The tropical dry areas have suffered the most severe anthropic pressures. This factor motivates studies aimed at characterizing and monitoring the soil quality to determine the management measures to apply and to suggest appropriate recovery procedures. The objective of this study was to evaluate the enzymatic activity of acid and alkaline phosphatases, urea and arylsulfatase in the superficial layers of soils in areas under different stages of forest regeneration, in Floresta-PE City.. Soil sampling was conducted at 0-5, 5-15 and 15-30 cm layer in the following areas: C-18 (vegetation regeneration for 18 years), P-13 (13 years), L-12 (12 years), C-9 (9 years), C-7 (7 years) and G-4 (4 years). The analytical methods used in the study were based on the incubation of the soil samples with a buffered solution of substrate specific for each enzyme. The methods were based on colorimetric determinations. The activity of acid and alkaline phosphatase and urease represented sensitive measures for detecting changes in soil quality at various stages of regeneration in tropical dry forests. The area with the longest duration of forest regeneration (C-18) showed higher enzyme activities. The soil enzymatic activities respond to different stages and management of forest regeneration in Brazilian tropical dry areas, namely Caatinga. The acid and alkaline phosphatase, arylsulfatase and urease increased with time of regeneration.

The objective of this study was to evaluate the effects of the addition of parts of leguminous trees on the growth and nutrition of maize (Zea mays L.), as well as on the chemical attributes of a degraded soil, 65 days after applying the residues. The experiment was conducted in pots, in a randomized block design with ten treatments and four replicates. The evaluated treatments were: T1 - No residues of leguminous trees, T2 - Leaves of Mimosa caesalpiniifolia, T3 - Branches of Mimosa caesalpiniifolia, T4 - Leaves + branches of Mimosa caesalpiniifolia, T5 - Leaves of Mimosa hostilis, T6 - Branches of Mimosa hostilis, T7 - Leaves + branches of Mimosa hostilis, T8 - Leaves of Gliricidia sepium, T9 - Branches of Gliricidia sepium and T10 - Leaves + branches of Gliricidia sepium. Pots were filled with soil from a degraded area and residues were added in the form of green mass after sowing the maize. Residues of leguminous trees positively influenced maize growth at 65 days after application and favored the accumulation of nitrogen, phosphorus and potassium in the shoots. Green fertilizers improved soil chemical attributes at 65 days after application, especially nitrate-N (NO3 --N), ammonium-N (NH4 +-N), total inorganic N (NO3 --N + NH4 +-N) and K, demonstrating that these species are good options for recovering degraded areas in the semi-arid region of Ceará.

Soil physical and chemical analyses are relatively high-cost and time-consuming procedures. In the search for alternatives to predict these properties from a reduced number of soil samples, the use of Artificial Neural Networks (ANN) has been pointed out as a great computational technique to solve this problem by means of experience. This tool also has the ability to acquire knowledge and then apply it. This study aimed at using ANNs to estimate the physical and chemical properties of soil. The data came from the physical and chemical analysis of 120 sampling points, which were submitted to descriptive analysis, geostatistical analysis, and ANNs training and analysis. In the geostatistical analysis, the semivariogram model that best fitted the experimental variogram was verified for each soil property, and the ordinary kriging was used as an interpolation method. The ANNs were trained and selected based on their assertiveness in the mapping of considered standards, and then used to estimate all soil properties. The mean errors of ordinary kriging estimates were compared to those of ANNs and then compared to the original values using Student's t-Test. The results showed that the ANN had an assertiveness compatible with ordinary kriging. Therefore, such technique is a promising tool to estimate soil properties using a reduced number of soil samples.

