基于插入式近红外光谱技术的酒醅理化指标在线检测系统应用OA

The traditional detection methods for the key physicochemical indicators(acidity,starch,and moisture)of fermented grains of strong-flavor(Nongxiangxing)Baijiu are lagging and cannot provide timely and effective guidance for production batching in the brewing workshop.Therefore,this study developed an online detection system based on insertion near-infrared spectroscopy for the brewing production line.The system integrated an anti-interference optical probe with automated actuators,and a full-spectrum partial least squares regression(PLSR)model was established by correlating real-time,in situ spectra of fermented grain samples collected from the hopper with reference values obtained by wet-chemical analysis.The results showed that the determination coefficients of the external validation set for the moisture,starch,and acidity prediction models of unloading fermented grains were 0.909,0.855,and 0.850,respectively,and the root mean square errors of cross-validation were 0.564%,0.453%,and 0.193 mmol/10 g,respectively.The external validation results showed that the prediction deviations for moisture,starch,and acidity were strictly controlled within the process tolerances of±1.0%,±1.5%,and±0.3 mmol/10 g,respectively,with root mean square errors of prediction of 0.61%,0.72%,and 0.21 mmol/10 g,respectively.In summary,the online detection system based on insertion near-infrared spectroscopy can be applied to the online detection of fermented grains,which enriched the detection means for fermented grains and provided key technical support for the intelligent upgrading of Baijiu brewing.