Rapid and cost-effective assessment of nutrients in pistachio (Pistacia vera L.) leaves through Fourier transform near-infrared spectroscopy (FT-NIRS)

Background: Pistachio nuts provide many health benefits in human diet. Nutrient levels in plant leaves and fertilizer schedules are determined based on traditional soil and leaf chemical analyses. However, these methods require additional labor, time, and cost, which is why most farmers do not prefer them and cannot detect nutrient deficiencies in time. Fast, easy-to-use and low-cost nutrient level assessment techniques are needed. AimThis study aims to explore the viability of near-infrared reflectance spectroscopy (NIRS) as a fast, user friendly, and cost effective technique for evluating the major macro- and micronutrient contents of dried and ground pistachio leaf sample. Methods: The feasibility of NIRS for estimating nutrient contents was investigated by analyzing samples from 200 pistachio trees. Dried and ground pistachio leaves were subjected to NIRS analysis. PLSR (Partial least square regression) analyses were performed to develop nutrient content prediction models using spectral information of samples. Results: It was found that the NIRS system had a very good potential to estimate the K, Ca, Cu, and Mg contents of the leaf samples (R-2 > 0.80). It was also found that Fe and Mn concentrations could also be estimated with good accuracy (R-2 = 0.70-0.80). However, the NIRS system did not give good results for the prediction of N, P, and Zn (R-2 < 0.40). Conclusion: In conclusion, the NIRS system can be used to quickly, easily, and economically assess the K, Ca, Cu, Mg, Fe, and Mn contents of dried and ground pistachio leaves. This technique has the potential to improve nutrient management practices in pistachio farming within a sustainable and environmentally conscious framework. Fourier transform NIRS (FT-NIRS) can provide valuable insights by complementing rather than replacing traditional chemical analysis. Laboratory analysis is still required for definitive nutrient content information, but FT-NIRS can significantly reduce the reliance on such analysis, thereby mitigating the environmental impact caused by the excessive use of chemical fertilizers and minimizing the health risks to laboratory staff. In addition, the rapid information-gathering capabilities of the FT-NIRS can be emphasized.