Results 171 to 180 of about 117,891 (325)
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Grain characteristics are the cumulative product of growth and development throughout the growing season. In barley (Hordeum vulgare), these traits determine the grain's value for malting purposes. The ability to accurately predict the genetic merit for malting quality is of great interest for barley breeding programs. Same‐season selection on
Amelia Loeb +10 more
wiley +1 more source
UAV NDVI-Based Vigor Zoning Predicts PR-Protein Accumulation and Protein Instability in Chardonnay and Sauvignon Blanc Wines. [PDF]
Plants (Basel)Vera-Esmeraldas A +5 more
europepmc +1 more source
Utilizing high‐throughput phenotyping to identify metribuzin tolerance in winter wheat
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Plant breeders and weed scientists address weed management collaboratively by selecting for herbicide tolerance in breeding programs. Metribuzin, a Group 5 PSII‐inhibiting herbicide, is labeled for use in wheat (Triticum aestivum L.). However, application to currently available lines results in frequent, variable, and unpredictable crop injury.
Melinda Zubrod +4 more
wiley +1 more source
Genetic mapping and candidate gene identification for key physiological traits associated with heat tolerance in wheat (Triticum aestivum L.) using a MAGIC population. [PDF]
PLoS OneBag A +12 more
europepmc +1 more source
Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
The 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
Machine learning‐based prediction of cereal rye cover crop biomass across diverse agroecosystems
Agricultural &Environmental Letters, Volume 11, Issue 1, June 2026.Abstract Accurate operational predictions of cereal rye (Secale cereale L.) biomass are critical for quantifying the agroecosystem services provided by cover crops and for guiding growers’ management decisions for subsequent cash crops. In this study, we developed machine learning‐based biomass prediction models using two advanced gradient‐boosted tree
Utsab Ghimire +6 more
wiley +1 more source
Flash droughts exacerbate global vegetation loss and delay recovery. [PDF]
Nat CommunChai Y +8 more
europepmc +1 more source
VEGETATION HOMOGENEOUS REGIONS USING NDVI VARIABILITY
, 2017 The classification techniques, such as cluster analysis, used in biological areas, in the plants and animals classification keys, are also useful for defining homogeneous regions, for climate data or for identification or monitoring of vegetation.
Cordeiro, Ana Paula Assumpção +5 more
openaire +1 more source