Potato (Solanum tuberosum L.) is a nutritionally demanding crop, and phosphorus (P) is a nutrient that exerts a large effect on tuber yield. However, as the availability of P is influenced by soil texture, there are doubts about how P supplementation affects the growth and yield of potato plants in different soil textures. Thus, here we aimed to evaluate the effect of P fertilization and soil texture on the nutrition, growth, tuber yield, and P use efficiency (PUE) of potato plants. The experiment was conducted under greenhouse conditions in a randomized block design with a 4×2 factorial scheme and five replications. The treatments were represented by four P rates (10, 50, 100, and 200 mg dm-3 P) and two soil textures (clayey and sandy). The concentrations of P, Ca, and Mg in the leaves were higher in sandy soil, and P rates increased the concentrations of N, P, and Ca in the leaves of potato plants. Phosphorus fertilization increased plant growth, the amount of P accumulated in the shoot, and tuber yield in both soils; this trend was stronger in the potato cultivated in the clayey soil than in the sandy soil. The applied-PUE was not affected by soil texture. In the potato cultivated in the sandy soil, the taken up-PUE was reduced due to the decrease in dry matter production and an increase in P concentration in the organs of the plant with higher P fertilizer rates.

The cultivation of irrigated guava in semi-arid areas highlights the need for information regarding its responses to irrigation water quality and the fertilization management that enables its exploitation. Thus, this study aimed to evaluate the effect of water salinity and nitrogen (N) doses on the growth and physiology of the guava cv. ‘Paluma’. The experiments was conducted in drainage lysimeters under field conditions in an experimental area at the Center of Sciences and Agri-Food Technology of the Federal University of Campina Grande (CCTA/UFCG), Campus II, in Pombal, PB, Brazil. The experiment had a randomized block design, and treatments consisted of a 5 x 4 factorial arrangement corresponding to five levels of irrigation water electrical conductivity, ECw (0.3, 1.1, 1.9, 2.7, and 3.5 dS m-1), and four N doses (70, 100, 130, and 160% of the recommended N dose). The 100% dose corresponded to 541.1 mg of N dm-3 of soil. Increments in irrigation water salinity from 0.3 dS m-1 led to a reduction in stomatal conductance, internal CO2 concentration, CO2 assimilation rate, transpiration, instantaneous water use efficiency, the number of leaves and branches, stem diameter, and absolute and relative growth rates. Nitrogen doses ranging from 378.7 to 865.7 mg of N dm-3 of soil did not affect gas exchange and plant growth. Although ‘Paluma’ guava growth was affected by increases in water salinity, these plants can be irrigated using water of up to 1.42 dS m-1 with an acceptable reduction of 10% in growth variables. The interaction between irrigation water salinity and N fertilization had no significant effect on any of the variables studied.

Rio Grande do Norte has mountain formations with edaphoclimatic conditions different from those predominating in the state, presenting deeper,acid soils, and milder climate. Among these formations, is the Santana mountain range, which is part of the Serra do Martins Formation. The objective of this work was to interpret the pedogenesis of the representative soils of the Santana mountain range through morphological, physical, and chemical characterizations of soil profiles and evaluate the effect of these attributes on the distribution of pedological forms along the landscape using multivariate analysis. Morphological, physical, and chemical analyses of seven soil profiles of the Santana mountain range were performed. The soils were classified according to the Brazilian Soil Classification System and the data subjected to multivariate analysis. The representative soil classes found were: LATOSSOLO AMARELO Distrófico argissólico; LATOSSOLO AMARELO Eutrófico argissólico; NEOSSOLO QUARTZARÊNICO Órtico típico; NEOSSOLO LITÓLICO Eutrófico fragmentário; NEOSSOLO REGOLÍTICO Eutrófico típico and CAMBISSOLO HÁPLICO Tb Eutrófico léptico. According to the analysis of the morphological attributes, the parent material had great influence on the formation of the different soil classes found in the Santana mountain range. The soil textural classes varied from sand to sandy clay loam. According to the analysis of the chemical attributes, the soil profiles presented acid reaction, great variation of base saturation, and low electrical conductivity. The multivariate analysis established groups of representative soil profiles of the Santana mountain range through the distinction of their physical and chemical attributes, mainly of subsurface diagnostic horizons.

