open Access   (Followers: 1)
List Forum für Wirtschafts- und Finanzpolitik     Hybrid Journal  
Local Economy     Hybrid Journal   (Followers: 3)
Low Carbon Economy     Open Access   (Followers: 4)
Management Dynamics     Open Access  
Media Ekonomi dan Manajemen     Open Access  
MediaTrend     Open Access  
Modern Economy     Open Access   (Followers: 3)
Mondes en développement     Full-text available via subscription  
NBER Working Paper Series     Full-text available via subscription   (Followers: 22)
Nordic Journal of Health Economics     Open Access   (Followers: 5)
Open Pharmacoeconomics & Health Economics Journal     Open Access   (Followers: 1)
Pensamiento Crítico     Open Access  
Proceedings of Voronezh State University. Series: Economics and Management     Open Access  
Quantitative Economics     Full-text available via subscription   (Followers: 14)
Quantitative Economics Research     Open Access  
Quarterly Journal of Applied Theories of Economics     Open Access  
RDE : Revista de Desenvolvimento Econômico     Open Access  
Regards économiques     Open Access  
Regional Research of Russia     Hybrid Journal   (Followers: 4)
Regional Science Policy & Practice     Hybrid Journal   (Followers: 2)
Research in World Economy     Open Access   (Followers: 3)
Review of Economics and Development Studies     Open Access   (Followers: 2)
Review of Economics and Institutions     Open Access   (Followers: 3)
Review of Economics and Statistics     Hybrid Journal   (Followers: 143)
Review of Market Integration     Hybrid Journal   (Followers: 2)
Revista Brasileira de Desenvolvimento Regional     Open Access  
Revista CIFE : Lecturas de Economía Social     Open Access  
Revista de Análisis Económico     Open Access  
Revista de Economía     Open Access  
Revista ECONO : Facultad de Ciencias Económicas. UNLP     Open Access  
Revista Economia & Gestão     Open Access  
Revista Facultad de Ciencias Económicas: Investigación y Reflexión     Open Access  
Revista Finanzas y Política Económica     Open Access  
Revista Icade. Revista de las Facultades de Derecho y Ciencias Económicas y Empresariales     Full-text available via subscription  
Revista Latinoamericana de Desarrollo Económico     Open Access  
Revista Panorama Económico     Open Access   (Followers: 1)
Revista Sociedad y Economía     Open Access  
Revista Teoria e Evidência Econômica     Open Access  
Revista U.D.C.A Actualidad & Divulgación Científica     Open Access  
Revue économique     Full-text available via subscription   (Followers: 3)
Ruch Prawniczy, Ekonomiczny i Socjologiczny     Open Access  
RUDN Journal of Economics     Open Access  
Russian Journal of Economics     Open Access  
Sdü Vizyoner Dergisi     Open Access  
Semestre Económico     Open Access  
Shanlax International Journal of Economics     Open Access  
Sosyoekonomi     Open Access  
Staff Studies : Central Bank of Sri Lanka     Open Access  
Statistics and Economics     Open Access  
Studia Universitatis ?Vasile Goldis? Arad ? Economics Series     Open Access  
Supreme Court Economic Review     Full-text available via subscription   (Followers: 3)
Swiss Journal of Economics and Statistics     Open Access  
Tahghighat-e-Eghtesadi     Open Access  
Textos de Economia     Open Access  
Theoretical Economics Letters     Open Access   (Followers: 2)
Torun International Studies     Open Access  
Turkish Economic Review     Open Access  
World Economics     Full-text available via subscription   (Followers: 8)
Wroclaw Review of Law, Administration & Economics     Open Access  
Œconomia     Open Access  
Науковий вісник НУБіП України. Серія: Економіка, аграрний менеджмент, бізнес     Open Access  

        1 2     

Similar Journals
Journal Cover
AgriEngineering
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2624-7402
Published by MDPI Homepage  [84 journals]
  • AgriEngineering, Vol. 4, Pages 335-355: Edaphic Response and Behavior of
           Agricultural Soils to Mechanical Perturbation in Tillage

    • Authors: Frankline M. Mwiti, Ayub N. Gitau, Duncan O. Mbuge
      First page: 335
      Abstract: Mechanical perturbation constrains edaphic functionality of arable soils in tillage. Seasonal soil tool interactions disrupt the pristine bio-physio-mechanical characteristics of agricultural soils and crop-oriented ecological functions. They interfere with the natural balancing of nutrient cycles, soil carbon, and diverse organic matter that supports soil ecosystem interactions with crop rooting. We review soil working in tillage, associated mechanistic perturbations, and the edaphic response of affected soil properties towards cropping characteristics and behavior as soil working tools evolve. This is to further credit or discredit the global transition to minimum and no-till systems with a more specific characterization to soil properties and edaphic crop-oriented goals of soil tooling. Research has shown that improvement in adoption of conservation tillage is trying to characterize tilled soils with edaphic states of native soil agroecosystems rendering promising strategies to revive overworked soils under the changing climate. Soil can proliferate without disturbance whilst generation of new ecologically rich soil structures develops under more natural conditions. Researchers have argued that crops adapted to the altered physio-mechanical properties of cultivated soils can be developed and domesticated, especially under already impedance induced, mechanically risked, degraded soils. Interestingly edaphic response of soils under no-till soil working appeared less favorable in humid climates and more significant under arid regions. We recommend further studies to elucidate the association between soil health state, soil disturbance, cropping performance, and yield under evolving soil working tools, a perspective that will be useful in guiding the establishment of future soils for future crops.
      Citation: AgriEngineering
      PubDate: 2022-03-23
      DOI: 10.3390/agriengineering4020023
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 356-366: Prediction of Harvest Time of
           Tomato Using Mask R-CNN

    • Authors: Daichi Minagawa, Jeyeon Kim
      First page: 356
      Abstract: In recent years, the agricultural field has been confronting difficulties such as the aging of farmers, a shortage of workers, and difficulties for new farmers. Harvesting time prediction has the potential to solve these problems, and is expected to effectively utilize human resources, save labor, and reduce labor costs. To achieve harvesting time prediction, various works are being actively conducted. Methods for harvesting time prediction using meteorological information such as temperature and solar radiation, etc., and methods for harvesting time prediction using neural networks based on color information from fruit bunch images are being investigated. However, the prediction accuracy is still insufficient, and the harvesting time prediction for individual tomato fruits has not been studied. In this study, we propose a novel method to predict the harvesting time for individual tomato fruits. The method uses Mask R-CNN to detect tomato bunches and uses two types of ripeness determination to predict the harvesting time of individual tomato fruits. The experimental results showed that the accuracy of the prediction using the ratio of R values was better for the harvesting time prediction of tomatoes that are close to the harvesting time, and the accuracy of the prediction using the average of the differences between R and G in RGB values was better for the harvesting time prediction of tomatoes that are far from the harvesting time. These results show the effectiveness of the proposed method.
      Citation: AgriEngineering
      PubDate: 2022-03-25
      DOI: 10.3390/agriengineering4020024
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 367-379: Machine Learning Model for
           Assuring Bird Welfare during Transportation

