Liming in Agricultural Production Models with and Without the Adoption of Crop-Livestock Integration

ABSTRACT Perennial forage crops used in crop-livestock integration (CLI) are able to accumulate large amounts of straw on the soil surface in no-tillage system (NTS). In addition, they can potentially produce large amounts of soluble organic compounds that help improving the efficiency of liming in the subsurface, which favors root growth, thus reducing the risks of loss in yield during dry spells and the harmful effects of “overliming”. The aim of this study was to test the effects of liming on two models of agricultural production, with and without crop-livestock integration, for 2 years. Thus, an experiment was conducted in a Latossolo Vermelho (Oxisol) with a very clayey texture located in an agricultural area under the NTS in Bandeirantes, PR, Brazil. Liming was performed to increase base saturation (V) to 65, 75, and 90 % while one plot per block was maintained without the application of lime (control). A randomized block experimental design was adopted arranged in split-plots and four plots/block, with four replications. The soil properties evaluated were: pH in CaCl2, soil organic matter (SOM), Ca, Mg, K, Al, and P. The effects of liming were observed to a greater depth and for a long period through mobilization of ions in the soil, leading to a reduction in SOM and Al concentration and an increase in pH and the levels of Ca and Mg. In the first crop year, adoption of CLI led to an increase in the levels of K and Mg and a reduction in the levels of SOM; however, in the second crop year, the rate of decline of SOM decreased compared to the decline observed in the first crop year, and the level of K increased, whereas that of P decreased. The extent of the effects of liming in terms of depth and improvement in the root environment from the treatments were observed only partially from the changes observed in the chemical properties studied.

ANATOMICAL STUDIES OF IN VITRO ORGANOGENESIS INDUCED IN LEAF-DERIVED EXPLANTS OF PASSIONFRUIT

With the aim of studying the organogenesis in vitro in Passiflora edulis Sims f. flavicarpa Deg., the passionfruit, leaf-derived explants were cultured on media containing NAA or BAP and incubated either in continuous darkness or in light. The histological events leading to de novo organ formation were evaluated. Darkness induces rhizogenesis in the presence of NAA, whereas direct shoot regeneration is stimulated by light and BAP. This latter condition is recommended for passionfruit micropropagation as several adventitious shoot buds were formed from meristemoids of parenchymal origin.

Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina

The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the adequate performance and pertinence of this methodology to estimate complex phenomena, such as solar radiation.

Physiological and anatomical characteristics of leaves of two clones of guarana

The objective of this work was to analyze gas exchange, photosynthetic characteristics, photochemical efficiency of photosystem II and anatomical characteristics of young plant leaves of two guarana (Paullinia cupana) clones (BRS-CG372RC and BRS-CG611RL) growing under open field. The variables of gas exchange and fluorescence of chlorophyll a were evaluated in mature leaves. The values of photosynthesis and transpiration found for BRS-CG372RC were 27% greater and 80% lesser than values found for BRS-CG611RL, respectively. The values of stomatal conductance found for the clones BRS-CG372RC and BRS-CG611RL were in the order of 224 and 614 mmol mm-2 s-1, respectively. The values of photorespiration, rate of carboxylation and rate electron transport were greater in BRS-CG372RC. The clone BRS-CG372RC exhibited stomatal density 26% greater than BRS-CG611RL. However, the area of ostiolar opening was 42% greater in BRS-CG611RL. The values of the water use efficiency in BRS-CG372RC were 134% greater than in BRS-CG611RL. High stomatal density and low stomatal conductance can be important characteristics in the selection of the clones with a good ability to assimilate carbon and optimize the use of water.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Semivariogram models for estimating fig fly population density throughout the year

The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae) throughout the year, using ordinary kriging. Nineteen monitoring sites were demarcated in an area of 8,200 m2, cropped with six fruit tree species: persimmon, citrus, fig, guava, apple, and peach. During a 24 month period, 106 weekly evaluations were done in these sites. The average number of adult fig flies captured weekly per trap, during each month, was subjected to the circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, hole effect, K-Bessel, J-Bessel, and stable semivariogram models, using ordinary kriging interpolation. The models with the best fit were selected by cross-validation. Each data set (months) has a particular spatial dependence structure, which makes it necessary to define specific models of semivariograms in order to enhance the adjustment to the experimental semivariogram. Therefore, it was not possible to determine a standard semivariogram model; instead, six theoretical models were selected: circular, Gaussian, hole effect, K-Bessel, J-Bessel, and stable.

Predicting chick body mass by artificial intelligence-based models

The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

Field data and prediction models of pesticide spray drift on coffee crop

The objective of this work was to generate drift curves from pesticide applications on coffee plants and to compare them with two European drift-prediction models. The used methodology is based on the ISO 22866 standard. The experimental design was a randomized complete block with ten replicates in a 2x20 split-plot arrangement. The evaluated factors were: two types of nozzles (hollow cone with and without air induction) and 20 parallel distances to the crop line outside of the target area, spaced at 2.5 m. Blotting papers were used as a target and placed in each of the evaluated distances. The spray solution was composed of water+rhodamine B fluorescent tracer at a concentration of 100 mg L-1, for detection by fluorimetry. A spray volume of 400 L ha-1 was applied using a hydropneumatic sprayer. The air-induction nozzle reduces the drift up to 20 m from the treated area. The application with the hollow cone nozzle results in 6.68% maximum drift in the nearest collector of the treated area. The German and Dutch models overestimate the drift at distances closest to the crop, although the Dutch model more closely approximates the drift curves generated by both spray nozzles.