Výsledky vyhledávání - "stress phenotyping"

Akademický článek

Explainable light-weight deep learning pipeline for improved drought stress identification

Autor: Aswini Kumar Patra, Lingaraj Sahoo

Publikováno v: Frontiers in Plant Science, Vol 15 (2024)

IntroductionEarly identification of drought stress in crops is vital for implementing effective mitigation measures and reducing yield loss. Non-invasive imaging techniques hold immense potential by capturing subtle physiological changes in plants un

Externí odkaz: https://doaj.org/article/ae071969c36c4cc3892c8b34cc472788

Zobrazit plný text záznamu

Akademický článek

Plant Stress Detection Using a Three-Dimensional Analysis from a Single RGB Image

Autor: Madaín Pérez-Patricio, J. A. de Jesús Osuna-Coutiño, German Ríos-Toledo, Abiel Aguilar-González, J. L. Camas-Anzueto, N. A. Morales-Navarro, J. Renán Velázquez-González, Luis Ángel Cundapí-López

Publikováno v: Sensors, Vol 24, Iss 23, p 7860 (2024)

Plant stress detection involves the process of Identification, Classification, Quantification, and Prediction (ICQP) in crop stress. Numerous approaches exist for plant stress identification; however, a majority rely on expert personnel or invasive t

Externí odkaz: https://doaj.org/article/66926da0bef3461482d519561c936e2e

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Akademický článek

Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean

Autor: Ashlyn Rairdin, Fateme Fotouhi, Jiaoping Zhang, Daren S. Mueller, Baskar Ganapathysubramanian, Asheesh K. Singh, Somak Dutta, Soumik Sarkar, Arti Singh

Publikováno v: Frontiers in Plant Science, Vol 13 (2022)

Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GW

Externí odkaz: https://doaj.org/article/069e944f59ec48798ddd2308075ba99d

Zobrazit plný text záznamu

Akademický článek

Improving model robustness for soybean iron deficiency chlorosis rating by unsupervised pre-training on unmanned aircraft system derived images

Autor: Li, Jiating ^a, Oswald, Cody ^b, Graef, George L. ^b, Shi, Yeyin ^{a, ⁎}

Publikováno v: In Computers and Electronics in Agriculture August 2020 175

Zobrazit plný text záznamu

Akademický článek

A Synthetic Review of Various Dimensions of Non-Destructive Plant Stress Phenotyping

Autor: Dapeng Ye, Libin Wu, Xiaobin Li, Tolulope Opeyemi Atoba, Wenhao Wu, Haiyong Weng

Publikováno v: Plants, Vol 12, Iss 8, p 1698 (2023)

Non-destructive plant stress phenotyping begins with traditional one-dimensional (1D) spectroscopy, followed by two-dimensional (2D) imaging, three-dimensional (3D) or even temporal-three-dimensional (T-3D), spectral-three-dimensional (S-3D), and tem

Externí odkaz: https://doaj.org/article/52bce445aca5461f869d518c1aea7820

Zobrazit plný text záznamu

Akademický článek

WinRoots: A High-Throughput Cultivation and Phenotyping System for Plant Phenomics Studies Under Soil Stress

Autor: Yangyang Zhang, Wenjing Zhang, Qicong Cao, Xiaojian Zheng, Jingting Yang, Tong Xue, Wenhao Sun, Xinrui Du, Lili Wang, Jing Wang, Fengying Zhao, Fengning Xiang, Shuo Li

Publikováno v: Frontiers in Plant Science, Vol 12 (2022)

Soil stress, such as salinity, is a primary cause of global crop yield reduction. Existing crop phenotyping platforms cannot fully meet the specific needs of phenomics studies of plant response to soil stress in terms of throughput, environmental con

Externí odkaz: https://doaj.org/article/d155c411047649c2ab6f49e6395e64d4

Zobrazit plný text záznamu