    • Authors: Ali Moghadam, Harshavardhan Thippareddi, Ramana Pidaparti
      First page: 367
      Abstract: Bird welfare and comfort is highly impacted by extreme environments, including hot/cold temperatures, relative humidity, and heat production within the coops during loading at the farm, transportation, and holding at the processing plants. Due to the complexity of the multiphysics phenomena involving fluid flow, heat transfer, and multispecies mixtures (humidity) within the coops, machine learning models may be helpful to evaluate broiler welfare under various environments. Machine learning techniques (Artificial Neural Networks and Bayesian Optimization) were applied to estimate the desired parameters required to ensure broiler welfare inside the coops. Artificial Neural Networks (ANNs) were trained with the results of Computational Fluid Dynamics (CFD) simulations for various ranges of inputs related to the microenvironment. Input variables included air velocity, broiler heat production, ambient temperature, and relative humidity. The Output variable was the Enthalpy Comfort Index (ECI), which is a measure of the bird welfare. The trained networks were then analyzed using Bayesian Optimization (BO) for the inverse mapping of ANNs and to predict the range of acceptable input parameters for a desired output, i.e., ECI in the comfort level. Results indicate that reducing the broilers heat production inside the coop along with increasing fan velocity enhances the broiler welfare and the thermal microenvironment. The BO developed in this study provide the microenvironmental parameters to estimate the bird welfare that is comfortable.
      Citation: AgriEngineering
      PubDate: 2022-03-30
      DOI: 10.3390/agriengineering4020025
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 380-399: Development and Modeling of an
           Onion Harvester with an Automated Separation System

    • Authors: Michel N. Erokhin, Alexey S. Dorokhov, Alexey V. Sibirev, Alexandr G. Aksenov, Maxim A. Mosyakov, Nikolay V. Sazonov, Maria M. Godyaeva
      First page: 380
      Abstract: One of the most important problems during the implementation of any technology is to reduce labor costs, energy, and resource conservation while increasing the yield of cultivated crops and, as a result, reducing the cost of production. Despite a significant amount of scientific research devoted to the problem of energy and resource conservation in the cultivation and harvesting of agricultural crops and the development of mechanization tools that ensure the high-quality performance of technological operations, there remain issues that have not been fully resolved to date. In addition, not all the results of known theoretical and experimental studies can be directly applied to intensify the process of harvesting root crops since the quality indicators of marketable products depend on the type and technological parameters of the separating working bodies. This article presents the design of a rod elevator with an adjustable angle of inclination of the web, which reduces damage to commercial products of root crops and bulbs with maximum completeness of separation. A laboratory facility has been developed to substantiate the design and technological parameters of a separating system with an adjustable web inclination angle. Based on the results of theoretical and experimental studies, a machine for harvesting onions with an adjustable blade inclination angle has been developed, which provides an increase in the quality indicators of onion harvesting at optimal values of the parameters: (1) translational speed of movement of the rod elevator with an adjustable web inclination angle of 1.7 m/s with a 98.4% completeness of separation and 1.7% damage to the bulbs; (2) translational speed of the movement of the machine for harvesting root crops and onions 1.0 m/s with a 98.5% separation completeness and 1.1% damage to the bulbs; (3) digging depth of the digging plowshare equal to 0.02 m, with an onion heap separation completeness of more than 98% and product damage of less than 1.4%. The results of theoretical and experimental studies of a rod elevator to substantiate the design and technological parameters during its interaction with a heap of onion are presented. Basic design and technological parameters of the studied rod elevator are substantiated, namely, the distance S1 of the movement of the rod of the actuators, the angle a1 of the longitudinal inclination of the surface of the rod elevator relative to the horizon, and differential equations of motion of the onion-sowing pile element on the surface of the rod elevator with an adjustable angle of inclination of the web.
      Citation: AgriEngineering
      PubDate: 2022-04-12
      DOI: 10.3390/agriengineering4020026
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 400-413: Prediction of Potassium in Peach
           Leaves Using Hyperspectral Imaging and Multivariate Analysis

    • Authors: Megan Io Ariadne Abenina, Joe Mari Maja, Matthew Cutulle, Juan Carlos Melgar, Haibo Liu
      First page: 400
      Abstract: Hyperspectral imaging (HSI) is an emerging technology being utilized in agriculture. This system could be used to monitor the overall health of plants or in pest/disease detection. As sensing technology advancement expands, measuring nutrient levels and disease detection also progresses. This study aimed to predict three different levels of potassium (K) concentration in peach leaves using principal component analysis (PCA) and develop models for predicting the K concentration of a peach leaf using a hyperspectral imaging technique. Hyperspectral images were acquired from a randomly selected fresh peach leaf from multiple trees over the spectral region between 500 and 900 nm. Leaves were collected from trees with varying potassium levels of high (2.7~3.2%), medium (2.0~2.6%), and low (1.3~1.9%). Four pretreatment methods (multiplicative scatter effect (MSC), Savitzky–Golay first derivative, Savitzky–Golay second derivative, and standard normal variate (SNV)) were applied to the raw data and partial least square (PLS) was used to develop a model for each of the pretreatments. The R2 values for each pretreatment method were 0.8099, 0.6723, 0.5586, and 0.8446, respectively. The SNV prediction model has the highest accuracy and was used to predict the K nutrient using the validation data. The result showed a slightly lower R2 = 0.8101 compared with the training. This study showed that HSI could measure K concentration in peach tree cultivars.
      Citation: AgriEngineering
      PubDate: 2022-04-21
      DOI: 10.3390/agriengineering4020027
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 414-423: Influence of Seed Quality
           Stimulation in “Khao Dawk Mali 105” Rough Rice during the
           Deterioration Period Using an Automatic Soaking and Germination
           Accelerator Unit and Infrared Radiation Treatment

    • Authors: Chanat Vipattanaporn, Cherdpong Chiawchanwattana, Juckamas Laohavanich, Suphan Yangyuen
      First page: 414
      Abstract: This study aimed to improve the seed quality during the deterioration period of rough rice (Oryza sativa L.), cultivar ‘Khoa Dawk Mali 105’ (KDML 105), using an automatic soaking and germination accelerator unit (ASGA) together with stimulation via infrared radiation treatment (IRT) to stimulate seed quality (germination rate and γ-aminobutyric acid (GABA) content). This study used a general full factorial design, and the independent variables were the storage period (10, 11 and 12 months), methods of germinated rough rice preparation (conventional method (CM) and an automatic soaking and germination accelerator unit (ASGA)), and stimulation with IRT. The initial grain moisture content did not exceed 14% (wet basis (wb)). The germination rate of the rough rice by CM and ASGA with stimulation with IRT was significantly higher than non-stimulated rice, by 6.56 and 8.11%, respectively, in each storage period. The GABA contents of the germinated rough rice using CM and ASGA stimulated with IRT were significantly higher than ungerminated rough rice, by 19.52 and 21.24% (10 months), respectively; 16.36 and 23.58% (11 months), respectively; and 69.88 and 67.69% (12 months), respectively.
      Citation: AgriEngineering
      PubDate: 2022-05-11
      DOI: 10.3390/agriengineering4020028
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 424-460: Disruptive Technologies in Smart
           Farming: An Expanded View with Sentiment Analysis

    • Authors: Sargam Yadav, Abhishek Kaushik, Mahak Sharma, Shubham Sharma
      First page: 424
      Abstract: Smart Farming (SF) is an emerging technology in the current agricultural landscape. The aim of Smart Farming is to provide tools for various agricultural and farming operations to improve yield by reducing cost, waste, and required manpower. SF is a data-driven approach that can mitigate losses that occur due to extreme weather conditions and calamities. The influx of data from various sensors, and the introduction of information communication technologies (ICTs) in the field of farming has accelerated the implementation of disruptive technologies (DTs) such as machine learning and big data. Application of these predictive and innovative tools in agriculture is crucial for handling unprecedented conditions such as climate change and the increasing global population. In this study, we review the recent advancements in the field of Smart Farming, which include novel use cases and projects around the globe. An overview of the challenges associated with the adoption of such technologies in their respective regions is also provided. A brief analysis of the general sentiment towards Smart Farming technologies is also performed by manually annotating YouTube comments and making use of the pattern library. Preliminary findings of our study indicate that, though there are several barriers to the implementation of SF tools, further research and innovation can alleviate such risks and ensure sustainability of the food supply. The exploratory sentiment analysis also suggests that most digital users are not well-informed about such technologies.
      Citation: AgriEngineering
      PubDate: 2022-05-12
      DOI: 10.3390/agriengineering4020029
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 461-474: Wheat Yield Prediction in India
           Using Principal Component Analysis-Multivariate Adaptive Regression
           Splines (PCA-MARS)

