A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control.
TL;DR: A high-throughput phenotyping system that is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions and can quantify the stress caused by freezing injury at the seedling stage is developed.
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Abstract: BACKGROUND Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, a more efficient and accurate method for freezing damage identification is urgently needed. RESULTS A high-throughput phenotyping system was developed in this paper, namely, RGB freezing injury system, to effectively and efficiently quantify the wheat freezing injury in the field environments. The system is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions. A data management system was also developed to store and manage the original images and the calculated phenotypic data in the system. In this experiment, a total of 128 wheat varieties were planted, three nitrogen concentrations were applied and two biological and technical replicates were performed. And wheat canopy images were collected at the seedling pulling stage and three image features were extracted for each wheat samples, including ExG, ExR and ExV. We compared different test parameters and found that the coverage had a greater impact on freezing injury. Therefore, we preliminarily divided four grades of freezing injury according to the test results to evaluate the freezing injury of different varieties of wheat at the seedling stage. CONCLUSIONS The automatic phenotypic analysis method of freezing injury provides an alternative solution for high-throughput freezing damage analysis of field crops and it can be used to quantify freezing stress and has guiding significance for accelerating the selection of wheat excellent frost resistance genotypes.
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References
Exploring the Feasibility of Winter Wheat Freeze Injury by Integrating Grey System Model with RS and GIS
Huifang Wang,Huifang Wang,Wei Guo,Jihua Wang,Jihua Wang,Wenjiang Huang,Xiao-he Gu,Yingying Dong,Yingying Dong,Xin-gang Xu +9 more
TL;DR: Wang et al. as discussed by the authors proposed a grey-system model (GSM) to monitor the degree and the distribution of the winter wheat freeze injury, which combines remote sensing (RS) and geographic information system (GIS) technology.
Freezing tolerance of winter wheat plants frozen in saturated soil
TL;DR: Evidence from progeny populations suggested that improved freezing tolerance was associated with decreased sensitivity to the length of time held at the minimum temperature and increased responsiveness to the post-freezing warming rate, leading to cultivars with improved tolerance of freezing in saturated soil.
Is Yield Increase Sufficient to Achieve Food Security in China
TL;DR: The combined influence of loss in yield and area has determined the crop sustainable production in China to be pessimistic for rice and wheat, and consequently it is no surprise to find that more than half of counties rank a lower level of production sustainability.
Monitoring Winter Wheat Freeze Injury Using Multi-Temporal MODIS Data
TL;DR: In this article, the authors used remote sensing data to monitor the occurrence and spatial distribution of winter wheat freeze in time, as well as the severity of the damage caused by freeze injury.