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首页> 外文期刊>Computers and Electronics in Agriculture >Purity analysis of multi-grain rice seeds with non-destructive visible and near-infrared spectroscopy
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Purity analysis of multi-grain rice seeds with non-destructive visible and near-infrared spectroscopy

机译：具有非破坏性可见和近红外光谱的多粒稻种纯度分析

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摘要

Seed purity is a crucial indicator of seed breeding, production and circulation. The traditional purity analysis methods are based on the authenticity identification of single-seed, which are complex, time consuming and lowly efficient. Using visible and near-infrared (Vis-NIR) spectroscopy, a novel purity analysis method of multi-grain rice seeds was developed. The samples were mixed samples that the target variety (Y Liangyou 900) was contaminated by the other four varieties. The standard normal variate method was used for spectral pretreatment. The equidistant combination-partial least squares (EC-PLS) was adopted for large-range wavelength screening. The wavelength step-by-step phase-out PLS (WSP-PLS) was further used to eliminate interference wavelengths and improve predicted effect. In vis-short NIR region, the selected WSP-PLS model included 19 non-equidistant wavelengths. The root mean square errors and correlation coefficients for prediction in modeling (RMSEPM, R-P,R-M) reached 0.115, 0.920, respectively. In validation, the root mean square errors and correlation coefficients for prediction (RMSEPV, R-P,R-V) were 0.152, 0.845, respectively. In the long NIR region, the selected model included 24 non-equidistant wavelengths, the RMSEPM, R-P,R-M were 0.103, 0.930 and the RMSEPV, R-P,R-V were 0.129, 0.894, respectively. Results showed that the predicted and actual purity values had high correlation, and the wavelength model complexity was low. The proposed Vis-NIR detection method has the feasibility to analyse the purity of multi-grain rice seeds, which is a rapid, non-destructive and promising analytical technique. As a simple and efficient wavelength selection method, WSP-PLS is expected to be used for more analysis objects.
机译：种子纯度是种子育种，生产和循环的关键指标。传统的纯度分析方法基于单种子的真实性识别，这是复杂，耗时和低效率的。使用可见和近红外（Vis-NIR）光谱，开发了一种多粒米种子的新型纯度分析方法。将样品混合样品，即目标品种（Y Liangyou 900）被其他四种品种污染。标准正常变化方法用于光谱预处理。采用等距离组合部分最小二乘（EC-PLS）用于大型波长筛选。逐步逐步淘汰PLS（WSP-PLS）还用于消除干扰波长并改善预测效果。在Vis-Short NIR区域中，所选择的WSP-PLS模型包括19个非等距波长。用于建模（RMSEPM，R-P，R-M）预测的根均方误差和相关系数分别达到0.115,0.920。在验证中，预测（RMSEPV，R-P，R-V）的根均方误差和相关系数分别为0.152,0.845。在长NIR区域中，所选择的模型包括24个非等距波长，RMSEPM，R-P，R-M为0.103,0.930和RMSEPV，R-P，R-V分别为0.129,0.894。结果表明，预测和实际纯度值相关性高，波长模型复杂性低。所提出的Vis-NIR检测方法具有分析多粒稻种纯度的可行性，这是一种快速，无损和有前途的分析技术。作为一种简单且有效的波长选择方法，预计WSP-PLS将用于更多的分析对象。

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