    • Authors: B. M. Nayana, Kolla Rohit Kumar, Christophe Chesneau
      First page: 461
      Abstract: Crop yield forecasting is becoming more essential in the current scenario when food security must be assured, despite the problems posed by an increasingly globalized community and other environmental challenges such as climate change and natural disasters. Several factors influence crop yield prediction, which has complex non-linear relationships. Hence, to study these relationships, machine learning methodologies have been increasingly adopted from conventional statistical methods. With wheat being a primary and staple food crop in the Indian community, ensuring the country’s food security is crucial. In this paper, we study the prediction of wheat yield for India overall and the top wheat-producing states with a comparison. To accomplish this, we use Multivariate Adaptive Regression Splines (MARS) after extracting the main features by Principal Component Analysis (PCA) considering the parameters such as area under cultivation and production for the years 1962–2018. The performance is evaluated by error analyses such as RMSE, MAE, and R2. The best-fitted MARS model is chosen using cross-validation and user-defined parameter optimization. We find that the MARS model is well suited to India as a whole and other top wheat-producing states. A comparative result is obtained on yield prediction between India overall and other states, wherein the state of Rajasthan has a better model than other major wheat-producing states. This research will emphasize the importance of improved government decision-making as well as increased knowledge and robust forecasting among Indian farmers in various states.
      Citation: AgriEngineering
      PubDate: 2022-05-17
      DOI: 10.3390/agriengineering4020030
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 475-482: Automated Systems for Estrous and
           Calving Detection in Dairy Cattle

    • Authors: Camila Alves dos Santos, Nailson Martins Dantas Landim, Humberto Xavier de Araújo, Tiago do Prado Paim
      First page: 475
      Abstract: Purpose: The objective of this review is to describe the main technologies (automated activity monitors) available commercially and under research for the detection of estrus and calving alerts in dairy cattle. Sources: The data for the elaboration of the literature review were obtained from searches on the Google Scholar platform. This search was performed using the following keywords: reproduction, dairy cows, estrus detection and parturition, electronic devices. After the search, the articles found with a title related to the objective of the review were read in full. Finally, the specific articles chosen to be reported in the review were selected according to the method of identification of estrus and parturition, seeking to represent the different devices and technologies already studied for both estrus and parturition identification. Synthesis: Precision livestock farming seeks to obtain a variety of information through hardware and software that can be used to improve herd management and optimize animal yield. Visual observation for estrus detection and calving is an activity that requires labor and time, which is an increasingly difficult resource due to several others farm management activities. In this way, automated estrous and calving monitoring devices can increase animal productivity with less labor, when applied correctly. The main devices available currently are based on accelerometers, pedometers and inclinometers that are attached to animals in a wearable way. Some research efforts have been made in image analysis to obtain this information with non-wearable devices. Conclusion and applications: Efficient wearable devices to monitor cows’ behavior and detect estrous and calving are available on the market. There is demand for low cost with easy scalable technology, as the use of computer vision systems with image recording. With technology is possible to have a better reproductive management, and thus increase efficiency.
      Citation: AgriEngineering
      PubDate: 2022-05-23
      DOI: 10.3390/agriengineering4020031
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 483-488: Energy Assessment for First and
           Second Season Conventional and Transgenic Corn

    • Authors: Rodolfo Michelassi Silber, Thiago Libório Romanelli
      First page: 483
      Abstract: The exploitation of natural resources for agriculture is growing to fulfill the demand for food, which requires the rational use of inputs for sustainable production. Brazilian agricultural production stands out on the international scene. For instance, corn is one of the most exported products in Brazil, which is possible through the planting in the second crop season within a year, called the “off-season”. In addition to being a technique that allows soil conservation, it also reduces the use of inputs and soil tillage. The agricultural production systems require a large amount of energy throughout their processes, mainly through inputs and fuels. Energy flows allow for the identification of the efficiency of the production system and, consequently, its sustainability. Indicators regarding net energy gain per area (Energy balance) and energy profitability (Energy Return on Investment) were applied. The first-season system presented higher energy demand when compared to the second-season system, with a difference of 10.24 GJ ha−1 between the conventional ones and 10.47 GJ ha−1 between the transgenic ones. However, the indicators showed higher energy efficiency in the transgenic off-season corn production, in which the return on energy was 55% higher, and the energy incorporation was 35% lower when compared to conventional first-season corn.
      Citation: AgriEngineering
      PubDate: 2022-06-02
      DOI: 10.3390/agriengineering4020032
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 489-506: Evaluation of LiDAR for the Free
           Navigation in Agriculture

    • Authors: Matthias Reger, Jörn Stumpenhausen, Heinz Bernhardt
      First page: 489
      Abstract: Driverless transport systems (DTS) or automated guided vehicles (AGV) have been part of intralogistics for over six decades. The uniform and structured environment conditions in industrial halls provided the ideal conditions for simple automation, such as in goods transport. Initially, implementing simply-designed safety devices, e.g., bumpers, could reduce risk to an acceptable level. However, these conditions are not present in an agricultural environment. Soiling and harsh weather conditions are anticipated both indoors and outdoors. The state of the art in intralogistics are light detection and ranging (LiDAR) scanners, which are suitable for both navigation and collision avoidance, including personal protection. In this study, the outdoor and navigation suitability of LiDAR is assessed in test series. The aim is to contribute advice on validation of LiDAR as a possible technology with respect to navigation and collision avoidance in freely navigating automatic feeding systems.
      Citation: AgriEngineering
      PubDate: 2022-06-09
      DOI: 10.3390/agriengineering4020033
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 507-522: Comparison of Single-Shot and
           Two-Shot Deep Neural Network Models for Whitefly Detection in IoT Web
           Application

    • Authors: Chinmay U. Parab, Canicius Mwitta, Miller Hayes, Jason M. Schmidt, David Riley, Kadeghe Fue, Suchendra Bhandarkar, Glen C. Rains
      First page: 507
      Abstract: In this study, we have compared YOLOv4, a single-shot detector to Faster-RCNN, a two-shot detector to detect and classify whiteflies on yellow-sticky tape (YST). An IoT remote whitefly monitoring station was developed and placed in a whitefly rearing room. Images of whiteflies attracted to the trap were recorded 2× per day. A total of 120 whitefly images were labeled using labeling software and split into a training and testing dataset, and 18 additional yellow-stick tape images were labeled with false positives to increase the model accuracy from remote whitefly monitors in the field that created false positives due to water beads and reflective light on the tape after rain. The two-shot detection model has two stages: region proposal and then classification of those regions and refinement of the location prediction. Single-shot detection skips the region proposal stage and yields final localization and content prediction at once. Because of this difference, YOLOv4 is faster but less accurate than Faster-RCNN. From the results of our study, it is clear that Faster-RCNN (precision—95.08%, F-1 Score—0.96, recall—98.69%) achieved a higher level of performance than YOLOv4 (precision—71.77%, F-1 score—0.83, recall—73.31%), and will be adopted for further development of the monitoring station.
      Citation: AgriEngineering
      PubDate: 2022-06-10
      DOI: 10.3390/agriengineering4020034
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 523-532: Comparison of Navel Orangeworm
           Adults Detected with Optical Sensors and Captured with Conventional Sticky
           Traps

