Measurement of Single Soybean Seed Attributes by Near-Infrared Technologies. A Comparative Study
Measurement of Single Soybean Seed Attributes by Near-Infrared Technologies. A Comparative Study
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DOI：
10.1021/jf3012807
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发表时间：
2012-08-29
影响因子：
6.1
通讯作者：
Hurburgh, Charles R.
中科院分区：
文献类型：
--
作者：
Agelet, Lidia Esteve;Armstrong, Paul R.;Hurburgh, Charles R.
测试了四种近红外光谱仪及其相关的光谱采集方法;比较了三种大豆单粒属性：重量（g），蛋白质（96）和油（%）。采用偏最小二乘法（PIS）和四种预处理方法，显着最容易预测的属性是种子重量（RPD > 3的平均值）和蛋白质最少。所有仪器的性能各不相同。油和蛋白质预测的性能与仪器采样系统相关，最好的预测使用光谱从：一个以上的种子角度：这是促进种子旋转或翻滚在光谱收集过程中，而不是静态采样方法。从所使用的预处理方法来看，没有一种方法能给出最佳的整体性能，但重量测量通常更成功地使用原始光谱，而蛋白质和油的预测通常通过SNV和SNV +去趋势来增强。
Four near-infrared spectrophotometers, and their associated spectral Collection methods, were tested; an Compared for measuring three soybean single-seed attributes: Weight (g), protein (96), and oil (%). Using partial least-squares (PIS) and four preprocessing methods, the attribute that was significantly most easily predicted was seed weight (RPD > 3 on average) and protein the least. The performance of all instruments differed from each other. Performances for oil and protein predictions were correlated with the instrument sampling system, with the best predictions using spectra taken from: more than one seed angle: This was facilitated by the seed spinning or tumbling during spectral collection as opposed to static sampling methods. From the preprocessing methods utilized, no single one gave the best overall performances but weight Measurements were often more successful with raw spectra, whereas protein and oil predictions were often enhanced by SNV and SNV + detrending.