Juan J. Quirós , Rebecca J. McGee , George J. Vandemark , Thiago Romanelli , Sindhuja Sankaran
{"title":"豌豆(Pisum sativum L)和鹰嘴豆(Cicer arietinum L)多光谱成像的田间表型分析","authors":"Juan J. Quirós , Rebecca J. McGee , George J. Vandemark , Thiago Romanelli , Sindhuja Sankaran","doi":"10.1016/j.eaef.2019.06.002","DOIUrl":null,"url":null,"abstract":"<div><p>Pea (<span><em>Pisum sativum</em></span> L) and chickpea (<span><em>Cicer arietinum</em></span><span><span><span> L) are important grain legumes grown in the Palouse region of the Pacific Northwest United States. The USDA-ARS grain legume breeding program in this region focuses on developing pea and chickpea varieties with high yield potential, resistance to biotic and abiotic stresses, and superior agronomic characteristics. In this study, aerial high resolution multispectral imaging was evaluated to phenotype yield potential differences among genotypes in green pea, yellow pea and chickpea. Five experiments (three </span>field pea and two chickpea) with 10–25 varieties grown at two locations (Pullman, Washington; Genesee, Idaho) were assessed. Images were acquired approximately 60, 70 and 90 days after planting (DAP) at 110 m above ground level. Normalized difference </span>vegetation index (NDVI), green normalized difference vegetation index, soil adjusted vegetation index (SAVI) and simple ratio (SR) image based features (SUM, MIN, MAX, MEAN) were extracted. In most cases, the MEAN NDVI data was found to be consistently correlated with dry seed yield (p < 0.05), with green pea genotypes showing strongest relationship (</span><em>r</em><span> = 0.64–0.93 at about 70 DAP, both during “plot-by-plot” and “by genotype” comparisons). The MEAN SAVI and SR values were also strongly correlated with yield at 61–72 DAP in most of the pea experiments. The data collected during flowering and early pod development phenological growth stages was found to be useful in yield estimation. The developed methods can be used for early generation evaluation in breeding programs, where yield cannot be estimated due to limited seed availability.</span></p></div>","PeriodicalId":38965,"journal":{"name":"Engineering in Agriculture, Environment and Food","volume":"12 4","pages":"Pages 404-413"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Field phenotyping using multispectral imaging in pea (Pisum sativum L) and chickpea (Cicer arietinum L)\",\"authors\":\"Juan J. Quirós , Rebecca J. McGee , George J. Vandemark , Thiago Romanelli , Sindhuja Sankaran\",\"doi\":\"10.1016/j.eaef.2019.06.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Pea (<span><em>Pisum sativum</em></span> L) and chickpea (<span><em>Cicer arietinum</em></span><span><span><span> L) are important grain legumes grown in the Palouse region of the Pacific Northwest United States. The USDA-ARS grain legume breeding program in this region focuses on developing pea and chickpea varieties with high yield potential, resistance to biotic and abiotic stresses, and superior agronomic characteristics. In this study, aerial high resolution multispectral imaging was evaluated to phenotype yield potential differences among genotypes in green pea, yellow pea and chickpea. Five experiments (three </span>field pea and two chickpea) with 10–25 varieties grown at two locations (Pullman, Washington; Genesee, Idaho) were assessed. Images were acquired approximately 60, 70 and 90 days after planting (DAP) at 110 m above ground level. Normalized difference </span>vegetation index (NDVI), green normalized difference vegetation index, soil adjusted vegetation index (SAVI) and simple ratio (SR) image based features (SUM, MIN, MAX, MEAN) were extracted. In most cases, the MEAN NDVI data was found to be consistently correlated with dry seed yield (p < 0.05), with green pea genotypes showing strongest relationship (</span><em>r</em><span> = 0.64–0.93 at about 70 DAP, both during “plot-by-plot” and “by genotype” comparisons). The MEAN SAVI and SR values were also strongly correlated with yield at 61–72 DAP in most of the pea experiments. The data collected during flowering and early pod development phenological growth stages was found to be useful in yield estimation. The developed methods can be used for early generation evaluation in breeding programs, where yield cannot be estimated due to limited seed availability.</span></p></div>\",\"PeriodicalId\":38965,\"journal\":{\"name\":\"Engineering in Agriculture, Environment and Food\",\"volume\":\"12 4\",\"pages\":\"Pages 404-413\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering in Agriculture, Environment and Food\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1881836618302854\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering in Agriculture, Environment and Food","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1881836618302854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
Field phenotyping using multispectral imaging in pea (Pisum sativum L) and chickpea (Cicer arietinum L)
Pea (Pisum sativum L) and chickpea (Cicer arietinum L) are important grain legumes grown in the Palouse region of the Pacific Northwest United States. The USDA-ARS grain legume breeding program in this region focuses on developing pea and chickpea varieties with high yield potential, resistance to biotic and abiotic stresses, and superior agronomic characteristics. In this study, aerial high resolution multispectral imaging was evaluated to phenotype yield potential differences among genotypes in green pea, yellow pea and chickpea. Five experiments (three field pea and two chickpea) with 10–25 varieties grown at two locations (Pullman, Washington; Genesee, Idaho) were assessed. Images were acquired approximately 60, 70 and 90 days after planting (DAP) at 110 m above ground level. Normalized difference vegetation index (NDVI), green normalized difference vegetation index, soil adjusted vegetation index (SAVI) and simple ratio (SR) image based features (SUM, MIN, MAX, MEAN) were extracted. In most cases, the MEAN NDVI data was found to be consistently correlated with dry seed yield (p < 0.05), with green pea genotypes showing strongest relationship (r = 0.64–0.93 at about 70 DAP, both during “plot-by-plot” and “by genotype” comparisons). The MEAN SAVI and SR values were also strongly correlated with yield at 61–72 DAP in most of the pea experiments. The data collected during flowering and early pod development phenological growth stages was found to be useful in yield estimation. The developed methods can be used for early generation evaluation in breeding programs, where yield cannot be estimated due to limited seed availability.
期刊介绍:
Engineering in Agriculture, Environment and Food (EAEF) is devoted to the advancement and dissemination of scientific and technical knowledge concerning agricultural machinery, tillage, terramechanics, precision farming, agricultural instrumentation, sensors, bio-robotics, systems automation, processing of agricultural products and foods, quality evaluation and food safety, waste treatment and management, environmental control, energy utilization agricultural systems engineering, bio-informatics, computer simulation, computational mechanics, farm work systems and mechanized cropping. It is an international English E-journal published and distributed by the Asian Agricultural and Biological Engineering Association (AABEA). Authors should submit the manuscript file written by MS Word through a web site. The manuscript must be approved by the author''s organization prior to submission if required. Contact the societies which you belong to, if you have any question on manuscript submission or on the Journal EAEF.