    • Authors: Charles S. Burks
      First page: 523
      Abstract: Attractants used with sticky traps for monitoring navel orangeworm include artificial pheromone lures, ovipositional bait (ovibait) bags, and phenyl propionate; however, the sticky traps have the limitations of potentially becoming ineffective because of full or dirty glue surfaces and of having access to data dependent on increasingly expensive labor. A study comparing detection with a commercially available pseudo-acoustic optical sensor (hereafter, sensor) connected to a server through a cellular gateway found similar naval orangeworm activity profiles between the sensor and pheromone traps, and the timestamps of events in the sensors was consistent with the behavior of navel orangeworm males orienting to pheromone. Sensors used with ovibait detected navel orangeworm activity when no navel orangeworm were captured in sticky traps with ovibait, and the timestamps for this activity were inconsistent with oviposition times for navel orangeworm in previous studies. When phenyl propionate was the attractant, sensors and sticky traps were more highly correlated than for pheromone traps on a micro-level (individual replicates and monitoring intervals), but there was high variation and week-to-week profiles differed. These results indicate that these sensors represent a promising alternative to sticky traps for use with pheromone as an attractant, but more research is needed to develop the use of sensors with other attractants. These results will guide developers and industry in transfer of this promising technology.
      Citation: AgriEngineering
      PubDate: 2022-06-14
      DOI: 10.3390/agriengineering4020035
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 533-543: Influence of Soil Wetting and
           Drying Cycles on Soil Detachment

    • Authors: Jian Wang, Dexter B. Watts, Qinqian Meng, Fan Ma, Qingfeng Zhang, Penghui Zhang, Thomas R. Way
      First page: 533
      Abstract: Agricultural soils undergo periods of saturation followed by desiccation throughout the course of a growing season. It is believed that these periods of wetting and drying influence soil structure and may affect the rate of soil detachment. Thus, an experiment was conducted to investigate the influence of a disturbed soil (soil sieved to simulate tillage) subjected to various wetting and drying cycles, on soil bulk density and the resistance to soil detachment with runoff. Seven treatments consisting of wetting and drying cycles ranging from 0 to 6 cycles were evaluated under laboratory conditions using an experimental flume apparatus. A Richards growth model proposed for predicting the influence of wetting and drying on soil detachment was also evaluated. Results showed that the soil bulk density increased as the number of wetting and drying cycles increased. The soil detachment rate decreased as the number of wetting and drying cycles increased. Moreover, initial soil detachment (occurring as soon as runoff began) rates were high for 1 to 3 wetting and drying cycles, while the rate of initial detachment decreased after the third cycle. For example, soils with two and three wetting and drying cycles took 6.5 and 7 min to reach the maximum 1 cm souring depth, respectively, while the soils subjected to four or more wetting and drying cycles did not reach the maximum 1 cm depth during the 15 min runoff experiment. In addition, the proposed S-Shaped Richards growth model was a good predictor for estimating the soil detachment of soils experiencing various wetting and drying cycles. Findings from this study suggest that more attention should be given to the influence that soil wetting and drying have on the prediction of soil detachment. Information from this study is expected to be useful for improving soil management strategies for reducing soil erosion.
      Citation: AgriEngineering
      PubDate: 2022-06-16
      DOI: 10.3390/agriengineering4020036
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 544-565: Central Control for Optimized
           Herbaceous Feedstock Delivery to a Biorefinery from Satellite Storage
           Locations

    • Authors: Jonathan P. Resop, John S. Cundiff, Robert D. Grisso
      First page: 544
      Abstract: The delivery of herbaceous feedstock from satellite storage locations (SSLs) to a biorefinery or preprocessing depot is a logistics problem that must be optimized before a new bioenergy industry can be realized. Both load-out productivity, defined as the loading of 5 × 4 round bales into a 20-bale rack at the SSL, and truck productivity, defined as the hauling of bales from the SSLs to the biorefinery, must be maximized. Productivity (Mg/d) is maximized and cost (USD/Mg) is minimized when approximately the same number the loads is received each day. To achieve this, a central control model is proposed, where a feedstock manager at the biorefinery can dispatch a truck to any SSL where a load will be available when the truck arrives. Simulations of this central control model for different numbers of simultaneous load-out operations were performed using a database of potential production fields within a 50 km radius of a theoretical biorefinery in Gretna, VA. The minimum delivered cost (i.e., load-out plus truck) was achieved with nine load-outs and a fleet of eight trucks. The estimated cost was 11.24 and 11.62 USD/Mg of annual biorefinery capacity (assuming 24/7 operation over 48 wk/y for a total of approximately 150,000 Mg/y) for the load-out and truck, respectively. The two costs were approximately equal, reinforcing the desirability of a central control to maximize the productivity of these two key operations simultaneously.
      Citation: AgriEngineering
      PubDate: 2022-06-17
      DOI: 10.3390/agriengineering4020037
      Issue No: Vol. 4, No. 2 (2022)
       
  • AgriEngineering, Vol. 4, Pages 1-16: Innovative Vibrating Hydraulic Dredge
           for Striped Venus (Chamelea gallina) Fishing

    • Authors: Giuseppina Mascilongo, Corrado Costa, Damianos Chatzievangelou, Daniele Pochi, Roberto Fanigliulo, Federica Di Giacinto, Ludovica Di Renzo, Carla Giansante, Nicola Ferri, Nicola D'Alterio, Claudio Costa, Marco L. Bianchini
      First page: 1
      Abstract: This work proposes the experimentation of an innovative hydraulic dredge for clam fishing (Chamelea gallina) in the Adriatic Sea (Italy). This innovative gear aimed at increasing the selectivity of the typical hydraulic dredge used currently, while at the same reducing the impact on benthos through the conception, installation, and experimentation of innovative technological solutions, consisting mainly of a vibrating bottom panel on the dredge and a “warning device” on the dredge mouth. Comparative experiments of the traditional vs. the modified gear, employing two boats fishing in parallel on the northern coast of Abruzzi (Adriatic Sea) and contrasting the catch with both paired comparisons and through modelling, showed that the innovative hydraulic dredge retains fewer undersize clams while yielding similar amounts of commercial product, moreover of higher quality; at the same time, it takes on board less discard, and catches significantly less vagile fauna. In short, the innovative gear is gaining five times over a list of six parameters considered as positive and/or advantageous for the clam fishery. The results allow proposals of potential improvements to clam-fishing instruments to make the selection processes more effective while promoting a lower impacting fishery, which is essential for clam management.
      Citation: AgriEngineering
      PubDate: 2022-01-06
      DOI: 10.3390/agriengineering4010001
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 17-31: Performance Assessment of Farm
           Machinery for Persimmon Fruit Cultivation in a Japanese Mountainous Area

