Dataset Information

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

ABSTRACT: 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 controllability, or root phenotypic acquisition. Here, we report the WinRoots, a low-cost and high-throughput plant soil cultivation and phenotyping system that can provide uniform, controlled soil stress conditions and accurately quantify the whole-plant phenome, including roots. Using soybean seedlings exposed to salt stress as an example, we demonstrate the uniformity and controllability of the soil environment in this system. A high-throughput multiple-phenotypic assay among 178 soybean cultivars reveals that the cotyledon character can serve as a non-destructive indicator of the whole-seedling salt tolerance. Our results demonstrate that WinRoots is an effective tool for high-throughput plant cultivation and soil stress phenomics studies.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC8832124 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

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

Zhang Yangyang Y Zhang Wenjing W Cao Qicong Q Zheng Xiaojian X Yang Jingting J Xue Tong T Sun Wenhao W Du Xinrui X Wang Lili L Wang Jing J Zhao Fengying F Xiang Fengning F Li Shuo S

Frontiers in plant science 20220128

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 controllability, or root phenotypic acquisition. Here, we report the WinRoots, a low-cost and high-throughput plant soil cultivation and phenotyping system that can provide uniform, controlled soil stress conditions and accurately quantify the whole-pla ...[more]

PMID: 35154184

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Project description:During the last decade, there has been rapid adoption of ground and aerial platforms with multiple sensors for phenotyping various biotic and abiotic stresses throughout the developmental stages of the crop plant. High throughput phenotyping (HTP) involves the application of these tools to phenotype the plants and can vary from ground-based imaging to aerial phenotyping to remote sensing. Adoption of these HTP tools has tried to reduce the phenotyping bottleneck in breeding programs and help to increase the pace of genetic gain. More specifically, several root phenotyping tools are discussed to study the plant's hidden half and an area long neglected. However, the use of these HTP technologies produces big data sets that impede the inference from those datasets. Machine learning and deep learning provide an alternative opportunity for the extraction of useful information for making conclusions. These are interdisciplinary approaches for data analysis using probability, statistics, classification, regression, decision theory, data visualization, and neural networks to relate information extracted with the phenotypes obtained. These techniques use feature extraction, identification, classification, and prediction criteria to identify pertinent data for use in plant breeding and pathology activities. This review focuses on the recent findings where machine learning and deep learning approaches have been used for plant stress phenotyping with data being collected using various HTP platforms. We have provided a comprehensive overview of different machine learning and deep learning tools available with their potential advantages and pitfalls. Overall, this review provides an avenue for studying various HTP platforms with particular emphasis on using the machine learning and deep learning tools for drawing legitimate conclusions. Finally, we propose the conceptual challenges being faced and provide insights on future perspectives for managing those issues.

Dataset Information

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

Publications

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

Similar Datasets

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