Results 41 to 50 of about 307,779 (118)

Artificial intelligence and Multispectral Imaging Technologies for Assessing Climate Impact on Maize Yield: A Literature Review

Maǧallaẗ al-baṣraẗ al-ʻulūm al-zirāʻiyyaẗ
Maize production in Central America and Mexico is particularly susceptible to climate variability, especially the El Niño-Southern Oscillation (ENSO), which causes drought and irregular rainfall.
Carlos R. Martínez- Martínez, Felipe Machorro- Ramos, Laura Rodríguez- Peralta   +2 more
doaj   +1 more source

Development of a 2D Image-Based Rice Panicle-Level Yield Prediction Framework Using Image-Based Reconstruction Technique

Agronomy
Asian countries, which account for more than 60% of global rice consumption, are expanding the adoption of precision agriculture technology using image sensors to increase the profitability of rice production.
Daehong Kim, Hyeongjun Lim, Sojung Kim
doaj   +1 more source

Sensitive Multispectral Variable Screening Method and Yield Prediction Models for Sugarcane Based on Gray Relational Analysis and Correlation Analysis

Remote Sensing
Sugarcane yield prediction plays a pivotal role in enabling farmers to monitor crop development and optimize cultivation practices, guiding harvesting operations for sugar mills. In this study, we established three experimental fields, which were planted
Shimin Zhang, Huojuan Qin, Xiuhua Li, Muqing Zhang, Wei Yao, Xuegang Lyu, Hongtao Jiang   +6 more
doaj   +1 more source

Simulation of strawberry yield using dry matter distribution based on the potential growth of the sink–source organs

Frontiers in Plant Science
Strawberry, a vital crop in horticulture, faces challenges like pest infestations and climate variability that affect stable production. A crop model based on photosynthesis-derived dry matter (DM) production is an effective method to examine the ...
Tomomi Sugiyama, Yusuke Kakei, Yasunaga Iwasaki, Atsushi Oda, Masahide Isozaki   +4 more
doaj   +1 more source

Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield

Plant Production Science
Techniques for determining the amount of nitrogen topdressing based on remote sensing during the flowering stage of wheat require highly accurate yield predictions. Optimal wavelength combinations for accurately predicting nitrogen uptake and wheat yield
Akina Mizumoto, Hiroko Sawada, Ryo Terasaki, Kou Nakazono, Hiroe Yoshida, Akihiro Ohsumi, Akira Fukushima   +6 more
doaj   +1 more source

Sensor-Based Yield Prediction in Durum Wheat Under Semi-Arid Conditions Using Machine Learning Across Zadoks Growth Stages

Remote Sensing
Yield prediction in wheat cultivated under semi-arid climatic conditions is gaining increasing importance for sustainable production strategies and decision support systems.
Süreyya Betül Rufaioğlu, Ali Volkan Bilgili, Erdinç Savaşlı, İrfan Özberk, Salih Aydemir, Amjad Mohamed Ismael, Yunus Kaya, João P. Matos-Carvalho   +7 more
doaj   +1 more source

Field-Scale Prediction of Winter Wheat Yield Using Satellite-Derived NDVI

Agronomy
This study evaluated the potential of Sentinel-2-derived NDVI (Normalized Difference Vegetation Index) for predicting within-field variability of winter wheat grain yield in central Lithuania during the 2024 growing season.
Edyta Okupska, Antanas Juostas, Dariusz Gozdowski, Elżbieta Wójcik-Gront   +3 more
doaj   +1 more source

Winter Wheat Yield Estimations Based on Multisource Remote Sensing Parameters and the BiLSTM–CNN Model

Remote Sensing
Winter wheat is a cornerstone of China’s grain production, contributing substantially to national food security and overall cereal output. This study modeled the nonlinear associations between multitemporal remote sensing variables and winter wheat yield.
Yi Xie, Sicheng Ma, Lan Xun, Shujing Shi, Pengxin Wang   +4 more
doaj   +1 more source

Joint Prediction of Cucumber Price and Yield Based on LSTM Weight Sharing

International Journal of Crowd Science
The agricultural market is characterized by unpredictable price fluctuations influenced by diverse uncontrollable factors, often leading to a mismatch between production and income, thus creating a vicious cycle.
Wenzheng Song, Yong Zheng, Yuchun Wang, Lun Hao, Lianjun Guo, Qingfeng Hao, Lizhen Cui, Yonghui Xu   +7 more
doaj   +1 more source

Improving grain yield prediction in Southern US oat germplasm using genomics information and environmental covariates. [PDF]

Plant Genome
Adewale SA, Babar MA, Jarquin D, Khan N, Harrison S, DeWitt N, Boyles R, Liu S, Melson E, Hathcoat D, Fiedler JD, Nandety RS.   +11 more
europepmc   +1 more source