Researches evaluating the use of mulch has contributing to optimize soil management towards sustainability, and improving soil quality. The objective of this study was to evaluate the efficiency of mulching on the reduction of erosion in a soil with sorghum (Sorghum bicolor L. Moench) crops subjected to simulated rainfall and increased soil organic carbon. The experiment was carried out from August to December 2013 under field conditions, using a randomized block design with three replications. The treatments consisted of sorghum with mulch, using the local vegetation available in the area; and sorghum without mulch. Simulated rainfalls were performed in three different periods of the crop cycle (initial, intermediate, and final), using a rainfall simulator. The use of mulch in soils with sorghum crops was efficient in improving soil water retention in all phases of the crop, and maintaining soil moisture during the rainfall intervals used, resulting in the absence of plant water loss, and greater contribution to soil organic carbon.

Genome-wide selection (GWS) uses simultaneously the effect of the thousands markers covering the entire genome to predict genomic breeding values for individuals under selection. The possible benefits of GWS are the reduction of the breeding cycle, increase in gains per unit of time, and decrease of costs. However, the success of the GWS is dependent on the choice of the method to predict the effects of markers. Thus, the objective of this work was to predict genomic breeding values (GEBV) through artificial neural networks (ANN), based on the estimation of the effect of the markers, compared to the Ridge Regression-Best Linear Unbiased Predictor/Genome Wide Selection (RR-BLUP/GWS). Simulations were performed by software R to provide correlations concerning ANN and RR-BLUP/GWS. The prediction methods were evaluated using correlations between phenotypic and genotypic values and predicted GEBV. The results showed the superiority of the ANN in predicting GEBV in simulations with higher and lower marker densities, with higher levels of linkage disequilibrium and heritability.

Reliable information on vegetation cover and its dynamics over time is essential for managing life, resources, and supporting policies. Although many related initiatives have been undertaken in Brazil since the 1980s, knowledge about its dry forests is still limited. In this study, we address the drivers of deforestation and their threat to the Brazilian dry forest called Caatinga. We evaluated the land cover dynamics and landscape metrics in the watershed of the Pontal River, as it has become one of the most socially and environmentally important areas in Brazil. The overall process consists of a systematic sampling grid of hydrological samples, where Landsat images (1975 to 2013) combined with the FRAGSTATS package were used to evaluate landscape metrics indices for the Caatinga. Data showed that the relative area (RA) decreased from 90.25% to 60.98% over the 38-year period, while fragmentation (PD) presented an increasing bias. In addition, the spatial distribution of both indices became more heterogeneous and clustered in the north. We suggest that appropriateness of land for farming was the leading cause of deforestation; rainfall is 112% more intense in the north of the watershed than in the south. Therefore, the northern fauna and flora have been significantly altered and reduced. The relationship between deforestation and time shows an increasing threat. Further studies evaluating these causes are needed to improve our understanding of the vegetation dynamics in this region.

The objective of this study was to evaluate the productive and economic performance of a forage cactus and sorghum intercropping system in relation to a forage cactus single cropping system under different irrigation blades with saline water. The study was conducted in Serra Talhada, State of Pernambuco, in a randomized block design, consisting of a factorial arrangement with split-plot parcels (5×2) and four replications. The five plots were the irrigation depths based on the reference evapotranspiration (ETo) (0, 8.75, 17.5, 26.25, and 35% ETo) and the two cropping systems were single forage cactus cropping and cactus intercropped with sorghum. The experiment was conducted for one year, with one forage cactus cycle and two cycles of sorghum. Yields were obtained at the end of the cycles. Economic profitability was analyzed by means of net revenue (NR) and the benefit/cost ratio (B/C), with cactus forage sold as forage or as "seed" and sorghum as forage. Net revenue and B/C simulations were carried out over an eight-year useful life span of the irrigation system. Increasing irrigation depth increased the dry matter yield of the intercropping system because of higher sorghum yield. Based on the NR and B/C ratio values, forage cactus and sorghum produced as forage produced higher economic outcomes in the intercropping system and showed a higher profitability from the 2nd year of implementation of the irrigation system. Forage cactus and sorghum intercropping irrigated with saline water is therefore recommended for forage production in the Brazilian semi-arid region.