The object of this study was to explore the potential for support vector machine (SVM) to improve the precision of predicting protein fractions by near infrared reflectance spectroscopy (NIRS). Generally, most protein fractions determined in Cornell Net Carbohydrate and Protein System (CNCPS), especially the neutral detergent insoluble protein (NDFCP) and acid detergent insoluble protein (ADFCP), could not be accurately predicted by the commonly used partial least squares (PLS) method. A recently developed chemometric method, SVM, was applied in NIRS prediction of alfalfa protein fractions in this study. Two hundred thirty alfalfa samples were scanned on a near infrared reflectance spectrophotometer, and analyzed for crude protein (CP), true protein precipitated in tungstic acid (TCP), borate-phosphate buffer-insoluble protein (BICP), NDFCP, and ADFCP. These 5 laboratory proteins and the CNCPS protein fractions A, B1, B2, B3, and C were predicted by NIRS using the PLS and SVM methods. According to PLS-NIRS regression, CP, TCP, BICP, A, and B2 obtained the determination coefficient of prediction (R(p)(2)) of 0.96, 0.91, 0.94, 0.94, and 0.93, and the ratios of standard deviation of prediction samples: standard error of prediction samples (RPD) values were 5.07, 3.31, 3.98, 3.96, and 3.91. Neutral detergent insoluble protein, ADFCP (fraction C), B1, and B3 were predicted with R(p)(2) of 0.75, 0.83, 0.30, and 0.62, and RPD values of 1.98, 2.42, 1.20, and 1.62; Calibrated by the SVM-NIRS method, R(p)(2) values of CP, TCP, BICP, NDFCP, ADFCP(C), A, and B2 achieved 0.99, 0.97, 0.97, 0.90, 0.93, 0.97, and 0.97, respectively. The RPD values of those fractions were 8.68, 8.26, 6.11, 3.08, 3.69, 5.97, and 5.81, respectively. The R(p)(2) and RPD values of fractions B1 and B3 were 2.67 and 0.87 (B1) and 2.51 and 0.75 (B3) directly predicted by SVM-NIRS model. In this study, the chemical analysis results of B1 and B3 were also correlated with calculated results from TCP-BICP and NDFCP-ADFCP, which were predicted by SVM-NIRS models. The B1 protein fraction achieved R(p)(2) and RPD values of 0.87 and 3.61, whereas values for B2 were 0.75 and 2.00. Data suggested that use of SVM methods in NIRS technology could improve the accuracy of predicting protein fractions. This study showed the potential of increasing the NIRS prediction accuracy to a level of practical use for all protein fractions, except B3.

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The key components of S. triqueter root exudates involved 4-oxo-pentanoic acid, succinic acid, glutaric acid, phthalate acid, citric acid, vanillic acid, myristic acid, pentadecanoic acid, decanoic acid, 14-methyl-pentadecanoic acid, hexadecanoic acid, octadecanoic acid and oleic acid, and the content of the water-soluble organic acids (citric acid, succinic acid and glutaric acid) significantly increased in pyrene and lead co-contaminated rhizosphere soil. These three water-soluble organic acids including citric acid, succinic acid and glutaric acid were detected as the specific root exudates of S. triqueter under stress of pollutants for pyrene and lead, so they were chosen as the research objects, and they were added into the bioremediation systems of pyrene and lead co-contaminated wetland soils. Compared with the control, the treatments added the three organic acids always improved the quantity of the bioavailable fraction of pyrene and lead in wetland soils and greatly influenced other chemical states of pyrene and lead fractions in the test concentration range. Under the 50 g kg -1 of organic acids concentration, the amount of the bioavailable fraction of pyrene and lead increased 41.0 and 872.7 % by citric acid, respectively. The enhancement of bioavailability of pyrene and lead in the wetland soil by adding organic acids generally decreased in the following order: citric acid [ succinic acid [ glutaric acid. Enhancing effects of organic acids on the bioavailability improvement of pyrene and lead is remarkable.

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