YELLOW PASSION FRUIT PLANT NUTRITIONAL DIAGNOSIS AT DIFFERENT PHENOLOGICAL STAGES BY THE DIAGNOSIS AND RECOMMENDATION INTEGRATED SYSTEM METHOD

This work was performed in the Rio de Janeiro State, Brazil, with the objective to evaluate the nutritional status of yellow passion fruit plants along different phenological stages, using the DRIS method. Fifty-four passion fruit cultivated areas with an annual yield productivity ranging from 6.95 to 33.8 t ha^?1 year^?1 and average productivity of 16.9 t ha^?1 year^?1 were selected in the region. The contents of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), chlorine (Cl), iron (Fe), zinc (Zn), manganese (Mn), and boron (B) were evaluated. The reference standards were established (mean and variation coefficient) for the values of the nutrient concentration ratios, two by two, on samples from high yield productivity plantations and analyzed by the DRIS index of nutrients for the medium and low yield productivity areas. The established standards differed according with the phenological stage of the culture. In a general way, the mean content of the evaluated nutrients did not differed between the two productivity levels into each phonological stage. There was a difference for the Nutritional Limitation Order between different phenological stages of yellow passion fruit plants. The most negative DRIS indexes and the highest absolute values for the Average Nutritional Balance on yellow passion fruit plants in the region, were found for potassium in May, phosphorus in October and iron in January.     

Biochar as a strategy to manage plant diseases caused by pathogens inhabiting the soil: a critical review

Phytoparasitica - The current agricultural scenario faces a range of challenges, with phytosanitary ones being paramount. In most cases, plant diseases are treated with chemicals; however, they...     

Evaluation of Cymbopogon flexuosus and Alpinia zerumbet essential oils as biopesticides against Callosobruchus maculatus

Journal of Plant Diseases and Protection - This study aimed to investigate the effects of the essential oils of Cymbopogon flexuosus and Alpinia zerumbet in the treatment of cowpea [Vigna...     

Genetic diversity via REML-BLUP of ex situ conserved macauba [Acrocomia aculeata (Jacq.) Lodd. ex Mart.] ecotypes

Genetic Resources and Crop Evolution - Macauba [Acrocomia aculeata (Jacq.) Lodd. ex Mart.], a palm tree native to Brazil, has a high potential as an alternative source for vegetal oil production....     

Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?

Efficient computing techniques allow the estimation of variance components for virtually any traditional dataset. When genomic information is available, variance components can be estimated using genomic REML (GREML). If only a portion of the animals have genotypes, single-step GREML (ssGREML) is the method of choice. The genomic relationship matrix (G) used in both cases is dense, limiting computations depending on the number of genotyped animals. The algorithm for proven and young (APY) can be used to create a sparse inverse of G (GAPY~-1) with close to linear memory and computing requirements. In ssGREML, the inverse of the realized relationship matrix (H⁻¹) also includes the inverse of the pedigree relationship matrix, which can be dense with a long pedigree, but sparser with short. The main purpose of this study was to investigate whether costs of ssGREML can be reduced using APY with truncated pedigree and phenotypes. We also investigated the impact of truncation on variance components estimation when different numbers of core animals are used in APY. Simulations included 150K animals from 10 generations, with selection. Phenotypes (h² = 0.3) were available for all animals in generations 1–9. A total of 30K animals in generations 8 and 9, and 15K validation animals in generation 10 were genotyped for 52,890 SNP. Average information REML and ssGREML with G⁻¹ and GAPY~-1 using 1K, 5K, 9K, and 14K core animals were compared. Variance components are impacted when the core group in APY represents the number of eigenvalues explaining a small fraction of the total variation in G. The most time-consuming operation was the inversion of G, with more than 50% of the total time. Next, numerical factorization consumed nearly 30% of the total computing time. On average, a 7% decrease in the computing time for ordering was observed by removing each generation of data. APY can be successfully applied to create the inverse of the genomic relationship matrix used in ssGREML for estimating variance components. To ensure reliable variance component estimation, it is important to use a core size that corresponds to the number of largest eigenvalues explaining around 98% of total variation in G. When APY is used, pedigrees can be truncated to increase the sparsity of H and slightly reduce computing time for ordering and symbolic factorization, with no impact on the estimates.     

Agronomic performance and water-use efficiency of F3 soybean populations grown under contrasting base saturation

Most of the Brazilian soils, especially in Cerrado biome, have high acidity and toxic aluminium, making the application of limestone an indispensable technique to obtain high yield in soybean crop. The hypothesis of this study was that contrasting base saturation provides changes in water-use efficiency (WUE) and agronomic traits of soybean populations. Thus, we evaluated the WUE and agronomic performance of F₃ soybean populations under different base saturation levels. Each experiment was conducted in a randomized complete blocks design with three replicates and 10 F₃ populations (P1, P2, P3, P4, P5, P6, P7, P8, P9 and P10) for two crop seasons. Segregating populations were obtained by bulk method. In the first experiment, F₃ populations were evaluated without correction of base saturation (V = 30%), while in the second experiment, limestone was applied three months before sowing to increase base saturation to 60%. The traits evaluated were as follows: calcium, magnesium and potassium contents, water-use efficiency (WUE), plant height, first pod height, main stem diameter and grain yield. Our findings indicate that WUE and agronomic performance of F₃ soybean populations depends on the saturation condition. We identified the P4 and P9 populations as the most promising for use in breeding programmes aiming at higher tolerance to abiotic stress caused by low base saturation in soil.     

