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Relationship between shelf-life and optical properties of 'Yuanhuang' pear in the region of 400-1150 nm

机译:400-1150 nm地区“元黄”梨子保质期与光学特性的关系

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The main goals of this study are to investigate the potential of absorption coefficient for the prediction of water contents in 'Yuanhuang' pear and analyze the relationship between the shelf-life and bulk optical properties in the range of 900-1050 nm. An automated integrating sphere (AIS) system was used to measure the total reflectance, total transmittance of pear flesh tissues in visible-Near infrared (Vis-NIR) range. These two measurements were used to estimate the absorption coefficient μ_a and reduced scattering coefficient μ'_s of pear samples by using an inverse adding doubling (IAD) light propagation model. The detection accuracy of the AIS system was verified by using both liquid (Intralipid-20% as scatterer) and solid phantom (TiO_2 as scatterer, carbon black as absorber). The relative error of measurement of μ'_s of liquid phantom with four different concentration (0.5%,l%,1.5%,2%) at 632.8 nm, 751 nm, 833 nm are less than 10% except for 2% concentration at 833 nm, and the relative error of measurement μ_a and μ'_s of solid phantom at 525.4 nm, 632.1 nm, 710.3 nm and 780.1 nm are less than 5% except for the μ_a at 525.4 nm. A total of 140 samples were used to conduct the moisture measurement, and drying method was used. Predictive models for moisture content from μ_a data were constructed using partial least squares regression (PLSR). The coefficient of correlation of calibration set (R_c) and validation set (R_p) were 0.50 and 0.45 respectively. The relationship between the shelf-life and optical properties was analyzed by dividing pear samples into three categories according to the actual shelf-life, and calculating classification accuracy by using actual and calculated shelf-life grade.
机译:本研究的主要目标是调查“元黄”梨中水含量预测的吸收系数的潜力,并分析了900-1050nm范围内的保质期和散装光学性能之间的关系。使用自动集成球(AIS)系统来测量可见近红外(Vis-NIR)范围中梨肉组织的总反射率,总透射率。通过使用逆添加倍增(IAD)光传播模型来估计这两个测量来估计吸收系数μ_a和降低散射系数μ'_的梨样品。通过使用液体(intralipid-20%作为散射剂)和固体幻影(TiO_2为散射体,炭黑作为吸收器)来验证AIS系统的检测精度。除了在833时,在632.8nm,751nm,833nm处的四种不同浓度(0.5%,1%,1.5%,2%)的μ'_液体体模的相对误差小于10%,除了833 NM,以及525.4nm,632.1nm,710.3nm和780.3nm处的固体幻像的测量μ_a和μ'_的相对误差小于5%,除了525.4nm。共使用140个样品进行水分测量,使用干燥方法。使用偏最小二乘回归(PLSR)构建来自μ_A数据的湿度含量的预测模型。校准集(R_C)和验证集(R_P)的相关系数分别为0.50和0.45。通过使用实际保质期将梨样品分为三类,通过使用实际和计算的保质期计算来分析保质期和光学性质之间的关系。

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