Assessment of engineering parameters and mass modeling for reducing postharvest losses of sweet lime (Citrus limetta) fruit - Desai, Shivani; Kad, Vikram; Shelke, Ganesh; Alqahtani, Nashi K.; Kumar Patil, Prashant; Kakade, Sudama; Yenge, Govind; Al-Dalain, Sati Y.; Helal, Mahmoud; Alnemari, Nimah; Sami, Rokayya; Abo-dief, Hala M.; et al. (Italian Journal of Food Science, 2025)
Lack of data on the engineering properties of sweet lime fruits leads to substantial waste during postharvest processes. This study analyzed the engineering properties of sweet lime fruit, including physical, chemical, thermal, and mechanical properties, and developed mass models to minimize postharvest losses. The average values of the sweet lime’s major axis (LA), intermediate axis (IA), and transverse axis (TA), as well as the arithmetic, geometric, and equivalent mean diameters, were 78.71, 77.07, 74.96, 76.92, 76.89, and 76.9 mm, respectively. The mean values of PLA, PIA, PTA, CPA, and Sa were 4663.01, 4567.45, 4444.17, 4558.21, and 18694.41 mm2, respectively. Sweet lime volumes were measured by Vellip, Vpro, and Vosp, with average values of 242.95, 254.97, and 249.79 cm3. The sphericity was 0.95, suggesting that the sweet lime has a spherical shape. The average bulk density and true density were 449.75 and 931.41 kg/m3. Stainless steel exhibited the minimum static friction. The average peak values of penetration, compression, and cutting forces were 9.44, 311.08, and 148.68 N, respectively. Sweet lime had average L*, a*, and b* values of 58.07, -13.15, and 51.38. Models such as S-curve, power, and quadratic were used to predict the sweet lime mass. The linear and quadratic models exhibited the highest R2 values for the intermediate axis, geometric mean diameter, and ellipsoidal volume, with 0.93, 0.95, and 0.93, respectively. The quadratic model, based on geometric mean diameter, is recommended for accurately estimating sweet lime mass. The results of this study showed a statistically significant relationship (ρ < 0.01) for all properties and models. By analyzing the acquired data, postharvest operations for sweet lime fruit processing can be designed, improved, and developed, leading to increased efficiency and productivity.