Year-independent prediction of rice grain protein content using machine learning with agronomy-aligned multi-year field data.
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| Title: | Year-independent prediction of rice grain protein content using machine learning with agronomy-aligned multi-year field data. |
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| Authors: | Jung HJ; Winter Crop Research Division, National Institute of Crop and Food Science, Rural Development Administration, Wanju, Republic of Korea., Lee YH; Crop Production and Physiology Division, National Institute of Crop and Food Science, Rural Development Administration, Wanju, Republic of Korea., Lee C; Central-Northern Region Crop Research Center, National Institute of Crop and Food Science, Rural Development Administration, Suwon, Republic of Korea., Cho SW; Department of Smart Agro-Industry, Gyeongsang National University, Jinju, Republic of Korea., Hwang TY; Department of Crop Science, Chungbuk National University, Cheongju, Republic of Korea. |
| Source: | Frontiers in plant science [Front Plant Sci] 2026 Jun 01; Vol. 17, pp. 1818096. Date of Electronic Publication: 2026 Jun 01 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101568200 Publication Model: eCollection Cited Medium: Print ISSN: 1664-462X (Print) Linking ISSN: 1664462X NLM ISO Abbreviation: Front Plant Sci Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1664-462X |
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| DOI: | 10.3389/fpls.2026.1818096 |
