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.

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.

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.

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.

Rehabilitation with forage grasses of an area degraded by urban solid waste deposits

Dry matter yield and chemical composition of forage grasses harvested from an area degraded by urban solid waste deposits were evaluated. A split-plot scheme in a randomized block design with four replicates was used, with five grasses in the plots and three harvests in the subplots. The mineral content and extraction and heavy metal concentration were evaluated in the second cut, using a randomized block design with five grasses and four replicates. The grasses were Brachiaria decumbens cv. Basilisk, Brachiaria ruziziensis, Brachiaria brizantha cv. Marandu and cv. Xaraés, and Panicum maximum cv. Tanzânia, cut at 42 days of regrowth. The dry matter yield per cut reached 1,480 kg ha-1; the minimum crude protein content was 9.5% and the average neutral detergent fiber content was 62.3%. The dry matter yield of grasses was satisfactory, and may be an alternative for rehabilitating areas degraded by solid waste deposits. The concentration of heavy metals in the plants was below toxicity levels; the chemical composition was appropriate, except for phosphorus. The rehabilitated areas may therefore be used for grazing.

Different herbage allowances and milk yield in crossbred Holstein x Gir

The objective of this study was to evaluate different herbage allowances in stargrass (Cynodon nlemfuensis Vanderyst var. nlemfuensis), on the herbage disappearance rate (HDR) and milk yield in crossbred Holstein x Gir cows. Thirty animals were assigned to three different herbage allowances (HA), ranging from 10.0, 12.5 and 15.0% BW. There was effect of HA on the HDR ( P<0.001). Increasing the HA in one unit had effect on the HDR increasing by 140.0kg ha(-1) day(-1). There was effect of leaf: stem ratio on milk yield (P<0.05). The increasing in supplying herbage allowances did not resulted in increased milk yield because the management for herbage allowance and herbage growth.

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.

STOCHASTIC MODEL FOR SIMULATING MAIZE YIELD

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment.

Organic and inorganic sources of zinc, copper and selenium in diets for dairy cows: intake, blood metabolic profile, milk yield and composition

The present study was carried out with the objective of evaluating the effects of feeding dairy cows with organic or inorganic sources of zinc (Zn), copper (Cu) and selenium (Se) on blood concentrations of these minerals, blood metabolic profiles, nutrient intake and milk yield and composition. Nineteen Holstein cows were selected and randomly assigned to two groups for receiving organic (n = 9) or inorganic (n = 10) sources of Zn, Cu and Se from 60 days before the expected date of calving to 80 days of lactation. Samples of feed, orts and milk were collected for analysis. Body condition score (BCS) was determined and blood samples were collected for analysis of Zn, Cu and Se concentrations, as well as for metabolic profile. Supplying organic or inorganic sources of Zn, Cu, and Se did not affect dry matter and nutrient intake, blood metabolic profile, milk yield and composition, plasma concentration of these minerals, and BCS or change the BCS in cows from 60 days before the expected date of calving to 80 days of lactation. An effect of time was observed on all feed intake variables, plasma concentrations of Zn and Se, milk yield, milk protein content, BCS and change in BCS.

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.

The nitrogen sufficiency index underlying estimates of nitrogen fertilization requirements of common bean

Chlorophyll determination with a portable chlorophyll meter can indicate the period of highest N demand of plants and whether sidedressing is required or not. In this sense, defining the optimal timing of N application to common bean is fundamental to increase N use efficiency, increase yields and reduce the cost of fertilization. The objectives of this study were to evaluate the efficiency of N sufficiency index (NSI) calculated based on the relative chlorophyll index (RCI) in leaves, measured with a portable chlorophyll meter, as an indicator of time of N sidedressing fertilization and to verify which NSI (90 and 95 %) value is the most appropriate to indicate the moment of N fertilization of common bean cultivar Perola. The experiment was carried out in the rainy and dry growing seasons of the agricultural year 2009/10 on a dystroferric Red Nitosol, in Botucatu, São Paulo State, Brazil. The experiment was arranged in a randomized complete block design with five treatments, consisting of N managements (M1: 200 kg ha-1 N (40 kg at sowing + 80 kg 15 days after emergence (DAE) + 80 kg 30 DAE); M2: 100 kg ha-1 N (20 kg at sowing + 40 kg 15 DAE + 40 kg 30 DAE); M3: 20 kg ha-1 N at sowing + 30 kg ha-1 when chlorophyll meter readings indicated NSI < 95 %; M4: 20 kg ha-1 N at sowing + 30 kg ha-1 N when chlorophyll meter readings indicated NSI < 90 % and, M5: control (without N application)) and four replications. The variables RCI, aboveground dry matter, total leaf N concentration, production components, grain yield, relative yield, and N use efficiency were evaluated. The RCI correlated with leaf N concentrations. By monitoring the RCI with the chlorophyll meter, the period of N sidedressing of common bean could be defined, improving N use efficiency and avoiding unnecessary N supply to common bean. The NSI 90 % of the reference area was more efficient to define the moment of N sidedressing of common bean, to increase N use efficiency.