Results 11 to 20 of about 870,191 (308)
Heteroskedasticity in Crop Yield Models
Journal of Agricultural and Resource Economics, 1992 This study examines three alternative models of correcting for heteroskedasticity in wheat yield: The time trend variance, the GARCH, and an econometric model that includes the potential sources of heteroskedasticity.
Seung-Ryong Yang +2 more
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Agrivoltaics Crop Yield Modeling
AgriVoltaics Conference ProceedingsAgrivoltaics (APV) combine agriculture and photovoltaic (PV) energy production on the same land and have the potential to provide several synergies for both production systems.
Felix Schuck +3 more
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A Systematic Literature Review on Crop Yield Prediction with Deep Learning and Remote Sensing
Remote Sensing, 2022 Deep learning has emerged as a potential tool for crop yield prediction, allowing the model to automatically extract features and learn from the datasets. Meanwhile, smart farming technology enables the farmers to achieve maximum crop yield by extracting
Priyanga Muruganantham +4 more
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Plant Biology, 2021 AbstractEpisodes of water shortage occur in most agricultural regions of the world. Their durations and intensities increase, and their seasonal timing alters with changing climate. During the ontogenic cycle of crop plants, each development stage, such as seed germination, seedling establishment, vegetative root and shoot growth, flowering ...
K.‐J. Dietz, C. Zörb, C.‐M. Geilfus
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Crop‐Yield Distributions Revisited [PDF]
American Journal of Agricultural Economics, 2003 AbstractThis article revisits the issue of crop‐yield distributions using improved model specifications, estimation, and testing procedures that address the concerns raised in recent literature, which could have invalidated previous findings of yield nonnormality.
Octavio A. Ramirez +2 more
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International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2021 Cotton, popularly known as White Gold has been an important commercial crop of National significance due to the immense influence of its rural economy. Transfer of technology to identify the quality of fibre is gaining importance for crop yield is compared with Random forest, Support Vector Machine, Weather, K Nearest neighbor.
Pallavi Shankarrao Mahore +1 more
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Advancements in remote sensing based crop yield modelling in India
Journal of Agrometeorology, 2023 Crop yield prediction at regional levels is an essential task for the decision-makers for rapid decision making. Pre-harvest prediction of a crop yield can prevent a disastrous situation and help decision-makers to apply more reliable and accurate ...
N. R. PATEL +2 more
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Crop Yield Gaps in Cameroon [PDF]
AMBIO, 2013 Although food crop yields per hectare have generally been increasing in Cameroon since 1961, the food price crisis of 2008 and the ensuing social unrest and fatalities raised concerns about the country's ability to meet the food needs of its population.
Genesis T, Yengoh, Jonas, Ardö
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Crop Yield Prediction Using Deep Neural Networks [PDF]
, 2019 Crop yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions. Accurate yield prediction requires fundamental understanding of the functional relationship between yield and these interactive ...
Khaki, Saeed, Wang, Lizhi, Wang, Lizhi
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Long-Term Corn–Soybean Rotation and Soil Fertilization: Impacts on Yield and Agronomic Traits
Agronomy, 2022 Although crop rotations have been widely shown as an effective approach for improving yield or soil quality in the long term, the relationship between crop rotations and quality traits of crop or biochar-based fertilization is still unclear.
Ming Yuan +19 more
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