    • Authors: Atsushi Yamamoto, Tsumugu Kusudo, Masaomi Kimura, Yutaka Matsuno
      First page: 17
      Abstract: Japanese agriculture is facing a decrease in agricultural workers. Mechanization, both to save time and reduce physical input, is essential to solving this issue. Recent worldwide progress in Internet-of-things technology has enabled the application of remote-controlled and unmanned machinery in agriculture. This study was conducted in the Gojo-Yoshino mountainous region in Nara, Japan, which is famous for its persimmon cultivation. The performance of newly introduced smart agricultural machinery was studied in the field by simulating cultivation work. The results showed that the remote-control weeder, speed sprayer, and remote-control mini crawler carrier saved 90%, 75%, and 5% of weeding, spraying, and harvesting times, respectively, when compared with conventional methods. Such time savings led to an 8% decrease in the total working time spent on persimmon cultivation. In addition, using the speed sprayer showed improvement in the fruit’s quality. Results of the power assist suits did not show a time-saving effect but showed a reduction of physical burden. These results suggest that the mechanization of persimmon cultivation is efficient and labor-saving, and satisfies the need for farmers. However, the high investment costs remain an issue in extending mechanization to the region.
      Citation: AgriEngineering
      PubDate: 2022-01-13
      DOI: 10.3390/agriengineering4010002
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 32-47: Automatic Classification of the
           Ripeness Stage of Mango Fruit Using a Machine Learning Approach

    • Authors: Denchai Worasawate, Panarit Sakunasinha, Surasak Chiangga
      First page: 32
      Abstract: Most mango farms classify the maturity stage manually by trained workers using external indicators such as size, shape, and skin color, which can lead to human error or inconsistencies. We developed four common machine learning (ML) classifiers, the k-mean, naïve Bayes, support vector machine, and feed-forward artificial neural network (FANN), all of which were aimed at classifying the ripeness stage of mangoes at harvest. The ML classifiers were trained on biochemical data and then tested on physical and electrical data.The performance of the ML models was compared using fourfold cross validation. The FANN classifier performed the best, with a mean accuracy of 89.6% for unripe, ripe, and overripe classes, when compared to the other classifiers.
      Citation: AgriEngineering
      PubDate: 2022-01-13
      DOI: 10.3390/agriengineering4010003
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 48-66: Research on Biomechanical Properties
           of Laver (Porphyra yezoensis Ueda) for Mechanical Harvesting and
           Postharvest Transportation

    • Authors: Wei Lu, Xiuchen Li, Guochen Zhang, Jiahong Tang, Shang Ni, Hanbing Zhang, Qian Zhang, Yilin Zhai, Gang Mu
      First page: 48
      Abstract: This paper investigates the effect of origin, harvest times and loading rates on the biomechanical properties of laver, aiming to develop laver harvesting and postharvest transportation equipment. The values and changing regular of biomechanical properties were obtained via a combination of morphological and mechanical tests as well as numerical statistics. The correlation between biological and mechanical properties was detected simultaneously. The results show that the biological properties are affected dramatically by origin and harvest times. The values of length, width, thickness and mass of laver from Dalian exceeded those found in Qingdao and Lianyungang. The width, thickness and mass increased, whereas the length-to-width ratio decreased with the increasing harvest time. Meanwhile, the mechanical properties are also influenced significantly by loading rates, origin and harvest times. Tensile and shear strength displayed an overall decreasing trend, whereas adhesive force and adhesiveness in general increased with the increasing loading rate. The tensile and shear strengths were greatest for laver from Qingdao, while the adhesive force and adhesiveness were greatest for laver from Dalian. Tensile strength, adhesive force and adhesiveness increased, and shear strength decreased with the delay of harvest time. In addition, the tensile strength and thickness of the laver at different harvest times were positively correlated. The maximum tensile strength, shear strength, adhesive force and adhesiveness were 3.56 MPa, 4.79 MPa, 0.32 N and 1.01 N·mm, respectively. These results are believed to be able to provide a reference for the design and optimization of machineries such as harvest, postharvest transportation and laver processing.
      Citation: AgriEngineering
      PubDate: 2022-01-20
      DOI: 10.3390/agriengineering4010004
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 67-69: Acknowledgment to Reviewers of
           AgriEngineering in 2021

    • Authors: AgriEngineering Editorial Office AgriEngineering Editorial Office
      First page: 67
      Abstract: Rigorous peer-reviews are the basis of high-quality academic publishing [...]
      Citation: AgriEngineering
      PubDate: 2022-01-30
      DOI: 10.3390/agriengineering4010005
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 70-103: Precision Irrigation Management
           Using Machine Learning and Digital Farming Solutions

    • Authors: Emmanuel Abiodun Abioye, Oliver Hensel, Travis J. Esau, Olakunle Elijah, Mohamad Shukri Zainal Abidin, Ajibade Sylvester Ayobami, Omosun Yerima, Abozar Nasirahmadi
      First page: 70
      Abstract: Freshwater is essential for irrigation and the supply of nutrients for plant growth, in order to compensate for the inadequacies of rainfall. Agricultural activities utilize around 70% of the available freshwater. This underscores the importance of responsible management, using smart agricultural water technologies. The focus of this paper is to investigate research regarding the integration of different machine learning models that can provide optimal irrigation decision management. This article reviews the research trend and applicability of machine learning techniques, as well as the deployment of developed machine learning models for use by farmers toward sustainable irrigation management. It further discusses how digital farming solutions, such as mobile and web frameworks, can enable the management of smart irrigation processes, with the aim of reducing the stress faced by farmers and researchers due to the opportunity for remote monitoring and control. The challenges, as well as the future direction of research, are also discussed.
      Citation: AgriEngineering
      PubDate: 2022-02-01
      DOI: 10.3390/agriengineering4010006
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 104-121: The Effect of Climatic Parameters
           on Strawberry Production in a Small Walk-In Greenhouse

    • Authors: Napassawan Khammayom, Naoki Maruyama, Chatchawan Chaichana
      First page: 104
      Abstract: The purpose of this study was to evaluate the impact of different environmental factors such as temperature, solar radiation, and relative humidity on the quality of strawberries in terms of their shape, size, and sugar accumulation. The experiment was carried out in a small walk-in greenhouse in Matsusaka city, Japan. Harunoka strawberries (Fragaria × ananassa Duch.) were cultivated from September to May of the following year. Production was evaluated on 20 February 2021 (peak season) and 5 April 2021 (end season). To evaluate the influence of environmental factors on strawberry fruit quality, the weight, shape, and soluble sugar content were recorded and compared to each other. According to the environmental data, the average temperature between day and night at peak harvest was around 12 °C, which was suitable for high-quality strawberry cultivation. However, the average temperature difference between day and night was approximately 4 °C at the end of the season. In addition, there were no significant differences in solar radiation and relative humidity between both seasons. Increasing temperatures led to the decline in the soluble sugar content at the end season. Thus, it can be concluded that the temperature difference between day and night is a major factor affecting strawberry production. The assessment of the impact of environmental conditions on strawberry quality can be used as a guideline not only in temperate climates, but also in other climates, such as in tropical countries.
      Citation: AgriEngineering
      PubDate: 2022-02-03
      DOI: 10.3390/agriengineering4010007
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 122-133: Potential of Grid-Connected
           Photovoltaic Systems in Brazilian Dairy Farms

    • Authors: Antonio José Steidle Neto, Daniela de Carvalho Lopes, Sheila Tavares Nascimento
      First page: 122
      Abstract: The insufficient supply of electrical energy, in addition to frequent disturbances and interruptions, has motivated the inclusion of solar, biogas, biomass or wind energy systems in many Brazilian farms. However, there are few studies that have addressed the technical and economic impacts of renewable sources for generating electricity in rural applications, leading farmers not to invest in these technologies for fear of financial losses. This study was carried out to evaluate the potential of grid-connected photovoltaic systems for supplying the electricity demand in dairy farms located at Minas Gerais State, Brazil. The electricity generated by grid-connected photovoltaic systems was estimated from global solar radiation measurements, considering six municipalities of Minas Gerais State, Brazil. Electricity consumption was monitored monthly during one year in 12 farms. The average percentages of electricity consumption in the main operations executed at farms were 4, 27, 12, 33 and 24% for lighting, milking, cleaning/disinfection (water heating and pumping), milk cooling/refrigeration and miscellaneous, respectively. The monthly differences between the electricity generation and consumption for the studied municipalities demonstrated the technical feasibility of grid-connected systems installed directly in the dairy farms, helping to achieve energy sustainability.
      Citation: AgriEngineering
      PubDate: 2022-02-03
      DOI: 10.3390/agriengineering4010008
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 134-140: Experimental Investigation of
           Methane Generation in the Presence of Surface and Un-Surface Nanoparticles
           of Iron Oxide

