Analysis of moisture, oil, and fatty acid composition of olives by near‐infrared spectroscopy: development and validation calibration models

BACKGROUND Olive is a new, expanding crop in Georgia. Its oil content steadily increases with maturity, but eventually plateaus at the maximum when the olives should be promptly harvested, avoiding overripening and quality degradation. This requires frequent testing. However, olive quality analysis by wet chemistry is laborious, slow and costly, whereas near‐infrared reflectance spectroscopy (NIRS), being precise, accurate, rapid and cheap, could be suitable. We developed and validated NIRS calibration models for moisture, fresh‐matter‐oil (oil‐FMO), dry‐matter‐oil (oil‐DMO) and major fatty acid composition analyses. RESULTS Of the12 models developed, seven constituents – moisture, oil‐FMO, oil‐DMO, and palmitic, palmitoleic, oleic and linoleic acids (representing 88–97% of the total fatty acids) had low standard errors and high coefficients of determination ( R 2 = 0.81–0.98; 1 − VR = 0.74–0.86) for both calibration and cross‐validation. For these seven constituents, predictions of an independent validation set yielded excellent agreement between the NIRS predicted values and the reference values with low standard error of prediction (SEP), low bias, high coefficient of determination ( r 2 = 0.80–0.93) and high ratios of performance to deviation (RPD = SD/SEP; 2.21–3.85). CONCLUSION Precise, accurate and rapid analysis of fresh olives for moisture, oil and major fatty acid composition can be done at a low cost using NIRS, meeting the analytical needs of the industry.