Nondestructive Determination of Quality Management in Table Grapes using Near Infrared Spectroscopy (NIRS) Technique

C. Kanchanomai, D. Naphrom, S. Ohashi, K. Nakano, P. Theanjumpol, Phonkrit Maniwara
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引用次数: 5

Abstract

Near infrared spectroscopy (NIRS) is a potential technique for nondestructive fruit quality management. The qualities of table grapes (Vitis vinifera) as soluble solid content (SSC), pH-value, titratable acidity (TA), firmness and seedlessness are the key parameters for consumer decision. This research was focused on using NIRS for quality management in table grapes as nondestructive determination. The sample spectra were acquired by NIR spectrometer (NIRSystem 6500) on interactance mode with fiber optic probe in wavelength range of 800-1,100 nm. To develop the calibration model, the relationship between NIR spectral data and all measured properties of table grapes were studied using Partial Least Square Regression (PLSR). The results showed the best models were the positive determination in Savitzky-Golay derivative 2 of TSS, seedlessness and TA. There were coefficient of determination (R) of 0.980, 0.903 and 0.897, and standard error of calibration (SEC) of 0.430, 0.262 and 0.062, respectively. The full cross validation was analyzed, the standard error of cross validation (SECV) of 0.522, 0.570 and 0.103, and bias of -0.00272, 0.00205 and-0.00279, respectively. The R2cal and SEC of pH value of 0.632 and 0.352, and firmness of 0.661 and 0.685, respectively. Therefore, NIRS technique can be an efficiency nondestructive determination for quality management of table grapes in these key parameters.
近红外光谱(NIRS)技术无损检测鲜食葡萄的质量管理
近红外光谱(NIRS)是一种有潜力的水果无损品质管理技术。鲜食葡萄(Vitis vinifera)的可溶性固形物含量(SSC)、ph值、可滴定酸度(TA)、硬度和无籽性是消费者决定的关键参数。研究了近红外光谱无损检测在鲜食葡萄质量管理中的应用。采用近红外光谱仪(NIRSystem 6500)与光纤探针在800 ~ 1100 nm波长范围内相互作用模式获取样品光谱。为了建立校准模型,利用偏最小二乘回归(PLSR)研究了近红外光谱数据与鲜食葡萄所有测量特性之间的关系。结果表明,TSS、无籽性和TA的Savitzky-Golay衍生物2阳性测定是最佳模型。测定系数(R)分别为0.980、0.903和0.897,校正标准误差(SEC)分别为0.430、0.262和0.062。进行全交叉验证,交叉验证标准误差(SECV)分别为0.522、0.570和0.103,偏倚分别为-0.00272、0.00205和0.00279。pH值为0.632和0.352时,R2cal和SEC分别为0.661和0.685。因此,近红外光谱技术可作为鲜食葡萄质量管理中这些关键参数的高效无损检测方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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