{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T13:49:06Z","timestamp":1772804946411,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,19]],"date-time":"2020-07-19T00:00:00Z","timestamp":1595116800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2016YFD0300604-4"],"award-info":[{"award-number":["2016YFD0300604-4"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41671438"],"award-info":[{"award-number":["41671438"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The objective of this study was to develop a low-cost method for rice growth information obtained quickly using digital images taken with smartphone. A new canopy parameter, namely, the canopy volume parameter (CVP), was proposed and developed for rice using the leaf area index (LAI) and plant height (PH). Among these parameters, the CVP was selected as an optimal parameter to characterize rice yields during the growth period. Rice canopy images were acquired with a smartphone. Image feature parameters were extracted, including the canopy cover (CC) and numerous vegetation indices (VIs), before and after image segmentation. A rice CVP prediction model in which the CC and VIs served as independent variables was established using a random forest (RF) regression algorithm. The results revealed the following. The CVP was better than the LAI and PH for predicting the final yield. And a CVP prediction model constructed according to a local modelling method for distinguishing different types of rice varieties was the most accurate (coefficient of determination (R2) = 0.92; root mean square error (RMSE) = 0.44). These findings indicate that digital images can be used to track the growth of crops over time and provide technical support for estimating rice yields.<\/jats:p>","DOI":"10.3390\/s20144011","type":"journal-article","created":{"date-parts":[[2020,7,20]],"date-time":"2020-07-20T10:59:38Z","timestamp":1595242778000},"page":"4011","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Estimation of a New Canopy Structure Parameter for Rice Using Smartphone Photography"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9237-6552","authenticated-orcid":false,"given":"Ziyang","family":"Yu","sequence":"first","affiliation":[{"name":"School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8551-0461","authenticated-orcid":false,"given":"Susan L.","family":"Ustin","sequence":"additional","affiliation":[{"name":"Center for Spatial Technologies and Remote Sensing (CSTARS), John Muir Institute of the Environment, University of California, Davis, CA 95616, USA"}]},{"given":"Zhongchen","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Agriculture, Northeast Agricultural University, Harbin 150030, China"}]},{"given":"Huanjun","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China"},{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}]},{"given":"Xinle","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China"}]},{"given":"Xiangtian","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China"}]},{"given":"Yang","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China"}]},{"given":"Haixiang","family":"Guan","sequence":"additional","affiliation":[{"name":"School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1799","DOI":"10.1111\/j.1365-3040.2012.02588.x","article-title":"Achieving yield gains in wheat","volume":"35","author":"Reynolds","year":"2012","journal-title":"Plant Cell Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1104\/pp.16.01585","article-title":"Diurnal solar energy conversion and photoprotection in rice canopies","volume":"173","author":"Meacham","year":"2017","journal-title":"Plant Physiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.fcr.2016.10.003","article-title":"Changes in light environment, morphology, growth and yield of soybean in maize-soybean intercropping systems","volume":"200","author":"Liu","year":"2017","journal-title":"Field Crops Res."},{"key":"ref_4","first-page":"140","article-title":"Estimating green LAI in four crops: Potential of determining optimal spectral bands for a universal algorithm","volume":"192\u2013193","author":"Peng","year":"2014","journal-title":"Agric. 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