{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,10]],"date-time":"2026-11-10T23:46:03Z","timestamp":1794354363329,"version":"4.9.0"},"reference-count":40,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T00:00:00Z","timestamp":1786147200000},"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":"crossref","award":["82404814"],"award-info":[{"award-number":["82404814"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["82404863"],"award-info":[{"award-number":["82404863"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"award":["82404814"],"award-info":[{"award-number":["82404814"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"award":["82404863"],"award-info":[{"award-number":["82404863"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Key Project at the Central Government Level, \u201cThe Ability Establishment of Sustainable Use for Valuable Chinese Medicine Resources\u201d","award":["2060302"],"award-info":[{"award-number":["2060302"]}]},{"name":"Postgraduate Research and Practice Innovation Program of Jiangsu Province","award":["KYCX25_1000"],"award-info":[{"award-number":["KYCX25_1000"]}]},{"name":"National Administration of Traditional Chinese Medicine High-level Key Discipline Construction Project","award":["zyyzdxk-2023293"],"award-info":[{"award-number":["zyyzdxk-2023293"]}]},{"name":"Start-up Research Fund of Nanjing Agricultural University","award":["130-804141"],"award-info":[{"award-number":["130-804141"]}]},{"name":"Open Funding of the State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture","award":["SKL2024Z0203"],"award-info":[{"award-number":["SKL2024Z0203"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Foods"],"abstract":"<jats:p>Chinese wolfberry (CW) is a medicinal-food homologous fruit. Key mineral elements are important indicators of the nutritional quality and geographical authenticity of CW. Rapid and non-destructive evaluation of key mineral elements remains challenging because inductively coupled plasma mass spectrometry (ICP-MS) is accurate but destructive and laboratory-dependent. In this study, 120 CW batches from Ningxia, Qinghai, Gansu, and Xinjiang were analyzed by combining ICP-MS reference measurements of Cu, Fe, Mn, and Zn with standardized RGB image features. Visible-color proxy curves were reconstructed from RGB\/L*a*b* information and Gaussian fitting, and frequency-domain texture descriptors were extracted from Fourier-derived angle\u2013energy curves. Multivariate analysis showed that mineral profiles, the 570\u2013593 nm visible-color proxy band, and the 0\u201340\u00b0 and 63\u2013140\u00b0 texture-angle ranges contributed to regional differentiation. A Dung Beetle Optimizer-radial basis function (DBO-RBF) regression model was then used for internal prediction of mineral element contents and compared with nine baseline regression algorithms. DBO-RBF achieved test-set R2 values of 0.949, 0.965, 0.951, and 0.913 for Cu, Fe, Mn, and Zn, respectively, with corresponding test RPD values of 2.9017, 3.2419, 3.0175, and 2.8416. These results indicate that image-derived visible-color and texture features can provide useful screening information for mineral quality assessment in CW, offering a rapid, low-cost, and non-destructive approach for preliminary batch evaluation.<\/jats:p>","DOI":"10.3390\/foods15162786","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T01:20:03Z","timestamp":1786324803000},"page":"2786","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Visible-Spectrum Proxy and Texture Features Coupled with Optimized Regression for Predicting Key Minerals in Chinese Wolfberry"],"prefix":"10.3390","volume":"15","author":[{"given":"Peng","family":"Chen","sequence":"first","affiliation":[{"name":"College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rao","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linjing","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6114-9747","authenticated-orcid":false,"given":"Ke","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xialin","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuwen","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5475-3863","authenticated-orcid":false,"given":"Peina","family":"Zhou","sequence":"additional","affiliation":[{"name":"Institute of Plant Resources and Chemistry, Nanjing Research Institute for Comprehensive Utilization of Wild Plants, Nanjing 210042, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9575-0204","authenticated-orcid":false,"given":"Chenghao","family":"Fei","sequence":"additional","affiliation":[{"name":"College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China"},{"name":"State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Beijing 100700, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"145863","DOI":"10.1016\/j.foodchem.2025.145863","article-title":"Near-infrared spectroscopy coupled with machine learning algorithms based on L1-norm and L21-norm to identify the geographical origins of Chinese wolfberry","volume":"493","author":"Zhu","year":"2025","journal-title":"Food Chem."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Cui, J., Li, K., Hao, J., Dong, F., Wang, S., Rodas-Gonz\u00e1lez, A., Zhang, Z., Li, H., and Wu, K. 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