Results 201 to 210 of about 97,221 (318)

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

The 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, Lucas Berger Munaro, Jessica E. Rutkoski   +2 more
wiley   +1 more source

Climate Change Trends and Impacts on Vegetation Greening Over the Tibetan Plateau [PDF]

, 2019
Climate Change Center of China Meteorological Administration, Intergovernmental Panel on Climate Change, Kendall M. G., Knight J., Liu Z. Y., Verhoef W.   +5 more
core   +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, Alakananda Mitra, David Fleisher, John Park, Jinyoung Y. Barnaby, Yonghyun Kim, Eunjin Han   +6 more
wiley   +1 more source

Exploring the potential role of multi-source remote sensing data during different growth stages in crop yield prediction. [PDF]

PeerJ
Gu X, Xu E, Chi Y, Zhou L, Liang Q.
europepmc   +1 more source

Multifunctionality of annual forage crop mixtures for improved biomass, beef cattle diets, and soil health outcomes

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Cover crop mixtures (CCMs) can fit well into various agricultural production systems and have gained popularity among grain and livestock producers, as well as organic and market gardeners across western Canada, due to their potential to enhance forage production and soil health.
Akim Tunde Omokanye, Surendra Bhattarai, Guillermo Hernandez Ramirez, Blasius Azuhnwi, Yamily Zavala, Hayford Gyamfi, Bharat Shrestha   +6 more
wiley   +1 more source

Quantifying responses of climatic and anthropogenic factors on vegetation normalized difference vegetation index variabilities over Yellow River Basin, China. [PDF]

Front Plant Sci
Yu Z, Wang L, Yan J, Yuan Z, Zhang X.
europepmc   +1 more source

Spatial relationship of turfgrass tissue nitrogen content and several vegetation indices on sand‐capped golf course fairways

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Vegetation indices (VIs), such as normalized difference vegetation index (NDVI), are widely used to assess nitrogen (N) status in crop systems and are gaining interest in turfgrass management. However, most studies have been conducted in controlled settings, and their relevance under real‐world golf course conditions remains unclear.
Madan Sapkota, Opeyemi E. Alabi, Weston W. Floyd, Sarah G. Hong, Dallas M. Williams, Briana M. Wyatt, A. Peyton Smith, Chase M. Straw   +7 more
wiley   +1 more source

Linking Grassland Canopy Structure and Function Responses to Field Experimental Drought Both Seasonally and Interannually. [PDF]

Ecol Evol
Encarnación Ojeda M, Xiao X, Nguyen EU, Souza L.   +3 more
europepmc   +1 more source

Reengineering the Baldree Traffic Simulator for turfgrass wear and traffic research

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Historically, turfgrass researchers utilized the Baldree Traffic Simulator (BTS) to imitate foot traffic for the evaluation of athletic field wear tolerance and performance. Research was conducted to reengineer the BTS “feet” to improve adaptability and compatibility with other aerification units and determine biophysical effects on two native
Erick G. Begitschke, Matthew Bowen, Larry M. Baldree, Nandita Gaur, Robert C. Lynall, Gerald M. Henry   +5 more
wiley   +1 more source

Economic value of in‐season information from N‐rich strip‐based nitrogen recommendations for winter wheat

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Nitrogen overapplication remains a persistent challenge in winter wheat production, contributing to low nitrogen use efficiency (NUE), higher production costs, and increased environmental externalities. Sensor‐based nitrogen management systems, such as the nitrogen‐rich strip (NRS), were developed to provide in‐season information on crop ...
Enoch Adom, Dayton M. Lambert, Phillip D. Alderman, B. Wade Brorsen   +3 more
wiley   +1 more source