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A simple and nondestructive method for the analysis of soluble solid content in citrus was established using portable visible to near‐infrared spectroscopy (Vis/NIRS) in reflectance mode in combination with appropriate chemometric methods. The spectra were obtained directly by the portable Vis/NIRS without destroying samples. Outlier detection was performed by using leave‐one‐out cross‐validation (LOOCV) with the 3σ criterion, and the calibration models were established by partial least squares (PLS) algorithm. Besides, different data pretreatment methods were used to eliminate noise and background interference before calibration, to determine the one that will lead to better model accuracy. However, the correlation coefficients are all <0.62 and the results of all pretreatments are still unsatisfactory. Variable selection methods were discussed for improving the accuracy, and variable adaptive boosting partial least squares (VABPLS) method was used to get higher robustness models. The results show that standard normal variate (SNV) transformation is the best pretreatment method, while VABPLS can significantly simplify the calculation and improve the result even without pretreatment. The correlation coefficient of the best prediction models is 0.82, while the value is 0.48 for the raw data. The high performance shows the feasibility of portable Vis/NIRS technology combination with appropriate chemometric methods for the determination of citrus soluble solid content. [ABSTRACT FROM AUTHOR]

It is difficult to produce southern stinky tofu, a famous traditional Chinese snack, at industry scale due to the complex composition of its brine. In this study, the fingerprints of organic volatile flavor compounds in the southern stinky tofu brine samples from five manufacturers were studied using headspace solid‐phase microextraction/gas chromatography–mass spectrometry (HS‐SPME/GC‐MS) with the aid of chemometric methods. The fingerprints were obtained by HS‐SPME/GC‐MS and analyzed with the time shift alignment method, Shannon entropy, correlation coefficient, and principal component analysis. The results show that the time shifts in the samples can be accurately corrected by the time shift alignment method despite unexpected interferences. The fingerprint information was evaluated by Shannon entropy, while the similarities and differences in the fingerprints were investigated by correlation coefficient. Moreover, the identification of stinky tofu manufacturers can be achieved by principal component analysis. The predominant volatile compounds in southern stinky tofu brines were indole, 3‐methylindole, phenol, and 4‐methylphenol. Therefore, the established fingerprinting of volatile compounds for the brines by combining HS‐SPME/GC‐MS with chemometric methods was a simple and reliable method. The fingerprints of organic volatile flavor compounds in the southern stinky tofu brine samples from five manufacturers were obtained by HS‐SPME/GC‐MS and analyzed with the time shift alignment method, Shannon entropy, correlation coefficient, and principal component analysis. [ABSTRACT FROM AUTHOR]