{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T23:05:25Z","timestamp":1778886325213,"version":"3.51.4"},"reference-count":32,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Program of science and technology at Universities of Inner Mongolia Autonomous Region","award":["NJZZ23047"],"award-info":[{"award-number":["NJZZ23047"]}]},{"name":"Research Program of science and technology at Universities of Inner Mongolia Autonomous Region","award":["BR230154"],"award-info":[{"award-number":["BR230154"]}]},{"name":"Program for improving the Scientific Research Ability of Youth Teachers of Inner Mongolia Agricultural University","award":["NJZZ23047"],"award-info":[{"award-number":["NJZZ23047"]}]},{"name":"Program for improving the Scientific Research Ability of Youth Teachers of Inner Mongolia Agricultural University","award":["BR230154"],"award-info":[{"award-number":["BR230154"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Moisture content is an important parameter for estimating the quality of pellet feed, which is vital in nutrition, storage, and taste. The ranges of moisture content serve as an index for factors such as safe storage and nutrition stability. A rapid and non-destructive model for the measurement of moisture content in pellet feed was developed. To achieve this, 144 samples of Caragana korshinskii pellet feed from various regions in Inner Mongolia Autonomous Region underwent separate moisture content control, measurement using standard methods, and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 935.5\u20132539 nm. The Monte Carlo cross validation (MCCV) was used to eliminate abnormal sample data from the spectral data for better model accuracy, and a global model of moisture content was built by using partial least squares regression (PLSR) with seven preprocessing techniques and two spectral feature extraction techniques. The results showed that the regression model developed by PLSR based on second derivative (SD) and competitive adaptive reweighted sampling (CARS) resulted in better performance for moisture content. The model showed predictive abilities for moisture content with a coefficient of determination of 0.9075 and a root mean square error (RMSE) of 0.4828 for the training set; and a coefficient of determination of 0.907 and a root mean square error (RMSE) of 0.5267 for the test set; and a relative prediction error of 3.3 and the standard error of 0.307.<\/jats:p>","DOI":"10.3390\/s23177592","type":"journal-article","created":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T09:12:22Z","timestamp":1693559542000},"page":"7592","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Rapid and Non-Destructive Estimation of Moisture Content in Caragana Korshinskii Pellet Feed Using Hyperspectral Imaging"],"prefix":"10.3390","volume":"23","author":[{"given":"Zhihong","family":"Yu","sequence":"first","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaochao","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5797-475X","authenticated-orcid":false,"given":"Jianchao","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Su","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9591-8505","authenticated-orcid":false,"given":"Wenhang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,1]]},"reference":[{"key":"ref_1","first-page":"154","article-title":"Feeding value of caragana korshinskii and its effect on ruminant production and economic efficiency","volume":"44","author":"Wang","year":"2021","journal-title":"Feed Res."},{"key":"ref_2","first-page":"95","article-title":"Nutrient composition analysis of feeding caragana korshinskii pellet feed and its effect on beef cattle fattening","volume":"21","author":"Chen","year":"2014","journal-title":"HLJPAAV"},{"key":"ref_3","first-page":"37","article-title":"A study on the establishment of near-infrared rapid analysis model for nutrient composition of alfalfa based on different pretreatment methods","volume":"42","author":"Rong","year":"2021","journal-title":"J. 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