Quantification of quality parameters in castanhola fruits by NIRS for the development of prediction models using PLS and variable selection algorithms on a laboratory scale

This paper proposes a novel methodology for the quantification of total phenolic compounds (TPCs) and total anthocyanin compounds (TACs) in castanhola fruits ( Terminalia catappa Linn ), using near infrared spectroscopy (NIRS) coupled with variable selection algorithms, such as interval partial least squares (iPLS) and genetic algorithm-partial least squares (GA-PLS). GA-PLS showed the best results in the prediction of both parameters. TPC parameters, R p 2 = 0.82, RMSEP = 11.3 mg GAE g −1 (mg gallic acid equivalents (GAE) per g sample), SEL 16.70 mg GAE g −1 , RPD = 2.89, sensibility 2.19 × 10 −7 , and selectivity 0.048 were also obtained using first derivative (5 points) and MSC pretreatment. TAC parameters, R p 2 = 0.80, RMSEP = 8.70 mg L −1 , SEL 6.93 mg L −1 , RPD = 1.90, sensibility 6.73 × 10 −6 and selectivity 0.07 were attained using second derivative (11 points) pre-treatment. From these findings, it can be concluded that NIRS coupled GA-PLS can be used as a non-destructive technique for determining TACs and TPCs in intact castanhola fruits. This paper proposes a novel methodology for the quantification of total phenolic compounds (TPCs) and total anthocyanin compounds (TACs) in castanhola fruits.