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你说的都有一些专业术语，可能翻译不好，不好意思哈。
Rapid Detection of Soybean Near-Infrared
Abstract: The fatty acid is an important indicator to measure the quality of soybean. Near-Infrared spectroscopy combined with chemometrics methods to establish the value of soybean fatty acid sample calibration equation, and the calibration equation was validated, optimized value of soybean fatty acid calibration equation, interactive calibration coefficient of determination (1-VR) to 0.948 2, the external validation coefficient of determination (R2) was 0.915 0 and standard deviation of calibration (SEC) to 1.205 8, the standard deviation of cross-validation (SECV) to 1.591 2, existing data predict the standard deviation (SEP) was 1.395. External verification, that this method can be applied to the actual test. Established based on the FOSS XDS Rapid Determination of Near Infrared Spectroscopy of soybean moisture content model and mathematical treatment of the optical processing means and so the impact on the model discussed, the model of internal and external verification. Experimental results show that the best model parameters: the normalization of the optical processing used standard treatment (SNV Only), mathematical processing methods used 1.4.4.1, soybean moisture calibration equation interactive calibration coefficient of determination (1 1 vR ) is 0.990 8, calibration coefficient of determination (R) 0.993 9, the standard error of calibration (SEC) 0.096 7, interactive calibration standard error (SECV) was 0.127 3, the existing data Standard errors of prediction (SEP) was 0.136. The model was tested on soybean moisture content, reached the place of the requirements of conventional standard method can be applied to rapid detection.
Keywords: Near infrared spectroscopy; soybean; water; fatty acid value

完全人译

Abstract: The fatty acid value is an important indicator to measure the quality of soybean. This paper tried to combine the near-Infrared spectroscopy technology with the chemometrics methods to establish a calibration equation of the fatty acid value of the soybean sample, and obtaied a optimized calibration equation of the value of fatty acid of soybean by validating the calibration equation. The interactive calibration determination coefficient (1-VR) is 0.948 2, the external validation determination coefficient (R2) is 0.915 0, the standard error calibration (SEC) is 1.205 8, the standard error of cross validation (SECV) is 1.591 2, and the existing data of standard error of predict (SEP) is 1.395.

It shows that the methods can be applied in a practical testng by external verification. This paper also established a soybean moisture content model based on the FOSS XDS rapid determination of near infrared spectroscopy instrument, and discussed the effections on the model both from the factors of mathematical treatment and optical treatment and so on, and proceeded internal and external verification to the model. The experiment results showed that the best model parameters are: to chose the standard treatment in a optical processing (SNV Only), to chose methods of 1.4.4.1 in a mathematical processing, the interactive calibration coefficient of determination of soybean moisture calibration equation (1 1 vR ) is 0.990 8, the calibration coefficient of determination (R) is 0.993 9, the standard error of calibration (SEC) is 0.096 7, the interactive calibration standard error (SECV) is 0.127 3, the existing data Standard errors of prediction (SEP) is 0.136.

A substitution of the conventional standard methods can be reached by applying this model to test the soybean moisture content and applied in a rapid detection.

Keywords: near infrared spectroscopy; soybean; moisture content; fatty acid value

建议分段，可显得眉目清晰

Abstract: The fatty acid is an important indicator to measure the quality of soybean. Near-Infrared spectroscopy combined with chemometrics methods to establish the value of soybean fatty acid sample calibration equation, and the calibration equation is validated, the optimized value of soybean fatty acid calibration equation, interactive calibration coefficient of determination (1-VR) to 0.948 2, the external validation coefficient of determination (R2) was 0.915 0 and standard deviation of calibration (SEC) to 1.205 8, the standard deviation of cross-validation (SECV) to 1.591 2, existing data predict the standard deviation (SEP) was 1.395. External verification, that this method can be applied to the actual test.
Established based on the FOSS XDS Rapid Determination of Near Infrared Spectroscopy of soybean moisture content model and mathematical treatment of the optical processing means and so the impact on the model discussed, the model of internal and external verification. Experimental results show that the best model parameters: the normalization of the optical processing used standard treatment (SNV Only), mathematical processing methods used 1.4.4.1, soybean moisture calibration equation interactive calibration coefficient of determination (1 1 vR ) is 0.990 8, calibration coefficient of determination (R) 0.993 9, the standard error of calibration (SEC) 0.096 7, interactive calibration standard error (S
ECV) was 0.127 3, existing data predict the standard deviation (SEP) was 0.136. The model was tested on soybean moisture content, reached the place of the requirements of conventional standard method can be applied to rapid detection.
Keywords: Near infrared spectroscopy; soybean; water; fatty acid value

就是这些、没错了

Fatty acid value is an important measure of soybean quality indicators. Nearly infrared spectroscopy technology and chemical measurement method, the calibration of soybean sample fatty acid values, and the calibration equation equation, optimized verifies the calibration of soybean fatty acid values, interactive correction coefficient equation of decision (1-0) for the VR] 94.8 2, external validation decision factor (R2) to 0 0, calibration standard deviation 915 (SEC) for 1 August 205, cross validation SECV) for the standard deviation of (1) 2, the existing data to predict ecol.model. SEP standard deviation for 1 395. Through the external validation, shows that this method can also be applied to practical test. FOSS is established based on XDS near-infrared spectrum analyzer rapid determination of moisture content of soybean processing and optical model, learn to handle means the influence factors such as model, probes into the internal and external model validation. Experimental results show that the optimal parameters for the building mode selection standards, optical treatment normalization SNV (number), how to learn 1.4.4.1 selection method, with the interaction of soybean moisture calibration equations (1 a decisive coefficients calibration for 0.990 8 vR, calibration decision (R) for 0.993 coefficient of 9, calibration error (SEC), interactive calibration for 0.67ka 7 standard error (SECV) for 0.127 3, the existing data (SEP) to predict the standard deviation of 0.136 for. Use this mode of soybean moisture content, reached the standard method instead of conventional requirements and can be used in the rapid detection.
Keywords: near infrared spectrum, Soybean, Moisture. Fatty acid values

Title: The study of rapid detection of soybean by Near Infrared Spectrum(NIR)

Abstract: Fatty acid value is an important indicator to measure the quality of soybean. The sample calibration equation of soybean fatty acid value was established by combining Near Infrared Spectrum with chemometrics method, and the equation was validated and optimized. The interactive calibration coefficient (1-VR) was 0.9482, and the external validation coefficient (R2) was 0.9150. The standard deviation of calibration (SEC) was 1.2058, and the standard deviation of cross-validation (SECV) was 1.5912. The standard deviation (SEP) was predicted to 1.395 by currently available data. External verification indicated that the method can be applied to the fact detect.
Based on the FOSS XDS Rapid Determination by NIR, the mathematical model of soybean moisture content was established. The effect of optical processing and mathematical treatment to the model were discussed and studied, and the internal and external verification of the model were also performed. the optimal model parameters obtainde by experimental results were described as following: to select the standard treatment in a optical processing (SNV Only), to select methods of 1.4.4.1 in a mathematical processing, the interactive calibration coefficient of determination of soybean moisture calibration equation (1 1 vR ) was 0.9908, the calibration coefficient of determination (R) was 0.9939, the standard error of calibration (SEC) was 0.0967, the interactive calibration standard error (SECV) was 0.1273. Existing data had showed that the standard deviation (SEP) was 0.136. The established model was applied to the determination of soybean moisture content, and the results had reached the the requirements of replacing conventional standard, indicating that the method could be applied to the rapid detection.

Keywords: NIR (Near Infrared Spectrum); soybean; moisture content; fatty acid value

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