    • Authors: Asim Ali, Hareef Ahmed Keerio, Sallahuddin Panhwar, Muhammad Zeshan Ahad
      First page: 134
      Abstract: The exploitation and harnessing of renewable energies are becoming increasingly important throughout the world. This study presents a method of methane (CH4) generation using biological disintegration of food waste (FW) by anaerobic digestion (AD). The CH4 production was enhanced by the addition of three different types of iron oxide (Fe3O4) nanoparticles (NPs) (Cetyletrimethlebromide (CTAB), urea-capped Fe3O4 NPs and Fe3O4 NPs without capping). The bio generation of CH4 and biodegradation of volatile solids (VS) were carried out in an AD treatment at mesophilic conditions (35–37 °C) for more than 50 days in batch mode. The concentration of all three types of NPs was kept constant at 75 mg/L. It was noticed that urea-capped NPs produced the maximum CH4 (5.386 L), followed by Fe3O4 NPs (5.212 L). Methane production in the control bioreactor was 2.143 L. The experimental results of CH4 generation (a dependent variable) were analyzed against the concentrations of NPs used (as independent variables) in multiple regression analysis (MRA). The overall model for the experiments resulted in R2 and R-adjusted values of 0.995 and 0.993, respectively.
      Citation: AgriEngineering
      PubDate: 2022-02-08
      DOI: 10.3390/agriengineering4010009
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 141-155: Detecting Crown Rot Disease in
           Wheat in Controlled Environment Conditions Using Digital Color Imaging and
           Machine Learning

    • Authors: Yiting Xie, Darren Plett, Huajian Liu
      First page: 141
      Abstract: Crown rot is one of the major stubble soil fungal diseases that bring significant yield loss to the cereal industry. The most effective crown rot management approach is removal of infected crop residue from fields and rotation of nonhost crops. However, disease screening is challenging as there are no clear visible symptoms on upper stems and leaves at early growth stages. The current manual screening method requires experts to observe the crown and roots of plants to detect disease, which is time-consuming, subjective, labor-intensive, and costly. As digital color imaging has the advantages of low cost and easy use, it has a high potential to be an economical solution for crown rot detection. In this research, a crown rot disease detection method was developed using a smartphone camera and machine learning technologies. Four common wheat varieties were grown in greenhouse conditions with a controlled environment, and all infected group plants were infected with crown rot without the presence of other plant diseases. We used a smartphone to take digital color images of the lower stems of plants. Using imaging processing techniques and a support vector machine algorithm, we successfully distinguished infected and healthy plants as early as 14 days after disease infection. The results provide a vital first step toward developing a digital color imaging phenotyping platform for crown rot detection to enable the management of crown rot disease effectively. As an easy-access phenotyping method, this method could provide support for researchers to develop an efficiency and economic disease screening method in field conditions.
      Citation: AgriEngineering
      PubDate: 2022-02-09
      DOI: 10.3390/agriengineering4010010
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 156-170: Assessment of a Deep Burial
           Destoning System of Agrarian Soils Alternative to the Stone Removal and
           On-Site Crushing

    • Authors: Pietro Toscano, Maurizio Cutini, Giovanni Cabassi, Nicolò Pricca, Elio Romano, Carlo Bisaglia
      First page: 156
      Abstract: Among its many functions, soil represents the active natural medium for plant growth. Different soils have various structural characteristics, that correspond to their qualitative parameters in terms of physical, chemical, and biological fertility. Because of their extremely slow formation processes, soils are also a non-renewable resource, easily subject to degradative processes. Among their mineral constituents many agrarian soils present, in addition to the fine earth, variable percentages of coarse fractions in their arable layer, which interfere with the crop growth, requiring more energy to manage cultivation operations, and damaging the machinery up to making its use impractical. In these conditions, it becomes necessary to proceed with the soil destoning, particularly for the management of Precision Farming techniques. Depending on the percentages, sizes and types of coarse fractions, the soil destoning systems concern: (i) the collection and removal of stones from the field, (ii) the on-site stones crushing, and (iii) the stone burial. In this article, we report the first evaluation of a deep burial destoning system carried out in the CREA Experimental Center of Treviglio (Italy). With the described reclamation system, a significant long-term improvement of soil quality in a 600 mm thick arable layer was achieved; avoiding the shortcomings of the destoning systems as commonly applied in agricultural lands.
      Citation: AgriEngineering
      PubDate: 2022-02-14
      DOI: 10.3390/agriengineering4010011
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 171-178: Reduction in Blockage Property of
           UV-Blocking Greenhouse Covering Material: In Situ and Lab Measurement
           Comparison

    • Authors: Chryssoula Papaioannou, Nikolaos Katsoulas, Evangelini Kitta
      First page: 171
      Abstract: The goal of this research was to compare and evaluate the measurements taken by different instruments regarding alterations while varying the ultraviolet (UV)-blocking property of cladding material during its usage under real greenhouse conditions. The UV-blocking covering material, low-density polyethylene (LDPE), is enriched with additives that are scattered in several layers during the manufacturing process, resulting in the reinforcement of its properties mechanically as well as optically. The duration of this study was three years, and the instruments used were: (a) sensors measuring the UV radiation reaching the earth’s surface in its A and B components; and (b) a portable spectroradiometer capable of measuring the transmissivity of a material, only in the UV-A region. Three covering materials were used with different UV radiation transmissivity. The transmittance was measured both in the laboratory (on samples taken from the roof) and in the field (where the greenhouses were located). Equations were defined to describe the variation in UV radiation transmission increase rate as a function of field exposure time. Lastly, it is important to note that the specific UV radiation sensors were extremely accurate.
      Citation: AgriEngineering
      PubDate: 2022-02-21
      DOI: 10.3390/agriengineering4010012
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 179-189: Distribution of Airflow and Media
           Moisture Content across Two Vertical Bed Biofilters

    • Authors: Augustina Osabutey, Brady Cromer, Alexander Davids, Logan Prouty, Noor Haleem, Robert Thaler, Richard Nicolai, Xufei Yang
      First page: 179
      Abstract: For its small square footage, a vertical bed biofilter was developed for odor emission mitigation for livestock facilities with limited area available for biofilter installation. However, a concern about the design is that airflow and moisture may be poorly distributed across the biofilter due to the effects of gravity. Relevant data are sporadic in the literature. To fill the knowledge gap, two vertical bed biofilters were constructed at a university swine facility and monitored for two months. The monitoring was taken at 27 grid points on each biofilter per field visit. Results revealed that both the airflow and medium moisture content were unevenly distributed. The sun-facing side of the biofilters had significantly lower medium moisture content (p < 0.01) due to solar-induced water evaporation. The side directly facing the barn exhaust had the highest airflow. Airflows varied along the height of the biofilters, but no significant difference was noted. The uniformity of airflow and moisture content, characterized by coefficient of variance (CV) and distribution uniformity (DU) respectively, were examined over the monitoring campaign. Possible reasons for uneven distribution were explored and recommendations are made to address the uniformity issue. The findings from the study are expected to further the development and implementation of biofiltration technology for livestock odor control.
      Citation: AgriEngineering
      PubDate: 2022-02-24
      DOI: 10.3390/agriengineering4010013
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 190-206: Improvement of the Performance of
           an Earth to Air Heat Exchanger for Greenhouse Cooling by the Incorporation
           of Water Finned Tubes—A Theoretical Approach

