ABSTRACT. Water and saline stresses are the main factors affecting agricultural production in semiarid regions. The tolerance of forage cactus to water and salt deficit makes it a promising solution, in particular Nopalea cochenillifera. The growth curves for species facing these conditions can provide useful information supporting the cultivation and management of natural populations and carry significant biological importance as growth rate assessment contributes to maintaining species viability. The objective of this study was to estimate the plant height and linear dimensions (length, width, and thickness) of N. cochenillifera Giant Sweet clone growing under water and saline stress. The experiment design was completely randomized, comprising a 4 × 4 factorial, with four water and four salinity levels; there were four replications. In order to estimate plant height in N. cochenillifera Giant Sweet clone as a function of the accumulated thermal sum, generalized additive models for location, scale, and shape (GAMLSS) were used to determine water level, saline level, length, width, and thickness. We constructed models using four distributions: the Weibull, Gumbel, Logistic, and Box-Cox power exponential distributions. The models were evaluated using global deviation and the generalized Akaike criterion. The Box-Cox power exponential proved to be the most effective in estimating N. cochenillifera height. This model enabled information relevant to practical environmental management to be obtained, as it precisely defined the optimum salt application and the required amount of replacement water, together with the cladode width for each plant growth stage using the accumulated thermal sum.

ABSTRACT. The forage palm is one of the main forages of ruminants in semiarid regions. Measurements of leaf area are required in agronomic studies because they are one of the main parameters used to evaluate plant growth. The objective of this study was to validate and define the best models for estimating the area and weight of Giant Sweet clone (Nopalea cochenillifera) forage cladodes in a non-destructive way based on the linear dimensions of length, width and thickness. There were 432 randomly measured cladodes at 550 days after planting. The length, width and thickness of each cladode were measured using a digital calliper. The cladodes were weighed individually. The cladode area was calculated by the gravimetric method. The power regression model was the most efficient method to explain the cladode area as a function of the product of length by width, while the gamma model was the most efficient method to explain the weight of cladodes as a function of the product of length by width and thickness. The power model, R C A ̂ = L W 0.982, and gamma model, W C ̂ = 0.536 T + 0.028 L W, were used to determine the area and weight of Nopalea cochenillifera Giant Sweet clone cladodes, respectively, based on the values of linear dimensions measured independently of the order of the cladode.

ABSTRACT. Agricultural production in semi-arid regions is limited due to water availability. In addition, the water quality available for irrigation is often compromised due to the high salt content present. Millet is a forage species considered tolerant to water deficit and moderately salt tolerant. In view of the above, the objective was to evaluate the growth of millet under water and saline stress associates. The experiment was carried out in a randomized block design, in a 4x3 factorial scheme, composed of four levels of water replacement, based on crop evapotranspiration (ETc): 25%.ETc, 50%.ETc, 75%.ETc and 100%.ETc and three levels of water salinity (0.03, 2.0 and 4.0 dS m-1). With 25%.ETc independent of salinity, all morphological characteristics of millet were affected, occurring death of plants in the initial growth phase. In the absence of salt and greater availability of water, greater plant growth occurred. With respect to salinity, there was a reduction in the increment of all variables evaluated, with the highest reduction at the highest saline level (4.0 dS m-1). Water and salt stresses, when associated, reduce the growth of millet, since concentrations above 2.0 dS m-1 and less than 50%.ETc compromise its full development, providing declines in yield.

Resumo Estudos com pastagens necessitam de informações sobre a área foliar, por ser um dos principais parâmetros de avaliação do crescimento das plantas. Desse modo, objetivou-se estimar a área da lâmina foliar do capim-pangolão (Digitaria pentzii Stent.), utilizando métodos não destrutivos por meio de análise de modelos de regressão. O delineamento utilizado foi em blocos casualizados, com três alturas de corte (10, 15 e 20 cm) e quatro repetições. Foram coletadas aleatoriamente 300 lâminas foliares do capim-pangolão e determinados os seus respectivos comprimentos (C) e larguras (L), com uso de paquímetro digital. A área da lâmina foliar do capim-pangolão foi estimada pelo método gravimétrico, sendo utilizados os modelos de regressão linear e potência para explicar a área das lâminas foliares em função do produto do comprimento e máxima largura. A área da lâmina foliar real apresentou valor médio de 18,64 cm2, variando de 4,29 a 45,95 cm2. A área da lâmina foliar do capim-pangolão, independentemente da altura de corte, foi estimada com melhor acurácia pelo modelo potência. O modelo potência, Ŷ=CL1,007, pode ser usado para estimar a área da lâmina foliar do capim-pangolão com base nos valores de comprimento e largura da lâmina foliar dessa espécie.

