The food adulteration date centuries back today for gaining illegally benefits. Although the majority of adulterated foods do not pose a public health risk, exception related to the cause. The critical point behind adding substance in products are economical purposes to increase the apparent value of the products for reducing production cost for economic gain. It remains a concern among consumers for having fake product in the price of desired commodities or lower quality alternative. A range of conventional methods such as gas chromatography (GC) and, high-performance liquid chromatography (HPLC) are widely used applications for quality analysis of food products. However, these most widely used techniques are personal based, time-consuming, and chemical required. Therefore, food industry required a nondestructive, portable and non-chemical technique for rapid analysis of food products for quality and authenticity evaluation. For this purpose, spectroscopic techniques such as near-infrared, mid-infrared, and Raman spectroscopy have been in use from last several decades. Therefore, in this study, we investigated the potential of FT-NIR spectroscopic technique for authenticity analysis of almond powder which is one of the very common commodity to be adulterated with low prize apricot powder. Thus, the almond powder was adulterated with apricot powder in a concentration range between 0-50% with an interval of 5%. FT-NIR spectra of ten replicated for each concentration were collected and arranged in a matrix. To evaluate the natural relationship among the preprocessed data from different concentration groups, a principal component analysis (PCA) method was applied. As a result, PCA loadings show some important region where the differences lie between almond and apricot powder. Moreover, using the score values of first two principal components, the data can be separated according to their concentration value of apricot. Finally, a multivariate analysis method of partial least square regression (PLSR) was adopted to predict the concentration of apricot powder in almond powder by dividing the data into calibration and validation sets. The PLSR model developed with standard normal variate preprocessed spectra attain highest accuracy (R²_cal=0.997; SEC=0.8% and R²_val=0.991; SEP=1.1%) and lowest error. In addition, the beta coefficient obtained from PLSR model shows unique peaks related to the variation in apricot powder concentration among the different groups of samples. Further, for the reproducibility purpose, the developed model was tested with another variety of adulterated almond powder and similar results (R²>0.99 and SEC<1.8%) was yielded. The result demonstrated the ability of FT-NIR spectroscopy with chemo-metrics for quality analysis of apricot in almond powder.