Simulation of fungal growth in papaya: an opportunity to enhance postharvest handling (e-Latin Food 2020)
Papaya (Carica papaya L.) is a climacteric fruit with a high susceptibility to decay and mechanical damage, causing economic losses. Anthracnose caused by Colletotrichum species is the most common disease in papaya; however, many other fungi that cause damage. In order to find alternative methods to control postharvest fungi, predictive mycology methods have been developed. Mathematical models can simulate and predict fungal behavior as a function of environmental conditions. However, simulations as a tool for making decisions to assure fruit quality are scarce. This study’s objective was to simulate the growth rate and the time to appearance of disease for Colletotrichum gloeosporioides and Alternaria alternata isolated from papaya as a function of temperature. Four C. gloeosporioides and two A. alternata isolates from decayed papaya were used. The isolates were cultured in a complex medium made with papaya pericarp to assess their growth rates and lag phases. The Baranyi-Roberts model was used to estimate the radial growth rates (µmax) and Microsoft Excel’s Solver feature was used to obtain the time for visible mycelium (tv). The cardinal model with infletion (CMI) was used to model tv for C. gloeosporioides whereas a polynomial function was used for A. alternata. The simulated models were compared with data obtained by growing the fungi on fresh papaya. The models obtained provide insight into the fungal growth dynamics and seem to be satisfactory for describing tv compared to the data observed in vivo. Transporters could be use them to establish how much time a given crop can conserve its quality before decay begins. These findings could be a useful tool for making decisions in the papaya supply chain.
Keywords: Carica papaya, predictive mycology, postharvest decay, growth simulations, supply chain.