{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T04:51:42Z","timestamp":1785819102806,"version":"3.56.0"},"reference-count":53,"publisher":"Cold Spring Harbor Laboratory","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cold Spring Harb Protoc"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:p>Grain quality is defined as the suitability of grain for a particular use. It is usually designated by chemical composition or physical properties of the grain. The ability to measure grain quality is important for identity preservation of specialty grain market classes, for development of new varieties with improved quality through breeding, and for basic scientific studies on the genetic or biochemical control of grain quality traits. This review introduces official methods for measuring maize compositional traits, including protein, starch, oil, amino acid, phytate, and phosphorus content. Additionally, we discuss two nonofficial methods: measuring phytate and available phosphorus levels, and assessing amino acid balance. Phytate and available phosphorous impact the mineral nutrition of grain, while amino acid balance reflects the value of grain as a protein source and the bioavailability of protein. We also describe the use of near-infrared spectroscopy (NIRS) to assess levels of various compounds in maize. NIRS relies on the fact that compounds with differing molecular properties uniquely interact with the near-infrared region (750\u20132500 nm) of the electromagnetic radiation spectrum, and thus, generate spectral information that can be used to develop calibration models\/equations for predicting the concentration of the compounds in grain samples. We discuss how sensitivity, accuracy, precision, throughput, and cost influence the choice of assay used to assess grain quality. Furthermore, we discuss how appropriate experimental design and data analysis can improve analytical outcomes when assessing grain quality.<\/jats:p>","DOI":"10.1101\/pdb.top108476","type":"journal-article","created":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T01:05:15Z","timestamp":1767056715000},"page":"pdb.top108476","source":"Crossref","is-referenced-by-count":2,"title":["Grain Quality in Maize"],"prefix":"10.1101","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8942-6961","authenticated-orcid":false,"given":"Anthony Assibi","family":"Mahama","sequence":"first","affiliation":[{"name":"Corn Insects and Crop Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Ames, Iowa 50011, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8765-8216","authenticated-orcid":false,"given":"Adrienne N.","family":"Moran Lauter","sequence":"additional","affiliation":[{"name":"Corn Insects and Crop Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Ames, Iowa 50011, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0479-4816","authenticated-orcid":false,"given":"M. Paul","family":"Scott","sequence":"additional","affiliation":[{"name":"Corn Insects and Crop Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Ames, Iowa 50011, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"246","published-online":{"date-parts":[[2025,12,29]]},"reference":[{"key":"2026080309050587000_2026.8.pdb.top108476.1","unstructured":"7 CFR Part 810 Subpart D. United States Standards for Corn. https:\/\/www.ecfr.gov\/current\/title-7\/part-810\/subpart-D"},{"key":"2026080309050587000_2026.8.pdb.top108476.2","unstructured":"AACC Approved Methods of Analysis 11th Ed. Method 76-11.01. Starch\u2014glucoamylase method with subsequent measurement of glucose with glucose oxidase. Cereals & Grains Association, St. Paul, MN. https:\/\/www.cerealsgrains.org\/resources\/Methods\/ [accessed July 24, 2024]."},{"key":"2026080309050587000_2026.8.pdb.top108476.3","unstructured":"AACC Approved Methods of Analysis 11th Ed. 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