Abstract Pasture studies require information on leaf area, as it is one of the main parameters for evaluation of plant growth. Thus, the objective of this study was to estimate the leaf blade area of pangolão grass (Digitaria pentzii Stent.) using non-destructive methods by regression model analysis. The experimental design consisted of randomized blocks, with three cutting heights (10, 15, and 20 cm) and four replications. Three hundred leaf blades of pangolão grass were randomly collected, and their respective lengths (L) and widths (W) determined using a digital caliper. The leaf blade area of pangolão grass was estimated by the gravimetric method, using linear and power regression models to explain the leaf blade area as a function of the product of L and maximum W. The real leaf blade area presented an average value of 18.64 cm2, ranging from 4.29 to 45.95 cm2. The leaf blade area of pangolão grass, regardless of cutting height, was estimated with greater accuracy by the power model. The power model, Ŷ=LW1.007, can be used to estimate the leaf blade area of pangolão grass based on leaf blade L and W values.

ABSTRACT. In this work, lacunarity analysis is performed on soil pores segmented by the pure voxel extraction method from soil tomography images. The conversion of forest to sugarcane plantation was found to result in higher sugarcane soil pore lacunarity than that of native forest soil, while the porosity was found to be lower. More precisely, this study shows that native forest has more porous soil with a more uniform spatial distribution of pores, while sugarcane soil has lower porosity and a more heterogeneous pore distribution. Moreover, validation through multivariate statistics demonstrates that lacunarity can be considered a relevant index of clustering and can explain the variability among soils under different land use systems. While porosity by itself represents a fundamental concept for quantification of the impact of land use change, the current findings demonstrate that the spatial distribution of pores also plays an important role and that pore lacunarity can be adopted as a complementary tool in studies directed at quantifying the effect of human intervention on soils.

ABSTRACT. The experiment was carried out to evaluate the productive performance of European quails (Coturnix coturnix) in the production phase, fed with diets containing different levels of digestible lysine. A total of 175 female quails, aged 65 days, were randomly distributed in a completely randomized design with five treatments and five replicates per treatment. The animals were housed in 25 metal cages, and each cage represented an experimental parcel, with seven birds per parcel. The birds were fed the experimental rations containing 1.177, 1.217, 1.317, 1.417, and 1.517% digestible lysine. The parameters evaluated were: laying rate, mass of eggs produced, feed intake in the period, lysine intake, feed conversion per dozen and per mass. Significant differences were observed for posture rate with quadratic behavior, which indicated higher production for the level of 1.23% of digestible lysine. There was an increasing linear behavior for the feed and lysine intake, and for conversion feed per dozen and by mass, we observed quadratic behaviors. This indicates better feed conversion index when the optimal inclusion level was 1.33% and 1.404% of digestible lysine in the diet, respectively. The requirement of digestible lysine in diets for European quails is 1.404%, which corresponds to a daily intake of 421.20 milligrams of digestible lysine.

ABSTRACT. Leaf area measurements are of the main parameters used in agronomic studies to evaluate plant growth. The current study used a non-destructive method based on linear leaf dimensions (length and width) to select the regression model to estimate millet (Pennisetum glaucum) leaf area. For two millet genotype (IPA BULK 1 BF and ADR 300) 128 randomly-chosen leaves were measured at different vegetative growth stages. Measures of length and width of each leaf were made using digital calipers. Leaf area was measured using a gravimetric method. The best-fit leaf area estimation model was selected via linear, potential and gamma regression models. Leaf area values varied from 3.02 to 209.21 cm2. The average value was 95.31 cm2. The potential regression model exhibited lower residual sum of squares and Akaike's information criterion and similar determination coefficient and Willmott index. Thus, potential regression was more efficient in explaining the leaf area of millet, independent of the genotype, when compared to other models evaluated in this research. Length (L) and width (W) could be used in the following potential regression model Y ̂ = 0.879 L W 0.971to estimate millet leaf blade.

ABSTRACT. This study adjusted different regression models to describe the growth pattern of meat quails from birth to 42 days of age. Data of 300 male quails were used. Weight and height information of all quails were collected weekly from the 1st to the 42nd day of age. Body weight of poultry was subjected to the polynomial, logistic, Gompertz, Weibull, and log-normal regression models. The criteria used to choose the best model to explain the growth curve of quails were the coefficient of determination of the model, Akaike’s information criterion, sum of squared residuals and Willmott’s index. For all the models used, the variables age and height were significant to explain the weight of quails. The polynomial (R² = 99.99%, AIC = 24.68, SSR = 27.5, d = 0.9999) and log-normal (R² = 99.60%, AIC = -17.5, SSR = 107.15, d = 0.9989) models presented the best fit criteria and were recommended to explain the growth of quails.