Excessive nitrogen fertilization results in nitrate accumulation in leafy vegetables. Reducing the dose of mineral nitrogen or using alternate fertilizers lowers the nitrate accumulation; however, a critical minimum level of mineral nitrogen is necessary to maintain yield and nutritional quality. The aim of this study was to evaluate the effect of two levels of mineral nitrogen (100% and 50%) and three levels of an amino acid solution (0, 0.3, and 0.9%) in the nutrient solution of two baby lettuce cultivars (green and red) grown in a floating system. Nitrogen reduction did not affect yield (12.9–13.4 and 11.0–11.3 g/plant, respectively) but reduced nitrate accumulation (by 43 and 19%, respectively) in both green and red lettuce, while enhancing phenolic content (by 28%) and antioxidant capacity (by 69%) in green lettuce and soluble solid (by 7%) and total chlorophyll content (by 9%) in red lettuce. Although nitrate accumulation was prevented (< 355 mg/kg FW) and most nutritional components increased in both lettuce types by amino acids supplementation, plant growth was negatively affected, especially in red lettuce, in both concentrations of amino acids (reduction by 9 and 35% in 0.3 and 0.9%, respectively). In both lettuce types, proline content increased by 0.9% amino acids supplementation (by 45%), implying a probable induction of a stress condition. Mineral nutrients were slightly affected by nitrogen reduction, which was probably perceived as an abiotic stress.

The present study investigated the potential of fresh peppermint (Mentha × piperita L.) and spearmint (Menthaspicata L.) production on a floating raft system combined with a commercial protein hydrolysate supplement (Amino16^®) in a nutrient solution aiming to improve plant product quality. Three levels of the protein hydrolysate solution (0, 0.25 and 0.50%) were added in the nutrient solution, and the plants were harvested after twenty-four days. Plant growth characteristics were recorded, and nutritional, essential oil and polyphenolic composition were determined in fresh tissue. The addition of protein hydrolysates did not affect the fresh or dry weight but reduced plant height. Nitrate content significantly decreased, while total chlorophyll and essential oil content increased in both species. Moreover, the protein hydrolysate solution further increased total antioxidant capacity, total soluble phenol and carotenoid contents in spearmint plants, while it did not affect the essential oil and polyphenolic composition in both species. In conclusion, protein hydrolysates solution may be added in the nutrient solution, to improve the quality of peppermint and spearmint grown in a floating system, without adverse effects on crop yield or the essential oil and polyphenolic profile.

Background: Quality and safety of potato is both cultivar and postharvest management dependent. The precise assessment of freshness and cultivar are complex tasks requiring time-consuming, expensive, and destructive techniques. Method: Potatoes from three commercial cultivars were stored for 5 months at 5 °C. Color and chlorophyll fluorescence were recorded, Red-Green-Blue (R-G-B), Red-Green-Near infrared (R-G-NIR) and Red-Blue-Near infrared (R-B-NIR) digital images, as well as hyperspectral images were acquired both on the external periderm of the tuber and in the inner flesh part. Partial least square regression (PLSR) and discriminant analysis, combined with feature selection techniques were implemented, in order to assess the potato freshness and to classify them into the respective genotypes. Results: The PLSR analysis of visible/near infrared (Vis/NIR) spectra reflectance most reliably predicted potato freshness, with a cross-validated regression coefficient equal to 0.981 and 0.947, as determined by external or internal measurements, respectively. Variance inflation factor, variable importance scores, and genetic algorithms identified specific wavelength regions that mostly affected the accuracy of the model in terms of strongest regression and lowest collinearity and root mean cross validation error. Conclusions: Vis/NIR spectra reflectance data from the skin of the potato tubers may be reliably used in the assessment of postharvest storage life, as well as in the cultivar discrimination process.

The objective of this study was to evaluate the feasibility of using visible, near-infrared, and short-wave infrared (VIS/NIR/SWIR) spectroscopy coupled with chemometrics for non-destructive prediction of nutritional components in Galia-type melon fruit. A total of 175 fully ripened melons were analyzed for soluble solids content (SSC), dry matter (DM), pH, and titratable acidity (TA) using partial least squares regression (PLSR), principal components regression (PCR), and multilinear regression (MLR) models. Reflectance spectra were captured at three fruit locations (pedicel, equatorial, and blossom end) in the 350–2500 nm range. The PLSR models yielded the highest accuracy, particularly for SSC (R = 0.80) and SSC/TA (R = 0.79), using equatorial zone data. Variable selection using the genetic algorithm (GA) successfully identified the spectral regions critical for each nutritional parameter at the pedicel, equatorial, and blossom end areas. Key wavelengths for SSC were found around 670–720 nm and 900–1100 nm, with important wavelengths for pH prediction located near 1450 nm, and, for dry matter, in the ranges 1900–1950 nm. Variable importance in projection (VIP) analysis confirmed that specific wavelengths between 680 and 720 nm, 900 and 1000 nm, 1400 and 1500 nm, and 1900 and 2000 nm were consistently critical in predicting the SSC, DM, and SSC/TA ratio. The highest VIP scores for SSC prediction were noted around 690 nm and 950 nm, while dry matter prediction was influenced most by wavelengths in the 1450 nm to 1950 nm range. This study demonstrates the potential of VIS/NIR/SWIR spectroscopy for rapid, non-destructive melon quality assessment, with implications for commercial postharvest management.

This study evaluates the potential of integrating visible and near-infrared (visNIR) spectroscopy, color analysis, and firmness testing for non-destructive tomato quality assessment and shelf-life prediction. Tomato fruit (cv. HM1823) harvested at four ripening stages were monitored over 12 days at 22 °C to investigate ripening stage-specific variations in key quality parameters, including color (hue angle), firmness (compression), and nutritional composition (pH, soluble solids content, and titratable acidity ratio). Significant changes in these parameters during storage highlighted the need for advanced tools to monitor and predict quality attributes. Spectral data (340–2500 nm) captured using advanced and cost-effective portable spectroradiometers, coupled with chemometric models such as partial least squares regression (PLSR), demonstrated reliable predictions of shelf-life and nutritional quality. The near-infrared spectrum (900–1700 nm) was particularly effective, with variable selection methods such as genetic algorithm (GA) and variable importance in projection (VIP) scores enhancing model accuracy. This study highlights the promising role of visNIR spectroscopy as a rapid, non-destructive tool for optimizing postharvest management in tomato. By enabling real-time quality assessments, these technologies support sustainable agricultural practices through improved decision-making, reduced postharvest losses, and enhanced consumer satisfaction. The findings also validate the utility of affordable spectroradiometers, offering practical solutions for stakeholders aiming to balance cost efficiency and reliability in postharvest quality monitoring.