[HTML][HTML] Recent Methods for Evaluating Crop Water Stress Using AI Techniques: A Review
SB Cho, HM Soleh, JW Choi, WH Hwang, H Lee… - Sensors, 2024 - mdpi.com
This study systematically reviews the integration of artificial intelligence (AI) and remote
sensing technologies to address the issue of crop water stress caused by rising global …
sensing technologies to address the issue of crop water stress caused by rising global …
Prediction of crop yield in India using machine learning and hybrid deep learning models
KS Saravanan, V Bhagavathiappan - Acta Geophysica, 2024 - Springer
Crop yield prediction is one of the burgeoning research areas in the agriculture domain. The
crop yield forecasting models are developed to enhance productivity with improved decision …
crop yield forecasting models are developed to enhance productivity with improved decision …
Machine Learning-Powered Forecasting of Climate Conditions in Smart Greenhouse Containing Netted Melons
The greenhouse environment plays a crucial role in providing favorable conditions for crop
growth, significantly improving their quality and yield. Accurate prediction of greenhouse …
growth, significantly improving their quality and yield. Accurate prediction of greenhouse …
LeafArea Package: A Tool for Estimating Leaf Area in Andean Fruit Species
PA Velasquez-Vasconez, D Andrade Díaz - International Journal of Plant …, 2024 - mdpi.com
The LeafArea package is an innovative tool for estimating leaf area in six Andean fruit
species, utilizing leaf length and width along with species type for accurate predictions. This …
species, utilizing leaf length and width along with species type for accurate predictions. This …
Comparative Analysis of Machine Learning Models for Predicting Rice Yield: Insights from Agricultural Inputs and Practices in Rwanda
C Mugemangango, J Nzabanita… - Research on …, 2024 - journals.nasspublishing.com
Food security is a global challenge, especially in developing countries like Rwanda. With a
growing population and limited agricultural land, Rwanda struggles to meet increasing food …
growing population and limited agricultural land, Rwanda struggles to meet increasing food …
[HTML][HTML] Evaluation and comparison of AquaCrop model and intelligent models to predict wheat yield (Case study: Miandoab and Mahabad cities)
M Sharafi, J Behmanesh… - Water and Soil …, 2024 - water-soil.tabrizu.ac.ir
AbstractBackground and Objectives: Due to population growth and Iran's location in arid and
semi-arid regions of the world, the need for water and food has increased and as a result …
semi-arid regions of the world, the need for water and food has increased and as a result …
RGB 画像を用いた岡山県奨励水稲品種「きぬむすめ」 の栄養指標値の推定
山口友亮， 尾澤陽， 前田周平， 妹尾知憲， 桂圭佑 - 日本作物学会紀事, 2023 - jstage.jst.go.jp
抄録 RGB 画像から岡山県奨励水稲品種 「きぬむすめ」 の栄養指標値を簡便に推定できる手法の
開発を試みた. 同品種を岡山県農林水産総合センター内の異なる圃場において多様な移植日と施肥 …
開発を試みた. 同品種を岡山県農林水産総合センター内の異なる圃場において多様な移植日と施肥 …