Results 121 to 130 of about 4,378 (202)

Phenomic prediction I: Plot‐level prediction of lodging severity in sorghum breeding trials using UAV‐based photogrammetric height data

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Lodging in sorghum (Sorghum bicolor (L.) Moench) presents a significant challenge for plant breeders due to the trade‐off between lodging resistance and grain yield. Manually measuring lodging across thousands of plots is time‐consuming, expensive, and error‐prone, making selection for lodging resistance challenging in breeding programs ...
Srinivasa Reddy Mothukuri, Sean Reynolds Massey‐Reed, Andries Potgieter, Kenneth Laws, Colleen Hunt, Esinam Nancy Amuzu‐Aweh, Mark Cooper, Emma Mace, David Jordan   +8 more
wiley   +1 more source

A data‐driven image extraction and analysis pipeline for plant phenotyping in controlled environments

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Advances in automation, imaging, and artificial intelligence have enabled large‐scale plant phenotyping, but image analysis remains a critical bottleneck for crop improvement and biological discovery. We developed an integrated multispectral phenotyping framework using imagery from the Texas A&M AgriLife Automated Precision Phenotyping ...
Fahimeh Orvati Nia, Joshua Peeples, Seth C. Murray, Andrew McFarland, Troy Vann, Shima Salehi, Robert Hardin, David D. Baltensperger, Amir M. H. Ibrahim, J. Alex Thomasson, Henry Fadamiro, Nithya K. Subramanian, Suresh D. Pillai, Rebecca Roston, Joslin Ishimwe, Diptadeep Basak, Nazar Oladepo, Uday Vysyaraju   +17 more
wiley   +1 more source

Computer vision associated with multivariate genomic selection methods increases yield prediction accuracy in blueberry

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Blueberry (Vaccinium spp.) is among the most consumed soft fruits and an important source of health‐promoting compounds. Among the key traits driving selection in breeding programs, yield is the most important. The standard way to measure yield is harvesting and weighing the total number of berries, a process that is laborious, expensive ...
Matheus M. Suela, Luis F. V. Ferrão, Paul M. Adunola, Camila F. Azevedo, Bruno C. C. Leme, Patricio Munoz   +5 more
wiley   +1 more source

Genomic characterization of plant height and lodging in spring oat (Avena sativa L.) using time‐series aerial sensor data

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Plant height is one of the key economic traits in spring oat (Avena sativa L.) and a major determinant of lodging, and consequently, yield potential. Understanding the genetic basis of the variation in plant height can significantly benefit plant improvement efforts.
Afrina Rahman, Anup Kumar Das, Jayanta Roy, Amandeep, Michael S. McMullen, Paulo Flores, Craig H. Carlson   +6 more
wiley   +1 more source

Resolving early growth variation in Pinus radiata: Effective indoor phenotyping of juvenile trees

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Indoor plant phenotyping facilities provide high‐resolution, dynamic trait data not achievable with other systems, but are rarely applied to trees due to size constraints. Using the model conifer Pinus radiata, this study evaluated whether early growth variation among three clonal genotypes can be detected and reliably resolved using indoor ...
S. A. Wakelin, B. Berger, S. Smaill, N. Jewell, C. Brien   +4 more
wiley   +1 more source

Reaction norm modeling of high‐dimensional genomic and environmental data improves prediction accuracy in winter wheat

The Plant Genome, Volume 19, Issue 4, December 2026.
Abstract Genomic prediction models that account for genotype‐by‐environment (G × E) have the potential to accelerate the rate of genetic gain for yield and agronomic performance, yet relatively few studies have applied G × E prediction in public soft red winter wheat (Triticum aestivum) breeding programs.
Shailesh Raj Acharya, Julian Garcia‐Abadillo, Jeanette Lyerly, Gina Brown‐Guedira, Diego Jarquin, Nonoy Bandillo   +5 more
wiley   +1 more source

Quantifying genetic and nongenetic improvement for grain yield in faba bean breeding

Crop Science, Volume 66, Issue 6, November/December 2026.
Abstract Faba Bean (Vicia faba) is a cool season legume crop, often grow as a rotation crop to improve sustainability of the farming systems. The Australian faba bean breeding program is publicly funded, with improving grain yield as a key breeding objective to increase grower profitability.
Huanhuan Zhao, Charity Chidzanga, Zulfi Jahufer, Samuel C. Catt   +3 more
wiley   +1 more source

Breeding for multi‐stress resilience in crops: Myth or possibility?

PLANTS, PEOPLE, PLANET, Volume 8, Issue 6, Page 1968-1977, November 2026.
Climate change threatens millions of farmers worldwide by exposing crops to multiple concurrent or sequential environmental stresses such as drought, heat, waterlogging, and diseases. Although crops have long been selected under naturally occurring multi‐stress conditions, breeding pipelines largely focus on optimal or single‐stress environments ...
Hamid Khazaei, Ian C. Dodd, Rodomiro Ortiz   +2 more
wiley   +1 more source

Decision support systems and plant phenomics

, 2016
The Earth is being polluted and territories that were fertile less than a decade ago now become barren. Meanwhile the human population is rapidly growing and the consumption of food is increasing exponentially. To overcome these challenges scientists are working hard on identifying quantitative phenotypes improving which would allow to overcome the ...
Valvachev, A. N., Krasnoproshin, V. V., Mikhalchenko, A. A.   +2 more
openaire   +1 more source