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利用图像分析测量稻谷粒尺寸、垩白度及稻谷粒伸长率

Measurement of Rice Grain Dimensions and Chalkiness, and Rice Grain Elongation Using Image Analysis.

作者信息

Santos Marnol V, Cuevas Rosa Paula O, Sreenivasulu Nese, Molina Lilia

机构信息

International Rice Research Institute, Los Baños, Laguna, Philippines.

出版信息

Methods Mol Biol. 2019;1892:99-108. doi: 10.1007/978-1-4939-8914-0_6.

Abstract

Measurements of rice grain dimensions, percent grain chalkiness, and grain elongation used to be tedious and slow due to the manual nature of measurements (e.g., use of calipers to measure grains one at a time) and the subjective nature of scoring based on visual inspection (i.e., chalkiness). Recent developments in imaging technologies have enabled more high-throughput means for measuring physical traits (i.e., grain dimensions and chalkiness) in raw grains and grain elongation by comparing ratio between raw versus cooked rice. The digital images of rice grains are captured through computer scanning and analyzed using software that can calculate area and pixel value statistics of user-defined parameters. The improvements in throughput made possible by the use of imaging technologies will allow faster quality grading of rice varieties. Market quality is usually defined based on the rice grain physical traits (grain size and shape), degree of chalkiness, and the ability of rice to elongate on cooking. In this chapter, the routine methods to measure the physical traits of rice and grain elongation using image analysis are described.

摘要

由于测量工作的手工性质(例如,使用卡尺逐个测量谷粒)以及基于目视检查(即垩白度)评分的主观性,过去测量水稻谷粒尺寸、谷粒垩白率和谷粒伸长率既繁琐又缓慢。成像技术的最新发展使得通过比较生米与熟米之间的比例来测量原粮的物理特性(即谷粒尺寸和垩白度)以及谷粒伸长率有了更高通量的方法。通过计算机扫描获取水稻谷粒的数字图像,并使用能够计算用户定义参数的面积和像素值统计数据的软件进行分析。使用成像技术实现的通量提高将使水稻品种的质量分级更快。市场质量通常根据水稻谷粒的物理特性(谷粒大小和形状)、垩白度程度以及水稻在烹饪时的伸长能力来定义。在本章中,将描述使用图像分析测量水稻物理特性和谷粒伸长率的常规方法。

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