Infection model for analyzing biological control of coffee rust using bacterial anti-fungal compounds.

Coffee rust is one of the main diseases that affect coffee plantations worldwide (Cressey, 2013 [10]). This causes an important economic impact in the coffee production industry in countries where coffee is an important part of the economy. A common method for combating this disease is using copper hydroxide as a fungicide, which can have damaging effects both on the coffee tree and on human health (Haddad et al., 2013 [13]). A novel method for biological control of coffee rust using bacteria has been proven to be an effective alternative to copper hydroxide fungicides as anti-fungal compounds (Haddad et al., 2009 [12]). In this paper, we develop and explore a spatial stochastic model for this interaction in a coffee plantation. We analyze equilibria for specific control strategies, as well as compute the basic reproductive number, R0, of individual coffee trees, conditions for local and global stability under specific conditions, parameter estimation of key parameters, as well as sensitivity analysis, and numerical experiments under local and global control strategies for key scenarios.

[Yield loss model and yield loss mechanism of high-yielding summer maize infected by Physoderma maydis].

A total of 21 different disease-grading summer maize groups were formed by fixed-point natural infection of maize brown spot in the field, and mass loss estimation models of single ear mass and 100-grain mass were constructed by stepwise regression with DPS software. The mass loss estimation models of single ear and 100-grain were Y = -4.012 + 0.377X1 - 0.228X2 + 0.694X3 - 0.144X4 and Y = -4.536 + 0.173X1 + 0.188X2 + 0.248X3 - 0.034X4, respectively, where Y was yield loss rate, X1 was the disease index at flowering stage, X2 was the disease index at pollination stage, X3 was the disease index at filling stage, and X4 was the disease index at dough stage. The measured relationships between the disease indices at different growth stages and the mass loss for single ear and 100-grain coincided well with the modeling results. Maize brown spot directly affected the net photosynthetic rate of ear height leaf and the activities of RuBP carboxylase and PEP carboxylase. The higher the disease-grade, the lower the net photosynthetic rate and the activities of the two enzymes were.