{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T20:20:57Z","timestamp":1782246057309,"version":"3.54.5"},"reference-count":44,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T00:00:00Z","timestamp":1600992000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31960487; 11604154"],"award-info":[{"award-number":["31960487; 11604154"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20181315"],"award-info":[{"award-number":["BK20181315"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Yangzhou Key R&amp;D Program (Modern Agriculture)","award":["YZ2018038"],"award-info":[{"award-number":["YZ2018038"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Scattering hyperspectral technology is a nondestructive testing method with many advantages. Here, we propose a method to improve the accuracy of egg freshness, research the influence of incident angles of light source on the accuracy, and explain its mechanism. A variety of weak classifiers classify eggs based on the spectra after preprocessing and feature wavelength extraction to obtain three classifiers with the highest accuracy. The three classifiers are used as metamodels of stacking ensemble learning to improve the highest accuracy from 96.25% to 100%. Moreover, the highest accuracy of scattering, reflection, transmission, and mixed hyperspectral of eggs are 100.00%, 88.75%, 95.00%, and 96.25%, respectively, indicating that the scattering hyperspectral for egg freshness detection is better than that of the others. In addition, the accuracy is inversely proportional to the angle of incidence, i.e., the smaller the incident angle, the camera collects a larger proportion of scattering light, which contains more biochemical parameters of an egg than that of reflection and transmission. These results are very important for improving the accuracy of non-destructive testing and for selecting the incident angle of a light source, and they have potential applications for online non-destructive testing.<\/jats:p>","DOI":"10.3390\/s20195484","type":"journal-article","created":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T01:39:33Z","timestamp":1600997973000},"page":"5484","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Nondestructive Detection for Egg Freshness Based on Hyperspectral Scattering Image Combined with Ensemble Learning"],"prefix":"10.3390","volume":"20","author":[{"given":"Dejian","family":"Dai","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China"},{"name":"Jiangsu Province Engineering Laboratory of Modern Facility Agriculture Technology and Equipment, Nanjing 210031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China"},{"name":"Jiangsu Province Engineering Laboratory of Modern Facility Agriculture Technology and Equipment, Nanjing 210031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Xiu","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1016\/j.compag.2018.12.012","article-title":"Maintaining the predictive abilities of egg freshness models on new variety based on VIS-NIR spectroscopy technique","volume":"156","author":"Dong","year":"2019","journal-title":"Comput. 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