    • Authors: Vasileios K. Firfiris, Sotirios D. Kalamaras, Anastasia G. Martzopoulou, Vassilios P. Fragos, Thomas A. Kotsopoulos
      First page: 190
      Abstract: Proper climatic conditions in greenhouses are one of the major parameters to ensure optimum crop development. The installation of heating and cooling systems are the common solution to form a proper microclimate inside the greenhouse. However, the operation of these systems is accompanied by energy consumption. Therefore, many methods and alternative systems are sought to encounter this issue. A system which has been examined as an alternative solution for full or partial cover of a greenhouse is the Earth to Air Heat Exchanger (EAHE). Up to now, many research works have concentrated on the investigation and operation of such systems. In this study, a method to enhance the efficiency of the EAHE is examined based on the simultaneous flow of water (Water assisted earth to air heat exchanger—WAEAHE) following the concept of a double pipe heat exchanger which has been widely used in other applications. Furthermore, the improvement of the systems’ efficiency is investigated via the application of fins on the internal pipe of the heat exchanger. For the purpose of the study, different case studies have been investigated in order to reach safe results conserving the parameters affecting its efficiency. The results of the theoretical analysis have shown that the application of an internal water pipe can increase the system’s efficiency sufficiently, while it is further increased with the application of fins. In fact, the application of fins can lead to an increase of the overall heat transfer coefficients varying from 36–68%. In the current study, only the energy efficiency of the system was estimated. This system needs to be further investigated to be technically and financially efficient and applicable in actual case studies.
      Citation: AgriEngineering
      PubDate: 2022-02-24
      DOI: 10.3390/agriengineering4010014
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 207-215: Estimate and Temporal Monitoring
           of Height and Diameter of the Canopy of Recently Transplanted Coffee by a
           Remotely Piloted Aircraft System

    • Authors: Nicole Lopes Bento, Gabriel Araújo e Silva Ferraz, Rafael Alexandre Pena Barata, Daniel Veiga Soares, Lucas Santos Santana, Brenon Diennevan Souza Barbosa
      First page: 207
      Abstract: Digital agriculture is fundamental to potential improvements in the field by optimizing processes and providing intelligent decision making. This study aims to calculate the height and canopy diameter of recently transplanted coffee plants over three periods of crop development using aerial images, verify statistical differences between field measurements and aerial images, estimate linear equations between field data and aerial images, and monitor the temporal profile of the growth and development of the cultivar understudy in the field based on information extracted from aerial images through a Remotely Piloted Aircraft System (RPAS). The study area comprises a recently transplanted five-month-old Coffea arabica L. cultivar IAC J10 with information of height and crown diameter collected in the field and aerial images obtained by RPAS. As a result, it was possible to calculate the height and diameter of the canopy of coffee plants by aerial images obtained by RPAS. The linear estimation equation for height and crown diameter was determined with satisfactory results by coefficients R and R2 and performance metrics MAE, RMSE, and regression residuals, and it was possible to monitor the temporal profile of the height of the coffee cultivar in the field based on aerial images.
      Citation: AgriEngineering
      PubDate: 2022-02-24
      DOI: 10.3390/agriengineering4010015
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 216-230: Turbulence Models Studying the
           Airflow around a Greenhouse Based in a Wind Tunnel and Under Different
           Conditions

    • Authors: Georgios Partheniotis, Sotirios D. Kalamaras, Anastasia G. Martzopoulou, Vasileios K. Firfiris, Vassilios P. Fragos
      First page: 216
      Abstract: Turbulence phenomena created around a greenhouse due to different wind loads are key factors in its structural design and significantly affect the ventilation rates through its side and roof openings. Using the turbulence models of ANSYS FLUENT software to investigate the airflow around an arched-roof-greenhouse-shaped obstacle placed inside a wind tunnel was the aim of this study. Velocity and pressure areas around the obstacle were examined by selecting three different turbulence models (Standard, RNG and Realizable k–ε models) under three different airflow entry velocities (0.34, 1.00 and 10.00 m s−1) in the wind tunnel. All k–ε models showed that when the air velocity was intensified, the airflow was identified as turbulent. The horizontal velocity profile predicted more accurately the presence of vortices in contrast with the vector sum of the perpendicular velocity components. Vortices were formed upstream, above the roof and downstream of the obstacle, and the applied models showed that when airflow velocity increases, the size of the upstream vortex decreases. Finally, there was a strong indication from the modeling results that the vortex on the roof of the obstacle was an extension of the vortex that was created downstream.
      Citation: AgriEngineering
      PubDate: 2022-02-25
      DOI: 10.3390/agriengineering4010016
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 231-254: An Improved Method of an Image
           Mosaic of a Tea Garden and Tea Tree Target Extraction

    • Authors: Jinzhu Lu, Yishan Xu, Zongmei Gao
      First page: 231
      Abstract: UAV may be limited by its flight height and camera resolution when aerial photography of a tea garden is carried out. The images of the tea garden contain trees and weeds whose vegetation information is similar to tea tree, which will affect tea tree extraction for further agricultural analysis. In order to obtain a high-definition large field-of-view tea garden image that contains tea tree targets, this paper (1) searches for the suture line based on the graph cut method in the image stitching technology; (2) improves the energy function to realize the image stitching of the tea garden; and (3) builds a feature vector to accurately extract tea tree vegetation information and remove unnecessary variables, such as trees and weeds. By comparing this with the manual extraction, the algorithm in this paper can effectively distinguish and eliminate most of the interference information. The IOU in a single mosaic image was more than 80% and the omissions account was 10%. The extraction results in accuracies that range from 84.91% to 93.82% at the different height levels (30 m, 60 m and 100 m height) of single images. Tea tree extraction accuracy rates in the mosaic images are 84.96% at a height of 30 m, and 79.94% at a height of 60 m.
      Citation: AgriEngineering
      PubDate: 2022-02-25
      DOI: 10.3390/agriengineering4010017
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 255-278: A Case Study for Decentralized
           Heat Storage Solutions in the Agroindustry Sector Using Phase Change
           Materials

    • Authors: Carlos Simão, João Murta-Pina, João Pedro Oliveira, Luís Coelho, João Pássaro, Diogo Ferreira, Fernando Reboredo, Tiago Jorge, Pedro Figueiredo
      First page: 255
      Abstract: The development of thermal energy storage solutions (TES) in agroindustry allows reduction of production costs and improvement of operation sustainability. Such solutions require high storage capacity and the ability to adapt to existing equipment. The use of phase change materials (PCMs), which are able to store thermal energy as latent heat, creates new opportunities for heat storage solutions (LHS, latent heat storage) with higher energy density and improved performance when compared to sensible heat storage. New architectures are envisaged where heat storage is distributed throughout the production chain, creating prospects for the integration of renewable generation and recovery of industrial heat waste. This work aims to investigate the benefits of decentralized thermal storage architecture, directly incorporating PCM into the existing equipment of an agroindustry production line. To assess the feasibility and potential gain in the adoption of this TES/LHS distributed solution, a tempering and mixing equipment for food granules is selected as a case study, representing a larger cluster operating under the operation paradigm of water jacket heating. The behavior of the equipment, incorporating an inorganic PCM, is modeled and analyzed in the ANSYS Fluent software. Subsequently, a prototype is instrumented and used in laboratory tests, allowing for data collection and validation of the simulation model. This case study presents a demonstration of the increase in storage capacity and the extension of the discharge process when compared to a conventional solution that uses water for sensible heat storage.
      Citation: AgriEngineering
      PubDate: 2022-02-28
      DOI: 10.3390/agriengineering4010018
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 279-291: Oil Palm Yield Estimation Based on
           Vegetation and Humidity Indices Generated from Satellite Images and
           Machine Learning Techniques

