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Near-infrared diffuse reflectance for quantitative and qualitative measurement of soluble solids and firmness of delicious and Gala apples

机译:近红外漫反射率用于定量和定性测量美味和Gala苹果中的可溶性固形物和硬度

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Development of nondestructive measurements of soluble solids and firmness of apples benefits the producers, processors, and packers. The soluble solids and firmness (Magness-Taylor (MT) maximum force) of apples were predicted by diffuse reflectance measurement in the visibleear-infrared (400-1800 nm) regions of the spectrum. Two apple cultivars, Gala (n = 800) and Red Delicious (n = 960), were measured. The spectroscopic measurements of soluble solids and firmness for each apple were validated by a refractometer reading on the juice and a puncture test using a universal testing instrument, respectively. The soluble solids of apples could be predicted by NIR spectroscopic techniques with principal component regression (PCR) and Mahalanobis Distance (MD) analysis. The coefficients of determination (R-2) for predicting soluble solids were 0.934 (SEP = 0.279; 10 factors)for Gala and 0.966 (SEP = 0.341; 10 factors)for Red Delicious apples with an NIR spectrum range (800-1100 nm). For classifying Gala apples into three classes based on the soluble solids, MD classifiers had classification accuracies of 93.5% for the full spectrum range (400-1800 nm) and 95.5% for the partial NIR spectrum range (800-1100 nm). Similarly, for the classification of Red Delicious apples, the classification accuracies were 92.1% with the full spectrum (400-1800 nm) and 93.6% with the partial NIR spectrum (800-1100 nm). A spectroscopic technique for apple firmness measurements was feasible for the Delicious apple. Using PCR models, the R2 values for predicting MT firmness were 0.218 (SEP = 4.91; 16 factors) for Gala and 0.786 (SEP = 7.02; 24 factors) for Red Delicious apples with the full spectrum (400-1800 nm), while the R-2 values were only 0.291 (SEP = 4.92; 12 factors) for Gala and 0.657 for Red Delicious (SEP = 7.33; 24 factors) with the partial NIR spectrum (800-1100 nm). The MD analyses were also conducted to classify; apples firmness. Based on three classes, the classification accuracies were 82.5% with the full spectrum (4001800 nm) and 80% with the partial NIR spectrum (800-1100 nm) for Gala apples. Similarly, the classification accuracies were 83.8% with the full spectrum (400-1800 nm) and 75.3% with the partial NIR spectrum (800-1100 nm)for Red Delicious apples. This shows that spectroscopic techniques are feasible to classify apple firmness with over 80% accuracy.
机译:可溶性固形物和苹果硬度的非破坏性测量方法的开发使生产者,加工者和包装者受益。通过在光谱的可见/近红外(400-1800 nm)区域进行漫反射测量,可以预测苹果的可溶性固形物和硬度(Magness-Taylor(MT)最大力)。测量了两个苹果品种,即Gala(n = 800)和Red Delicious(n = 960)。每个苹果的可溶性固形物和硬度的光谱测量分别通过在果汁上的折光仪读数和使用通用测试仪的穿刺测试来验证。苹果的可溶性固形物可以通过近红外光谱技术通过主成分回归(PCR)和马氏距离(MD)分析来预测。预测可乐固体的测定系数(R-2)对于Gala为0.934(SEP = 0.279; 10个因子),对于具有NIR光谱范围(800-1100 nm)的红色美味苹果为0.966(SEP = 0.341; 10个因子) 。为了根据可溶固体将Gala苹果分为三类,MD分类器的全光谱范围(400-1800 nm)的分类精度为93.5%,部分NIR光谱范围(800-1100 nm)的分类精度为95.5%。同样,对于红色美味苹果的分类,全光谱(400-1800 nm)的分类准确度为92.1%,部分近红外光谱(800-1100 nm)的分类准确度为93.6%。一种用于苹果硬度测量的光谱技术对于美味苹果是可行的。使用PCR模型,全光谱(400-1800 nm)的Gala预测MT硬度的R2值为0.218(SEP = 4.91; 16个因子),红色美味苹果的R2值为0.786(SEP = 7.02; 24个因子),而带有部分NIR光谱(800-1100 nm)的Gala R-2值仅为0.291(SEP = 4.92; 12个因子)和Red Delicious(SEP = 7.33; 24因子)的0.657。 MD分析也进行了分类。苹果坚挺。基于三类,嘎拉苹果的全光谱(4001800 nm)分类准确度为82.5%,部分NIR光谱(800-1100 nm)分类准确度为80%。同样,红色美味苹果的全光谱(400-1800 nm)分类准确度为83.8%,部分NIR光谱(800-1100 nm)分类准确度为75.3%。这表明光谱技术可以以80%以上的准确度对苹果硬度进行分类。

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