Dry matter production of Tanzania grass as a function of agrometeorological variables

The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry-field conditions in Sao Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree-days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in Sao Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree-days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.

Validation of models for predicting milk urea nitrogen concentrations, estimating dry matter intake by the NRC (2001)

The objective of this study was to validate three different models for predicting milk urea nitrogen using field conditions, attempting to evaluate the nutritional adequacy diets for dairy cows and prediction of nitrogen excreted to the environment. Observations (4,749) from 855 cows were used. Milk yield, body weight (BW), days in milk and parity were recorded on the milk sampling days. Milk was sampled monthly, for analysis of milk urea nitrogen (MUN), fat, protein, lactose and total solids concentration and somatic cells count. Individual dry matter intake was estimated using the NRC (2001). The three models studied were derived from a first one to predict urinary nitrogen (UN). Model 1 was MUN = UN/12.54, model 2 was MUN = UN/17.6 and model 3 was MUN = UN/(0.0259 × BW), adjusted by body weight effect. To evaluate models, they were tested for accuracy, precision and robustness. Despite being more accurate (mean bias = 0.94 mg/dL), model 2 was less precise (residual error = 4.50 mg/dL) than model 3 (mean bias = 1.41 and residual error = 4.11 mg/dL), while model 1 was the least accurate (mean bias = 6.94 mg/dL) and the least precise (residual error = 5.40 mg/dL). They were not robust, because they were influenced by almost all the variables studied. The three models for predicting milk urea nitrogen were different with respect to accuracy, precision and robustness.

Efeitos gênicos de caracteres associados à eficiência no uso de nitrogênio em milho

Os objetivos deste trabalho foram determinar o controle genético da eficiência no uso do nitrogênio (EUN), identificar a importância das eficiências na absorção (EAN) e na utilização (EUtN) na sua composição,  e quantificar relação entre produção de matéria seca da parte aérea (MPS) e do sistema radicular com a EUN e  com seus componentes. Foram avaliadas 41 combinações híbridas em duas disponibilidades de N: baixa (BN)  e alta (AN). Utilizou-se o delineamento de blocos ao acaso com duas repetições, em arranjo fatorial simples  (combinação híbrida x disponibilidade de N). As análises estatísticas foram realizadas por meio das equações  de modelos mistos. Correlações de elevada magnitude foram detectadas entre EAN e EUN, bem como entre  essas eficiências e a MPS, tanto em BN como em AN. Em ambas as disponibilidades de N, efeitos genéticos  aditivos apresentaram maior importância para os caracteres associados à EUN. Dessa forma, a seleção baseada  no desempenho individual de linhagens quanto à MPS pode possibilitar a obtenção de genótipos com alta  EUN. Independentemente da disponibilidade de N, a EAN é o componente mais importante da EUN.

DEFICIENCY SYMPTOMS AND UPTAKE OF MICRONUTRIENTS BY CASTOR BEAN GROWN IN NUTRIENT SOLUTION

Castor bean is a nutrient-demanding species, but there is still little information on its micronutrient requirements. The objectives of this study were to evaluate the effects of levels of B (2.5, 12.5 and 25.0 mu mol L-1), Cu (0.05, 0.25 and 0.50 mu mol L-1), Mn (0.2, 1.0 and 2.0 mu mol L-1) and Zn (0.2, 1.0 and 2.0 mu mol L-1) in a nutrient solution on plant B, Cu, Mn and Zn concentrations and uptake, vegetative growth and fruit yield of castor bean "Iris", grown in greenhouse. The experiment was arranged in a completely randomized block design with three replicates. The first deficiency symptoms were observed for B, followed by Zn, Cu and Mn. The main changes in the cell ultrastructure due to lack of B were thickening of the cell walls and middle lamellae, distorted chloroplasts and tightly stacked thylakoids, besides the absence of starch grains. The Mn, Zn and Cu deficiencies led to disruption of chloroplasts, disintegration of thylakoids and absence of amyloplasts. The concentration and uptake of B, Cu, Mn, and Zn in castor bean plants increased with micronutrient supply in the solution. Fruit yield was drastically reduced by B and Mn deficiencies. On the other hand, the dry matter yield of the shoot and root of castor bean plants was not. In the treatment with full nutrient solution, the leaves accumulated 56 and 48 % of the total B and Mn taken up by the plants, respectively, and the seeds and roots 85 and 61 % of the total Cu and Zn taken up, respectively. This shows the high demand of castor bean Iris for B and Mn for fruit yield.

Predicting Growth of Panicum maximum: An Adaptation of the CROPGRO-Perennial Forage Model

Warm-season grasses are economically important for cattle production in tropical regions and tools to aid in management and research on these forages would be highly beneficial both in research and the industry. This research was conducted to adapt the CROPGRO-Perennial Forage model to simulate growth of the tropical species guineagrass (Panicum maximum Jacq. cv. 'Tanzania') and to describe model adaptation for this species. To develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation, and partitioning during a 17-mo experiment with Tanzania guineagrass in Piracicaba, SP, Brazil. Compared with starting parameters for palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. 'Xaraes'], dormancy effects of the perennial forage model had to be minimized, partitioning to storage tissue or root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield was 6576 kg ha(-1), averaged across 11 regrowth cycles of 35 (summer) or 63 d (winter), with a RMSE of 494 kg ha(-1) (Willmott's index of agreement d = 0.985, simulated/observed ratio = 1.014). The model also gave good predictions against an independent data set, with similar RMSE, ratio, and d. The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of guineagrass and can be used to simulate growth.

