Use of objective imaging systems to assess subjective grain appearance traits important to the US rice industry

Abstract

Background and objectives Milled rice grain appearance traits, including chalk, determine its grade, price, and marketability. These appearance traits are evaluated visually (VI) in the United States by officially trained inspectors and at commercial mills. Digital imaging systems (IS) provide an alternative means to objectively and rapidly measure these traits. The goals of this study were to compare chalk values determined by VI and IS and to identify IS parameters that are associated with the five grain appearance traits commonly assessed by the US rice industry. Findings Milled rice chalk determined by three VI methods used by commercial mills, a rice export company, and government inspectors, and three IS, WinSeedle, SeedCount, and S21, differed significantly. However, all six methods agreed on ranking of the best and worst of 20 US cultivars for chalkiness. Multiple linear regression analyses identified quality parameters from each IS that are associated with—bran streaks, chalk, kernel color, uniformity length, and appearance overall as determined by commercial mills. Conclusions IS can rapidly quantify rice grain appearance traits but agree with subjective ratings for chalkiness only when differences are extreme. Subjective grain appearance traits as determined by commercial mills appear to be based on several parameters detected by IS. Significance and novelty IS demonstrated that discolored kernels and grain chalkiness are the major factors explaining differences in overall appearance of US long‐grain varieties as subjectively assessed by commercial mills.

Effects of alternate wetting and drying irrigation management and air temperature during grainfill on rice grain physicochemical and functionality traits of US inbred varieties

“…The 100‐kernel wt was an average of two subsamples per experimental unit. Chalkiness was determined using WinSeedle (Regent Instruments Canada Inc.) and is expressed as % chalk area over the total kernel area (Eizenga et al., 2019; McClung et al., 2019).…”

“…Thus far, AWD irrigation management has been primarily focused on grain yield, while the impact of AWD on grain quality, a crucial factor affecting the crop value and edible portion of rice, is not well understood (Graham‐Acquaah et al., 2019; McClung et al., 2019; Zhao & Fitzgerald, 2013). Rice grain quality is complex, and it includes several component traits–grain physical and appearance traits including chalkiness, sensory traits, and functional properties.…”

“…US rice farmers have shown interest in adopting AWD irrigation management systems in commercial rice fields (McClung et al., 2020). Rice produced in the USA is for both domestic and export markets, and to remain competitive, US rice needs to maintain premium grain quality (McClung et al., 2019). A better understanding of the effect of AWD management on grain quality characteristics of US varieties under varying air temperatures is needed.…”

A mobile phone digital image method designed for efficient durum wheat flour characterization

“…This scheme has been applied in the evaluation of the appearance of cereal grains. 12 The detection and counting of pulse pests in digital images with the ImageJ soware has also been published. 13 In line with the aforementioned publications, this work proposes a fast efficient method of digital image analysis that allows the counting of particles in a semi-automatic way with the image processing platform Fiji, a variant of the ImageJ soware.…”

“…This scheme has been applied in the evaluation of the appearance of cereal grains. 12 The detection and counting of pulse pests in digital images with the ImageJ software has also been published. 13…”