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| Filter results7 paper(s) found. |
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1. Predicting Winter Wheat Biomass And Grain Protein ContentDynamic crop models such as EPIC [1], SALUS [2], and STICS [3] are non-linear models that describe the growth and development of a crop interacting with environmental factors (soil and climate) and agricultural practices (crop species, tillage type, fertilizer amount…). They are developed to predict crop yield and quality or to optimize the farming practices in order to satisfy agricultural objectives, as the reduction of nitrogen lixiviation. More recently, crop... M.M. Mansouri |
2. Application Of Hyperspectral Imaging For Rapid And Non-Invasive Quantification Of Quality Of Mulberry FruitThis study investigated the potential of using hyperspectral imaging working in visible and short-wave near infrared region (380-1030 nm) for rapid and non-invasive determination of the total flavonoid in mulberry fruit. Mulberry fruit with its sweet flavor is widely used in jam, pies, tarts, wines, and liquor, and is a delicacy among humans and birds alike. The quality evaluation of mulberry is usually determined by chemical or sensory analysis. However these methods are not ca... L. Huang, H. Jin, Y. He, F. Liu, Y. Zhou |
3. A Novel Hyperspectral Feature Extraction Algorithm Based On Waveform Resolving For Raisin ClassificationNear infrared hyperspectral imaging technology was adopted in the paper to determine the variety of raisins produced in Xinjiang Uygur Autonomous Region, China. There are 2 varieties of raisins taking part in the research and the wavelengths of the hyperspectral images are from 900nm to 1700nm. A novel waveform resolving method was proposed in the paper to reduce the hyperspectral data and extract features. The waveform resolving method compresses the original hyperspectral data for one ... Y. Zhao, X. Xu, Y. Shao, Y. He, Q. Li |
4. Survey of Pesticide Application Practices and Technologies in Georgia Agricultural CropsGeorgia is a leading producer of numerous crops including cotton, peanut, blueberries, pecans, bell peppers, cabbage, watermelons, and peaches in the United States. Pesticide applications are critical for the successful production of these crops. Pesticide regulations and application technologies are changing rapidly due to growing concerns around off-target movement and increased focus on improving the efficiency and efficacy of pesticide applications. In order to provide suitable ... S.S. Virk, E.P. Prostko |
5. Precision Agriculture Education in Africa: Perceptions, Opportunities and Challenges, and the Way ForwardPrecision Agriculture is critical for accelerated transformation of the agrifood systems in Africa for shared prosperity and enhanced livelihoods. The paper presents an overview of the perceptions of faculty, undergraduate and postgraduate students from Ghanaian universities about PA education, and its opportunities and challenges. The study involves a case study of two public universities, the University of Cape Coast and the Technical University of Cape Coast, respectively a and a desk revi... K.A. Frimpong |
6. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in ArgentinaThe lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomis... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito |
7. Teaching Mathematics Towards Precision Agriculture Through Data Analysis and ModelsPrecision agriculture is used in a wide variety of field operations and agricultural practices that affect our daily lives. Many fields of agriculture are increasingly adopting equipment automation, robotics, and machine learning techniques. These all lead to recognize that data collection and exploitation is a valuable tool assisting in real-time farming and livestock decisions. Thus, the immediate need to empower students in Agriculture Sciences with mathematical tools using data analysis i... R. Sviercoski |