Long-term decomposition of sugarcane harvest residues in Sao Paulo state, Brazil

Crop residues returned to the soil are important to preserve fertility and sustainability. This research addressed the long-term decomposition of sugarcane post-harvest residues (trash) under reduced tillage, therefore field renewal was performed with herbicide followed by subsoiling and ratoons were deprived of interrow scarification. The trial was conducted in the northern Sao Paulo State, Brazil during four consecutive crops (2005-2008) where litter bags containing N-15-labeled trash were disposed in the field attempting to simulate two distinct situations: the previous crop trash (PCT) or residues incorporated in the field after tillage, and post-harvest trash (PHT) or the remains of plant-cane harvest. Decomposition rates regarding dry matter (DM), carbon (C), root growth, plant nutrients (N, P, K, Ca, Mg and S), lignin (LIG) cellulose (CEL) and hemicellulose (HCEL) contents were assessed for PCT (2005 ndash;2008) and for PHT (2006-2008). There were significant reductions on DM and C:N ratio due to C losses and root growth within the litter bags over time. The DM from PCT and PHT decreased 96% and 73% after four and three crops, respectively, and the higher nutrients release were found for K, Ca and N. The LIG, CEL and HCEL concentrations in PCT decreased 60%, 29%, 70% after four crops and 47%, 35%, 70% from PHT after three crops, respectively. Trash decomposition was driven mainly by residues biochemical composition, root growth within the trash blanket and the climatic conditions during the crop cycles. (C) 2012 Elsevier Ltd. All rights reserved.

Deficiency symptoms and uptake of micronutrients by castor bean grown in nutrient solution

Castor bean is a nutrient-demanding species, but there is still little information on its micronutrient requirements. The objectives of this study were to evaluate the effects of levels of B (2.5, 12.5 and 25.0 µmol L-1), Cu (0.05, 0.25 and 0.50 µmol L-1), Mn (0.2, 1.0 and 2.0 µmol L-1) and Zn (0.2, 1.0 and 2.0 µmol L-1) in a nutrient solution on plant B, Cu, Mn and Zn concentrations and uptake, vegetative growth and fruit yield of castor bean "Iris", grown in greenhouse. The experiment was arranged in a completely randomized block design with three replicates. The first deficiency symptoms were observed for B, followed by Zn, Cu and Mn. The main changes in the cell ultrastructure due to lack of B were thickening of the cell walls and middle lamellae, distorted chloroplasts and tightly stacked thylakoids, besides the absence of starch grains. The Mn, Zn and Cu deficiencies led to disruption of chloroplasts, disintegration of thylakoids and absence of amyloplasts. The concentration and uptake of B, Cu, Mn, and Zn in castor bean plants increased with micronutrient supply in the solution. Fruit yield was drastically reduced by B and Mn deficiencies. On the other hand, the dry matter yield of the shoot and root of castor bean plants was not. In the treatment with full nutrient solution, the leaves accumulated 56 and 48 % of the total B and Mn taken up by the plants, respectively, and the seeds and roots 85 and 61 % of the total Cu and Zn taken up, respectively. This shows the high demand of castor bean Iris for B and Mn for fruit yield.

Accuracy, precision and robustness of different methods to obtain samples from silages in fermentation studies

The objective of this study was to evaluate accuracy, precision and robustness of two methods to obtain silage samples, in comparison with extraction of liquor by manual screw-press. Wet brewery residue alone or combined with soybean hulls and citrus pulp were ensiled in laboratory silos. Liquor was extracted by a manual screw-press and a 2-mL aliquot was fixed with 0.4 mL formic acid. Two 10-g silage samples from each silo were diluted in 20 mL deionized water or 17% formic acid solution (alternative methods). Aliquots obtained by the three methods were used to determine the silage contents of fermentation end-products. The accuracy of the alternative methods was evaluated by comparing mean bias of estimates obtained by manual screw-press and by alternative methods, whereas precision was assessed by the root mean square prediction error and the residual error. Robustness was determined by studying the interaction between bias and chemical components, pH, in vitro dry matter digestibility (IVDMD) and buffer capacity. The 17% formic acid method was more accurate for estimating acetic, butyric and lactic acids, although it resulted in low overestimates of propionic acid and underestimates of ethanol. The deionized water method overestimated acetic and propionic acids and slightly underestimated ethanol. The 17% formic acid method was more precise than deionized water for estimating all organic acids and ethanol. The robustness of each method with respect to variation in the silage chemical composition, IVDMD and pH is dependent on the fermentation end-product at evaluation. The robustness of the alternative methods seems to be critical at the determination of lactic acid and ethanol contents.