Results 41 to 50 of about 163,439 (186)

Advancing Agricultural Production With Machine Learning Analytics: Yield Determinants for California's Almond Orchards. [PDF]

, 2020
Agricultural productivity is subject to various stressors, including abiotic and biotic threats, many of which are exacerbated by a changing climate, thereby affecting long-term sustainability.
Brown, Patrick H, Chen, Bin, Jin, Yufang, Lampinen, Bruce D   +3 more
core   +3 more sources

California Almond Yield Prediction at the Orchard Level With a Machine Learning Approach. [PDF]

, 2019
California's almond growers face challenges with nitrogen management as new legislatively mandated nitrogen management strategies for almond have been implemented.
Brown, Patrick, Chen, Bin, Jin, Yufang, Zhang, Zhou   +3 more
core   +2 more sources

Dominance and G×E interaction effects improvegenomic prediction and genetic gain inintermediate wheatgrass (Thinopyrumintermedium) [PDF]

, 2020
Genomic selection (GS) based recurrent selection methods were developed to accelerate the domestication of intermediate wheatgrass [IWG, Thinopyrum intermedium (Host) Barkworth & D.R. Dewey].
Bajgain P., Bajgain P., Bandeira e Sousa M., Crossa J., Falconer D., Granato I., Lopez‐Cruz M., Meuwissen T. H., Morais O., Muleta K. T., Oliveira G., Sallam A. H., Wagoner P., Wolfe M. D., Zhang X.   +14 more
core   +1 more source

MT-CYP-Net: Multi-task network for pixel-level crop yield prediction under very few samples

International Journal of Applied Earth Observations and Geoinformation
Accurate and fine-grained crop yield prediction plays a crucial role in advancing global agriculture. However, the accuracy of pixel-level yield estimation based on satellite remote sensing data has been constrained by the scarcity of ground truth data ...
Shenzhou Liu, Di Wang, Haonan Guo, Chengxi Han, Wenzhi Zeng   +4 more
doaj   +1 more source

Winter wheat yield prediction using convolutional neural networks from environmental and phenological data

Scientific Reports, 2022
Crop yield forecasting depends on many interactive factors, including crop genotype, weather, soil, and management practices. This study analyzes the performance of machine learning and deep learning methods for winter wheat yield prediction using an ...
Amit Kumar Srivastava, Nima Safaei, Saeed Khaki, Gina Lopez, Wenzhi Zeng, Frank Ewert, Thomas Gaiser, Jaber Rahimi   +7 more
doaj   +1 more source

Combined Spectral and Spatial Modeling of Corn Yield Based on Aerial Images and Crop Surface Models Acquired with an Unmanned Aircraft System

Remote Sensing, 2014
Precision Farming (PF) management strategies are commonly based on estimations of within-field yield potential, often derived from remotely-sensed products, e.g., Vegetation Index (VI) maps.
Jakob Geipel, Johanna Link, Wilhelm Claupein   +2 more
doaj   +1 more source

Sustainable Crop Yield Prediction

International Research Journal on Advanced Engineering Hub (IRJAEH)
Accurate forecasting of crop yields is fundamental to improving agricultural efficiency and ensuring global food availability. This research implements machine learning methodologies to estimate crop output using key agronomic and environmental indicators, such as precipitation, pesticide application, mean temperature, and carbon emissions.
null Aman Pramod Kumbhar, null Ashutosh Kulkarni, null Shaili Kakde, null Shreya Gupt, null Vaishali Jadhav   +4 more
openaire   +1 more source

Agricultural Crop Yield Prediction Using Machine Learning

Revista Arbitrada Interdisciplinaria Koinonía, 2020
Crop yield prediction is addressed through machine learning. Two predictor variables were used: hectares harvested, and production in tons. For the first case, the best model was a dense neural network (DNN) architecture, with a MSE of 0.0081, followed ...
Joel Junior García-Arteaga, Jesús Javier Zambrano-Zambrano, Roberth Alcivar-Cevallos, Walter Daniel Zambrano-Romero   +3 more
doaj   +1 more source

The performance of the EU-Rotate_N model in predicting the growth and nitrogen uptake of rotations of field vegetable crops in a Mediterranean environment [PDF]

, 2013
The EU-Rotate_N model was developed as a tool to estimate the growth and nitrogen (N) uptake of vegetable crop rotations across a wide range of European climatic conditions and to assess the economic and environmental consequences of alternative ...
A. VENEZIA, Allen, C. NENDEL, C. R. RAHN, Cao, F. PIRO, Guertal, R. D. LILLYWHITE, Rahn, Stanski, T. REN, Westerveld, Willmott   +12 more
core   +1 more source

The Prediction of Wheat Yield in the North China Plain by Coupling Crop Model with Machine Learning Algorithms

Agriculture, 2022
The accuracy prediction for the crop yield is conducive to the food security in regions and/or nations. To some extent, the prediction model for crop yields combining the crop mechanism model with statistical regression model (SRM) can improve the ...
Yanxi Zhao, Dengpan Xiao, Huizi Bai, Jianzhao Tang, De Li Liu, Yongqing Qi, Yanjun Shen   +6 more
doaj   +1 more source