    • Authors: Fernando Watson-Hernández, Natalia Gómez-Calderón, Rouverson Pereira da Silva
      First page: 279
      Abstract: Palm oil has become one of the most consumed vegetable oils in the world, and it is a key element in profitable global value chains. In Costa Rica, oil palm cultivation is one of the three crops with the largest occupied agricultural area. The objective of this study was to explain and predict yield in safe time lags for production management by using free-access satellite images. To this end, machine learning methods were performed to a 20-year data set of an oil palm plantation located in the Central Pacific Region of Costa Rica and the corresponding vegetation indices obtained from LANDSAT satellite images. Since the best correlations corresponded to a one-year time lag, the predictive models Random Forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), Extreme Gradient Boosting (XGBoost), Recursive Partitioning and Regression Trees (RPART), and Neural Network (NN) were built for a Time-lag 1. These models were applied to all genetic material and to the predominant variety (AVROS) separately. While NN showed the best performance for multispecies information (r2 = 0.8139, NSE = 0.8131, RMSE = 0.3437, MAE = 0.2605), RF showed a better fit for AVROS (r2 = 0.8214, NSE = 0.8020, RMSE = 0.3452, MAE = 0.2669). The most relevant vegetation indices (NDMI, MSI) are related to water in the plant. The study also determined that data distribution must be considered for the prediction and evaluation of the oil palm yield in the area under study. The estimation methods of this study provide information on the identification of important variables (NDMI) to characterize palm oil yield. Additionally, it generates a scenario with acceptable uncertainties on the yield forecast one year in advance. This information is of direct interest to the oil palm industry.
      Citation: AgriEngineering
      PubDate: 2022-03-03
      DOI: 10.3390/agriengineering4010019
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 292-310: Sensing Technologies for Measuring
           Grain Loss during Harvest in Paddy Field: A Review

    • Authors: Muhammad Isa Bomoi, Nazmi Mat Nawi, Samsuzana Abd Aziz, Muhamad Saufi Mohd Kassim
      First page: 292
      Abstract: A combine harvester has been widely employed for harvesting paddy in Malaysia. However, it is one of the most challenging machines to operate when harvesting grain crops. Improper handling of a combine harvester can lead to a significant amount of grain loss. Any losses during the harvesting process would result in less income for the farmers. Grain loss sensing technology is automated, remote, and prospective. It can help reduce grain losses by increasing harvesting precision, reliability, and productivity. Monitoring and generating real-time sensor data can provide effective combine harvester performance and information that will aid in analyzing and optimizing the harvesting process. Thus, this paper presents an overview of the conventional methods of grain loss measurements, the factors that contribute to grain losses, and further reviews the development and operation of sensor components for monitoring grain loss during harvest. The potential and limitations of the present grain loss monitoring systems used in combine harvesting operations are also critically analyzed. Several strategies for the adoption of the technology in Malaysia are also highlighted. The use of this technology in future harvesting methods is promising as it could lead to an increase in production, yield, and self-sufficiency to meet the increasing demand for food globally.
      Citation: AgriEngineering
      PubDate: 2022-03-09
      DOI: 10.3390/agriengineering4010020
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 311-319: Vegetation Indices Applied to
           Suborbital Multispectral Images of Healthy Coffee and Coffee Infested with
           Coffee Leaf Miner

    • Authors: Luana Mendes dos Santos, Gabriel Araújo e Silva Ferraz, Diego Bedin Marin, Milene Alves de Figueiredo Carvalho, Jessica Ellen Lima Dias, Ademilson de Oliveira Alecrim, Mirian de Lourdes Oliveira e Silva
      First page: 311
      Abstract: The coffee leaf miner (Leucoptera coffeella) is a primary pest for coffee plants. The attack of this pest reduces the photosynthetic area of the leaves due to necrosis, causing premature leaf falling, decreasing the yield and the lifespan of the plant. Therefore, this study aims to analyze vegetation indices (VI) from images of healthy coffee leaves and those infested by coffee leaf miner, obtained using a multispectral camera, mainly to differentiate and detect infested areas. The study was conducted in two distinct locations: At a farm, where the camera was coupled to a remotely piloted aircraft (RPA) flying at a 3 m altitude from the soil surface; and the second location, in a greenhouse, where the images were obtained manually at a 0.5 m altitude from the support of the plant vessels, in which only healthy plants were located. For the image processing, arithmetic operations with the spectral bands were calculated using the “Raster Calculator” obtaining the indices NormNIR, Normalized Difference Vegetation Index (NDVI), Green-Red NDVI (GRNDVI), and Green NDVI (GNDVI), the values of which on average for healthy leaves were: 0.66; 0.64; 0.32, and 0.55 and for infested leaves: 0.53; 0.41; 0.06, and 0.37 respectively. The analysis concluded that healthy leaves presented higher values of VIs when compared to infested leaves. The index GRNDVI was the one that better differentiated infested leaves from the healthy ones.
      Citation: AgriEngineering
      PubDate: 2022-03-17
      DOI: 10.3390/agriengineering4010021
      Issue No: Vol. 4, No. 1 (2022)
       
  • AgriEngineering, Vol. 4, Pages 320-334: Development of an Automated Linear
           Move Fertigation System for Cotton Using Active Remote Sensing

    • Authors: Stewart Bell, A. Bulent Koc, Joe Mari Maja, Jose Payero, Ahmad Khalilian, Michael Marshall
      First page: 320
      Abstract: Optimum nitrogen (N) application is essential to the economic and environmental sustainability of cotton production. Variable-rate N fertigation could potentially help farmers optimize N applications, but current overhead irrigation systems normally lack automated site-specific variable-rate fertigation capabilities. The objective of this study was to develop an automated variable-rate N fertigation based on real-time Normalized Difference Vegetation Index (NDVI) measurements from crop sensors integrated with a lateral move irrigation system. For this purpose, NDVI crop sensors and a flow meter integrated with Arduino microcontrollers were constructed on a linear move fertigation system at the Edisto Research and Education Center in Blackville, South Carolina. A computer program was developed to automatically apply site-specific variable N rates based on real-time NDVI sensor data. The system’s ability to use the NDVI data to prescribe N rates, the flow meter to monitor the flow of N, and a rotary encoder to establish the lateral’s position were evaluated. Results from this study showed that the system could accurately use NDVI data to calculate N rates when compared to hand calculated N rates using a two-sample t-test (p > 0.05). Linear regression analysis showed a strong relationship between flow rates measured using the flow meter and hand calculations (R2 = 0.95), as well as the measured distance travelled using the encoder and the actual distance travelled (R2 = 0.99). This study concludes that N management decisions can be automated using NDVI data from on-the-go handheld GreenSeeker crop sensors. The developed system can provide an alternative N application solution for farmers and researchers.
      Citation: AgriEngineering
      PubDate: 2022-03-18
      DOI: 10.3390/agriengineering4010022
      Issue No: Vol. 4, No. 1 (2022)
       
 
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