Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
DOI:
https://doi.org/10.13083/reveng.v30i1.12656Keywords:
mathematical modeling, populational monitoring, digital sensors, thermometryAbstract
Insect pest infestation in stored grains can cause several losses during storage, in addition to promoting the spread of fungi, changing the temperature of the grain mass, and reducing the value of the final product. Knowing the behavior of these insect pests and how they reproduce in the grain mass is essential to design more efficient control strategies and ensure a quality final product. Thus, this work aimed to accomplish modeling and simulation of the population growth of insects Rhyzopertha dominica, Sitophilus oryzae, Oryzaephilus surinamensis and Tribolium castaneum throughout the storage of corn grain, using data retrieved from digital sensors of temperature installed in three Brazilian storage facilities in different regions. Data were collected through managing system CERES (company Procer Automação e Sistemas) and retrieved from 1st of July to 29th September 2019. In each one of the facilities, a silo equipped with the aforementioned sensors was used. Mean weekly values of temperature of the grain mass and the intergranular relative humidity were used, calculated using the Modified Henderson equation. The silos evaluated in facilities 1, 2, and 3 have a static capacity of 2,100; 6,304, and 93 tones, respectively, considering soybean with a bulk density of 750 kg m-3. Higher growth rates of all assessed species were observed for the storage facility number 2; and lowest values for storage facility number 1. Storage facilities that presented a higher potential for the growth rate of insects are subjected to elevated levels of insect populations throughout time.
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