Corn (Zea mays L.) stands out as one of the main grains cultivated worldwide.
The consumption of corn varies from the "in natura" form, to the processed ones, such
as canned food. This study aimed to study the kinetics of hydration of green corn and
sweet corn grains with a focus on the use of biodiversity for the production of canned
food. The experiments were conducted at the Federal University of Tocantins and
Federal Institute of Tocantins, where 4 corn cultivars (C1, C2 and C3 common green
corn and C4 sweet corn) were planted, under different environments, fertilizer levels
and sowing times. The cobs were harvested, at the green corn stage, with grain
moisture between 70 and 80%, performed the physical and chemical characterization
of the grains for moisture content, protein, lipids, ash, carbohydrate and fiber. For the
hydration kinetics, the corn grains were soaked in distilled water at temperatures of 25,
35, 45, 55, and 65 ºC for up to 70 minutes. MatLab Software was used for mathematical
fitting for the PELEG, PAGE, Weibull, Ibarz et al. and Henderson and Pabis models
and SPSS Software was used to develop the Artificial Neural Network. The green grain
yields of C4 were similar (p<0.05), by the Scott-Knott test, with C1 and C3 in
environments 2 and 4. In environments 1, C1 was similar to C3, and in environment 3
C3 had a higher yield of 77%. It can be observed that the sweet corn cultivated in
Palmas - TO presented a yield of green grains of 60%, similar to C1, thus noting that
even under different climatic conditions and different corn genotypes, sweet corn
presented productive viability similar to green corn. The average contents of ash,
moisture, carbohydrate, fiber, lipids and protein of green and sweet corn cultivars
showed higher values for the 120N fertilization level. Regarding mathematical
modeling, the coefficient of determination R2 for C1 showed the best fit to the model
of Ibarz et al at 25ºC. For C2 the best mathematical model was that of Ibarz et al at
25ºC and the PELEG model at 45ºC. The results obtained for C3 and C4 are similar to
those obtained for C1, because the best model was also the Ibarz et al. All R2 found
in the ANN presented values above 0.90, indicating that 90% of the variables studied
for the uptake content were explained by the variables time and temperature, also
observed linearity between the values of uptake and predicted value of the modeling.
Given these results it was observed the important to study the yield of sweet and green
corn grains, because they influence productivity. And it can be concluded that green
corn "in natura" managed to maintain the quality standards related to water absorption,
resembling sweet corn, thus enabling the use of these grains in the processing of
canned food.
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