(177d) Transpiration Rates of Leafy Vegetables during Postharvest Storage: Gravimetric and Theoretical Approach

Leafy vegetables are essential to human health and nutrition, since they are rich sources of vitamins, minerals and dietary fibers. However, most of them are high perishable and have a very reduced shelf life. Transpiration or water loss is a critical physiological process that affects the quality and safety of postharvest vegetables, leading to wilting and undesirable changes in nutritional and physicochemical aspects. Refrigeration is the main technology used to preserve these vegetables and has a high potential to improve their shelf life. Rocket and lettuce are leafy vegetables largely consumed in all over the world and for this reason they are studied in this paper. So, these paper aims to evaluate the effect of low temperatures (2 and 6 °C) on rocket and lettuce transpiration rates (TR), using a gravimetric and a theoretical approach. In gravimetric approach TR was calculated by measuring the weight loss over time and was expressed as changes in vegetable weight (g) per initial weight (kg) per unit time (day). The theoretical approach was based on Fick’s Law of diffusion. According to Ben-Yehoshua (1987) the flow of water vapor is proportional to the difference in water activity between the vegetable surface and the surrounding air. So, it can be expressed as the product between a mass transfer coefficient (K) and the water activity differential. Caleb et al. (2012) showed that the surrounding air water activity does not significantly change with temperature in the conditions of this experiment and has a value of 0.984, so it was kept constant. Moreover, preliminary tests showed that the rocket and lettuce water activity does not significantly change during the storage period, resulting in a constant gradient of water loss. The water activity was measured using water activity meter (Aqualab 3.0). A temperature term was incorporated in K in order to estimate its effect on TR. Combining both approaches, an overall equation able to predict the mass as a function of temperature and storage period was obtained, according to Caleb et al. (2012). Experimental data were obtained and used to estimate the two constants from the model. The equation was fitted by non-linear regression using Statistica software (Statistica 7.0, Statsoft, USA). For the experiments, the vegetables were harvest from a hydroponic system early in the morning and immediately sent to the laboratory, where they were cleaned and packaged in microperforated polyethylene films, that were kept open during storage. Each film was packaged with approximately 15 grams of vegetable. Then, they were stored in a refrigerator with temperature control and temperature and humidity monitoring at 2 and 6 °C and changes on weight loss were analyzed on days 0 (day of harvest), 3, 5, 7, 9 and 10, using an electronic balance (Marte – Model A100). Tests were made in triplicate. Results show a decrease on TR with temperature for rocket and lettuce. During the storage period, a decrease on TR was also observed comparing the first and the last day, except for lettuce storage at 6 °C. The TR decreased from 8.97 to 8.29 (g/kg day) and from 7.09 to 6.09 (g/kg day) to rocket at 6 and 2 °C, respectively, and from 6.78 to 6.31 (g/kg day) to lettuce at 2 °C, and increased from 10.05 to 11.58 (g/kg day) to lettuce stored at 6 °C. The proposed model showed a good agreement with the results (R² = 0,998). In order to validate the model, experimental data at 4 °C were compared with model predictions and they showed a good agreement too. As could be observed in the results, small changes in temperature (4 °C) can significant affect vegetables water loss and thus vegetables shelf life. Comparing lettuce and rocket, the first was even more sensitive to temperature chances and a change for 4 °C fast doubled lettuce water loss. The model is capable to predict changes on properties from vegetables and is a useful tool to understand the influence of temperature on water loss, supporting following studies to find the best storage conditions for each commodity, reducing food and energy waste.