RESUMO
Research on medicinal plants is essential for their conservation, propagation, resistance to environmental stress, and domestication. The use of organic nutrition has been demonstrated to improve soil fertility and plant quality. It is also important to study the effects of the Basic Cation Saturation Ratio (BCSR) approach, which is a topic where there is currently controversy and limited scientific information. Evaluating the growth and yields of Agastache mexicana subsp. mexicana (Amm) in different environments is crucial for developing effective propagation and domestication strategies. This includes examining warm and subhumid environments with rain in summer in comparison to mild environments with summer rain. Significant differences were observed in the effects of cold, waterlogging, and heat stresses on the plant's biomass yield and the morphometric-quantitative modeling by means of isolines. The biomass yield was 56% higher in environment one compared to environment two, 19% higher in environment one with organic nutrition, and 48% higher in environment two with organic nutrition compared to using only BCSR nutrition. In the second harvesting cycle, the plants in environment one did not survive, while the plants in environment two managed to survive without needing additional nutrition. Statistical and mathematical analyses provided information about the population or sample. Additionally, further analysis using isolines as a new approach revealed new insights into understanding phenology and growth issues.
RESUMO
In this research, the mathematical model associated with the hydrothermal dehydration process of Nixtamalized Corn Grains (NCG) with different Steeping Time (ST) values, allows the fitting of experimental data with initial moisture M0 and the equilibrium moisture ME as a function of Isothermal Dehydration Time (IDT). The moisture percentage for any time t and dehydration rate (isolines M(t) and isolines vI respectively) of the NCG is shown by means of matrix graphics as a simultaneous function of IDT and ST. The relationship between initial dehydration rate v0 and initial moisture M0 establishes as a function of ST. Also, the mathematical model associated with the solution of the second Fick's law allows calculating the diffusivity rate vk (H2O molecules out of NCG) and verify that the rate of change in moisture and the dynamical proportionality constant k has a non-linear dependence on the IDT and that k is directly proportional to Deff. The k values strongly relate to ST and the calcium ions percentage into NCG according to solubility lime values into cooking water (or nejayote) as a function of decreasing temperature when ST increases.
RESUMO
A model of an Equivalent Artificial Neural Net (EANN) describes the gains set, viewed as parameters in a layer, and this consideration is a reproducible process, applicable to a neuron in a neural net (NN). The EANN helps to estimate the NN gains or parameters, so we propose two methods to determine them. The first considers a fuzzy inference combined with the traditional Kalman filter, obtaining the equivalent model and estimating in a fuzzy sense the gains matrix A and the proper gain K into the traditional filter identification. The second develops a direct estimation in state space, describing an EANN using the expected value and the recursive description of the gains estimation. Finally, a comparison of both descriptions is performed; highlighting the analytical method describes the neural net coefficients in a direct form, whereas the other technique requires selecting into the Knowledge Base (KB) the factors based on the functional error and the reference signal built with the past information of the system.