Results 101 to 110 of about 722,503 (205)

CROP Political Survey 2002-10B

, 2023
The CROP Inc. political surveys in the Canadian Opinion Research Archive are focussed primarily on the political attitudes of residents in Quebec. The surveys were conducted on an occasional basis depending on events in the province. The are concentrated,
CROP
core   +1 more source

Unmanned aerial vehicle–based spatiotemporal phenotyping and growth modeling for forecasting potato yield

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Monitoring spatial variations in plant growth and forecasting yield before harvest provides valuable insights for optimizing agronomic decision‐making in potato (Solanum tuberosum L.) cultivation. Although unmanned aerial vehicle (UAV)‐based remote sensing has recently enabled the development of tuber fresh weight (TW) estimation models, their
Yuto Imachi, Kunihiro Tanaka, Minato Miyauchi, Kyosuke Miyamoto, Masahiro Okada, Pieter M. Blok, Wei Guo, Hiroyoshi Iwata   +7 more
wiley   +1 more source

CROP Political Survey 1982-03

, 2023
The CROP Inc. political surveys in the Canadian Opinion Research Archive are focussed primarily on the political attitudes of residents in Quebec. The surveys were conducted on an occasional basis depending on events in the province. The are concentrated,
CROP
core   +1 more source

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

CROP Political Survey 2001-11

, 2023
The CROP Inc. political surveys in the Canadian Opinion Research Archive are focussed primarily on the political attitudes of residents in Quebec. The surveys were conducted on an occasional basis depending on events in the province. The are concentrated,
CROP
core   +1 more source

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal, Mohammad Maruf Billah, Mandeep Singh, Dante Koupal, Pradeep Raj Sitaula, Jyotirmoy Halder, Jagdeep Sidhu, Maitiniyazi Maimaitijiang, Sunish K. Sehgal   +8 more
wiley   +1 more source

CROP Political Survey 1990-12

, 2023
The CROP Inc. political surveys in the Canadian Opinion Research Archive are focussed primarily on the political attitudes of residents in Quebec. The surveys were conducted on an occasional basis depending on events in the province. The are concentrated,
CROP
core   +1 more source

High‐throughput image‐based phenotyping of soybean hilum color

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Hilum color in soybean (Glycine max [L.] Merr.) is an important morphological trait influencing market classification and seed quality traits, yet its phenotyping is largely subjective, relying on visual inspection and assignment to one of eight color classes. This study developed an image‐based high‐throughput pipeline to measure and classify
Katherine Fortune, Ali Heidari, Milad Eskandari   +2 more
wiley   +1 more source

Phenomics assisted trait dissection and genotype selection for improved nitrogen use efficiency in rice

Plant Stress
Modern crop phenomics and current advances in machine learning (ML) models are promising tools to speed up genetic improvement of nitrogen use efficiency (NUE) in rice.
Nguyen Trung Duc, Dhandapani Raju, Sudhir Kumar, Renu Pandey, Ranjith Kumar Ellur, Gopala Krishnan S, Chandan Vishwakarma, Elangovan Allimuthu, Biswabiplab Singh, Ambika Rajendran, Rabi Narayan Sahoo, Viswanathan Chinnusamy   +11 more
doaj   +1 more source

AGIcam: An open‐source Internet of Things–based camera system for automated in‐field phenotyping and yield prediction

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Continuous, high‐frequency monitoring is essential to capture rapid phenological transitions and dynamic crop responses to the environment. However, most phenotyping platforms lack the temporal resolution and automation required for consistent, season‐long trait assessment.
Worasit Sangjan, Nisit Pukrongta, Trevor Buchanan, Arron H. Carter, Michael O. Pumphrey, Sindhuja Sankaran   +5 more
wiley   +1 more source