Results 161 to 170 of about 136,284 (289)

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang   +12 more
wiley   +1 more source

Determination of the contact patch length in tractor tire-soil interaction. [PDF]

open access: yesSci Rep
Nadykto V   +7 more
europepmc   +1 more source

Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe   +3 more
wiley   +1 more source

Phenotype imputation using high‐throughput phenotyping produces a new secondary trait for further selection modeling

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Data from high‐throughput phenotyping (HTP) could be used for phenotype imputation to enhance genomic selection (GS) or gene discovery, but this has not been explored in crop species. Three machine learning models: multiple linear regression (MLR), missForest, and k‐nearest neighbors, were evaluated for grain yield (GY) phenotype imputation in
Raysa Gevartosky   +2 more
wiley   +1 more source

Growth and yield response of cashew (Anacardium occidentale L.) clones to spacing in the Guinea Savanna zone of Ghana

open access: yesAgrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract The Guinea Savanna zone of many countries constitutes a critical cashew‐producing area. Despite its importance, data‐driven recommendations on optimal tree spacing remain largely unavailable to farmers in Ghana. This knowledge gap constrains productivity, reduces returns on investment, and affects farmer interest and ultimately the long‐term ...
Sampson Konlan   +7 more
wiley   +1 more source

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