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利用图像分析准确预测高粱籽粒的营养价值。

Accurate prediction of nutritional value of sorghum grain using image analysis.

作者信息

Ebadi M R, Sedghi M, Akbari Moghaddam Kakhki R

机构信息

a Animal Science Research Department , Isfahan Agricultural and Natural Resources Research and Education Centre, AREEO , Isfahan , Iran.

b Department of Animal Sciences, College of Agriculture , Isfahan University of Technology , Isfahan , Iran.

出版信息

Br Poult Sci. 2019 Apr;60(2):154-160. doi: 10.1080/00071668.2018.1562157. Epub 2019 Feb 1.

Abstract
  1. This study evaluated the application of L (lightness)a (redness) and b (blueness) colour analysis and chemical compositions to predict the nutritional value of sorghum grain. 2. A total of 12 varieties of sorghum grain were analysed for Lab colours, chemical composition, energy and total and digestible amino acid content. Regression models based on the linear, non-linear and the interaction effects of inputs were applied to predict the nutritional value of sorghum grains either using Lab colour or chemical composition, as the model inputs. 3. The results illustrated a significant relationship between ab and/or chemical compositions with energy content in the samples of sorghum grain. The provided estimation equations presented high goodness of fit in terms of R ranging from 0.744 to 0.999. 4. Total and digestible amino acids of sorghum grain were estimated based on ab and chemical compositions data with the goodness of fit ranging from 0.641 to 0.999 (R). 5. In conclusion, the Lab colour analysis may be used for developing equations to predict nutritional value of sorghum grain as an alternative approach to the conventional time-consuming and costly chemical and bioassay methods.
摘要
  1. 本研究评估了L(亮度)a(红色度)和b(蓝色度)颜色分析及化学成分在预测高粱籽粒营养价值方面的应用。2. 对12个高粱籽粒品种进行了Lab颜色、化学成分、能量以及总氨基酸和可消化氨基酸含量的分析。基于输入变量的线性、非线性和交互效应构建回归模型,分别以Lab颜色或化学成分作为模型输入来预测高粱籽粒的营养价值。3. 结果表明,高粱籽粒样品中ab和/或化学成分与能量含量之间存在显著关系。所提供的估计方程在R值方面显示出较高的拟合优度,范围从0.744至0.999。4. 根据ab和化学成分数据估算高粱籽粒的总氨基酸和可消化氨基酸,拟合优度范围为0.641至0.999(R)。5. 总之,Lab颜色分析可用于开发预测高粱籽粒营养价值的方程,作为传统耗时且昂贵的化学和生物测定方法的替代方法。

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