Results 131 to 140 of about 163,439 (186)

Wheat yield prediction using integrated optical and radar remote sensing with machine learning across key phenological stages. [PDF]

Sci Rep
Navidi MN, Fazli E, Kharazmi R, Seyedmohammadi J.   +3 more
europepmc   +1 more source

UAV multispectral sensing and data-driven modeling for precision onion yield prediction. [PDF]

Front Plant Sci
Wayal SM, Parab S, Raj A, Khandagale K, Bhegde S, Dawale M, Bhangare I, Khaire M, Kadam Y, Shaikh Z, Karuppaiah V, Gedam P, Bibwe B, More SJ, Sharma LK, Mahajan V, Gawande SJ.   +16 more
europepmc   +1 more source

Predicting Multiple Traits of Rice and Cotton Across Varieties and Regions Using Multi-Source Data and a Meta-Hybrid Regression Ensemble. [PDF]

Sensors (Basel)
Qin Y, Tauqir M, Yu X, Zheng X, Jiang X, Xu N, Zhang J.   +6 more
europepmc   +1 more source

Artificial intelligence in plant science: from image-based phenotyping to yield and trait prediction. [PDF]

Front Plant Sci
Wang T, Tong R, Xu T, Li Y, Chen Y.
europepmc   +1 more source

Agentic AI-driven autonomous decision support system for smart agriculture. [PDF]

Sci Rep
Swati NLP, Gupta SV, Duddela NS, Parvathy LR.   +3 more
europepmc   +1 more source

Towards enhancing the performance of crop prediction system for precision agriculture using feature correlation square-based nearest neighbor classifier. [PDF]

Sci Rep
Kindra K, Bhuvaneswari Amma NG, Nageswari Amma NG.   +2 more
europepmc   +1 more source

Harvesting insights: interpretable machine learning to understand environmental drivers of U.S. maize and soybean yield. [PDF]

Sci Rep
Smith HW, Heffernan CJ, Ashworth AJ, Nalley LL, Bullock DS, Tullis J, Owens PR.   +6 more
europepmc   +1 more source

Machine learning for multi-omics data integration in crop improvement: a systematic review. [PDF]

BMC Bioinformatics
Tsega A, Mullualem D.
europepmc   +1 more source

An evaluation of machine learning for soil analysis in internet of things-enabled smart farming. [PDF]

Sci Rep
Chaudhary P, Gulia P, Gill NS, Alduaiji N, Shukla PK, Vishnoi S.   +5 more
europepmc   +1 more source

MS-YieldStackNet: multi-source data fusion for wheat yield estimation using a stacked ensemble neural network. [PDF]

PeerJ Comput Sci
Ali W, Ramzan Z, Shahbaz M, Bhutta QUZ, Talha M, J AlGhamdi M.   +5 more
europepmc   +1 more source