High levels of whole raw soya beans in dairy cow diets: digestibility and animal performance

The aim of this study was to evaluate the effects of high levels of whole raw soya beans in the diets of lactating cows. Twelve Holstein dairy cows were used, randomized in three 4 ×  4 balanced and contemporary Latin squares and fed the following diets: (i) control (C), without including whole raw soya beans; (ii) 80 g/kg in DM of whole raw soya beans (G80); (iii) 160 g/kg in DM of whole raw soya beans (G160); and (iv) 240 g/kg in DM of whole raw soya beans (G240). There was significant reduction (p < 0.05) in dry matter intake (kg/day) in cows supplemented with G240 compared with C (23.8 vs. 25.3 respectively). G240 diets presented lower crude protein digestibility (g/kg) (p < 0.05) in comparison with C diet (683 vs. 757 respectively). There was significant effect of experimental rations in nitrogen balance (p < 0.05), G240 diet presenting significant reduction in comparison with the other diets, and faecal excretion of nitrogen was higher for G240 diet. The concentration of ruminal ammoniacal nitrogen was significantly higher (p < 0.05) for cows receiving control diet, compared to other diets. G240 diet resulted in significantly lower milk and protein yield (p < 0.05) in comparison with C diet. Significant C18:2 cis fatty acids were observed in milk concentrations (p < 0.05) for G240 diet. The use of high level of whole raw soya beans in dairy cow diets improves the unsaturated fatty acid profile in milk, and the diets (G80 and G160) led to minor alterations in the digestive processes and animal metabolism.     

Effect of adding crude glycerine to diets with feed additives on the feed intake,ruminal degradability,volatile fatty acid concentrations and in vitro gas production of feedlot Nellore cattle

The effects of adding crude glycerine with sodium monensin or essential oils to beef cattle diets on the intake, degradability of DM and nutrients, rumen concentration of volatile fatty acids (VFA) and in vitro gas production were evaluated. Five ruminally cannulated Nellore steers were randomly assigned to a 5 × 5 Latin square design. The treatments were as follows: CONT, without crude glycerine and additives; EO, with essential oils and without crude glycerine; MON, with sodium monensin and without crude glycerine; EOG, with essential oils and crude glycerine; MONG, with sodium monensin and crude glycerine. Treatments with essential oil and sodium monensin increased the NDF and STC intake and the DM degradability. When crude glycerine was combined with either sodium monensin or essential oil, there was a reduction in DM, NDF and STC intake and an increase in DM and CP degradability of the diets. The adding crude glycerine to essential oil diets reduced the CH₄ production. Sodium monensin treatments reduced DM and NDF intake and the production of total gas, CH₄, total VFA and acetic acid concentration. In conclusion, the adding crude glycerine (200 g/kg DM) with either sodium monensin (0.03 g/kg DM) or essential oil (0.5 g/kg DM) can be utilized in diets for Nellore cattle without causing detrimental effects on feed intake and improving the DM degradability.     

Accounting for population structure in selective cow genotyping strategies

The objective of the present study was to investigate the impact of considering population structure in cow genotyping strategies over the accuracy and bias of genomic predictions. A small dairy cattle population was simulated to address these objectives. Based on four main traditional designs (random, top‐yield, extreme‐yield and top‐accuracy cows), different numbers (1,000; 2,000 and 5,000) of cows were sampled and included in the reference population. Traditional designs were replicated considering or not population structure and compared among and with a reference population containing only bulls. The inclusion of cows increased accuracy in all scenarios compared with using only bulls. Scenarios accounting for population structure when choosing cows to the reference population slightly outperformed their traditional versions by yielding higher accuracy and lower bias in genomic predictions. Building a cow‐based reference population from groups of related individuals considering the frequency of individuals from those same groups in the validation population yielded promising results with applications on selection for expensive‐ or difficult‐to‐measure traits. Methods here presented may be easily implemented in both new or already established breeding programs, as they improved prediction and reduced bias in genomic evaluations while demanding no additional costs.     

Environmental factors that influence milk production of Pantaneiro ewes and the weight gain of their lambs during the pre-weaning period

The main objective of this research was to conduct an exploratory study of the lactation curve in order to characterize the productive potential of Pantaneiro ewes and lambs. Fifty ewes were bred using four rams in two different mating seasons. The ewes were kept with their lambs on pasture of Brachiaria brizantha. Ewe body score, ewe weight, and lamb weight were evaluated. Milk sampling was performed every week. In the morning for milk collections, the ewes were treated with 1 UI of oxytocin (intramuscular) for complete milking. Lambs were separated from the ewes for 4 h and milk collections were performed. The total milk production over 24 h was estimated by multiplying the production of this period (4 h) by 6. The data were analyzed using the MIXED procedure (P?<?0.05) in SAS. Milk production data were fitted to the curve using the incomplete gamma function of Wood, and lamb growth data were fitted using the Gompertiz equation. The average milk production of the ewes was 1.03 kg/day^?1. Younger ewes had the lowest milk production (18?=?798?±?330, 24?=?1001?±?440, 36?=?1100?±?490, and 48?=?1106?±?490 g/day^?1). Ewe body score at lambing affected initial milk production (1.0?=?816?±?660, 1.5?=?1089?±?105, and 2.0?=?1424?±?1600 g/day^?1). Lambs were weaned with an average weight of 20.3 kg. Daily weight gain from birth to weaning was 181 g. Locally adapted Pantaneiro ewes showed a linear decreasing lactation curve, with reduced production from the second week of lactation. Overall, evaluation of the dairy production and lamb performance revealed great variation, denoting potential for selection.