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首页> 外文期刊>Journal of Food Measurement and Characterization >Nondestructive moisture content determination of three different market type in-shell peanuts using near infrared reflectance spectroscopy.
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Nondestructive moisture content determination of three different market type in-shell peanuts using near infrared reflectance spectroscopy.

机译:使用近红外反射光谱法测定三种不同市场壳体花生的含水量。

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摘要

A near infrared reflectance (NIR) method is presented here by which the average moisture content (MC) of about 100 g of in-shell peanuts could be determined rapidly and nondestructively. MCs of three market type peanuts, Runners, Valencia and Virginia were determined by this method while the peanuts were in their shells (in-shell peanuts). The MC range of the peanuts tested was between 6 and 26%. NIR reflectance measurements were made at 1 nm intervals in the wavelength range of 1,000-1,800 nm and the spectral data was modeled using partial least squares regression analysis. Eight different models were developed by utilizing different data preprocessing methods such as, Norris-Gap first derivative with a gap size of 3, peak normalization with 1,680 nm (which is the no absorbance wavelength for water), and transformation from reflectance to absorption. Applying model fitness measures, a suitable model was selected out of these. Predicted values of the samples tested were compared with the values determined by the standard air-oven method. The predicted values agreed well with the air-oven values with an R2 value better than 0.93 for all three types of in-shell peanuts. This method being rapid, nondestructive, and non contact, may be suitable for measuring and monitoring MCs of different types of peanuts, while they are in their shells itself, in the peanut industry.
机译:这里给出了近红外反射率(NIR)方法,通过该方法,其可以快速和无损地确定约100g壳体花生的平均水分含量(MC)。三个市场类型花生,跑步者,瓦伦西亚和弗吉尼亚的MCS由这种方法决定,而花生在他们的壳中(壳牌花生)。测试的花生的MC系列在6%至26%之间。在1,000-1,800nm的波长范围内以1nm间隔进行NIR反射测量,并且使用偏最小二乘回归分析进行频谱数据。通过利用不同的数据预处理方法,诸如Norris-Gap首先衍生物的八种不同的数据预处理方法而开发了八种不同的型号,峰值归一化与1,680nm(其是水的吸光度波长),以及从反射率的变化。应用模型健身措施,其中选择了合适的模型。将测试的样品的预测值与由标准空气烘箱方法确定的值进行比较。预测值与空气烤箱值相同,R2值优于0.93,适用于所有三种壳体花生。这种方法快速,无损和非接触,可能适用于测量和监测不同类型的花生的MCS,而在花生行业中它们在其壳体中。

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