972 resultados para Forage yield variability


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The objective of this study was to analyze variability, linear and spatial correlations of forage dry mass yield (FDM) and dry matter percentage (DM%) of Brachiaria decumbens with the bulk density (BD), gravimetric (GM) and volumetric (VM) moisture, mechanical resistance to penetration (RP) and organic matter content (OM), at depths 1 (0-0.10 m) and 2 (0.10-0.20 m), in a Red Latosol (Oxisol), in order to select an indicator of soil physical quality and identify possible causes of pasture degradation. The geostatistical grid was installed to collect soil and plant data, with 121 sampling points, over an area of 2.56 ha. The linear correlation between FDM × DM% and FDM × BD2 was low, but highly significant. Spatial correlations varied inversely and positively, respectively. Except for DM% and BD, at both depths, the other attributes showed average to high variability, indicating a heterogeneous environment. Thus, geostatistics emerges as an important tool in understanding the interactions in pasture ecosystems, in order to minimize possible causes of degradation and indicate better alternatives for soil-plant-animal management. The decrease in FDM and increased BD1 are indicators of physical degradation (compaction) of Red Latosol (Oxisol), particularly in the places with the highest concentration of animals and excessive trampling, in Cerrado conditions, in the municipality of Selvíria, Mato Grosso do Sul State, Brazil.

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Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m(2) in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500 °C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVInov) and 10 December 2014 (NDVIdec) because the potential AB was highly associated with NDVInov and NDVIdec (r (2) = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVInov and NDVIdec, respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass.

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Low variability of crop production from year to year is desirable for many reasons, including reduced income risk and stability of supplies. Therefore, it is important to understand the nature of yield variability, whether it is changing through time, and how it varies between crops and regions. Previous studies have shown that national crop yield variability has changed in the past, with the direction and magnitude dependent on crop type and location. Whilst such studies acknowledge the importance of climate variability in determining yield variability, it has been assumed that its magnitude and its effect on crop production have not changed through time and, hence, that changes to yield variability have been due to non-climatic factors. We address this assumption by jointly examining yield and climate variability for three major crops (rice, wheat and maize) over the past 50 years. National yield time series and growing season temperature and precipitation were de-trended and related using multiple linear regression. Yield variability changed significantly in half of the crop–country combinations examined. For several crop–country combinations, changes in yield variability were related to changes in climate variability.

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Forage plants, particularly the Brachiaria genus, are the main source of nutrients for cattle and are at times the only feed offered. The concentration of elements in the plant is related to the soil, fertilization, climate, season, variety, and cultural practices. An experiment on dystrophic Red-Yellow Latosol soil in Aracatuba, São Paulo was performed to evaluate the effects of the doses and sources of nitrogen fertilizers on the chemical properties of the soil and the dry matter yield of the grass Brachiaria brizantha cv. Xaraes. A randomized block design was employed involving three replicates in a 3 x 3 factorial, with three doses (100, 200 and 400 kg ha(-1) year(-1)) and three sources (Ajifer (R) L40, ammonium sulfate and urea) of nitrogen and a control treatment without nitrogen (zero). The greatest effects on the chemical properties of the soil as a function of nitrogen fertilization in the Xaraes grass were observed in the topsoil. The use of Ajifer (R) L40 and ammonium sulfate as sources of nitrogen had similar effects, with an increase in the sulfur content and a reduction in the soil pH at the superficial layer. The use of the fertilizers Ajifer (R) L40, ammonium sulfate and urea did not affect the micronutrient contents, except for Fe and Mn, and did not alter the sodium concentration or electrical conductivity of the soil. The dry matter yield of Xaraes grass was similar for all three nitrogen sources.

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Proanthocyanidins (PAs) in sainfoin (Onobrychis viciifolia Scop.) are of interest to ameliorate the sustainability of livestock production. However, sainfoin forage yield and PA concentrations, as well as their composition, require optimization. Individual plants of 27 sainfoin accessions from four continents were analyzed with LC-ESI-QqQ-MS/MS for PA concentrations and simple phenolic compounds. Large variability existed in PA concentrations (23.0–47.5 mg g–1 leaf dry matter (DM)), share of prodelphinidins (79–96%), and mean degree of polymerization (11–14) among, but also within, accessions. PAs were mainly located in leaves (26.8 mg g–1 DM), whereas stems had less PAs (7.8 mg g–1 DM). Overall, high-yielding plants had lower PA leaf concentrations (R2 = 0.16, P < 0.001) and fewer leaves (R2 = 0.66, P < 0.001). However, the results show that these two trade-offs between yield and bioactive PAs can be overcome.

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The CERES-Maize model was used to estimate the spatial variability in corn (Zea mays L.) yield for 1995 and 1996 using data measured on soil profiles located on a 30.5 m grid within a 3.9 ha field in Michigan. The model was calibrated for one grid profile for the 1995 and then used to simulate corn yield for all grid points for the 2 yrs. For the calibration for 1995, the model predicted corn yield within 2%. For 1995, the model predicted yield variability very well (r(2) = 0.85), producing similar yield maps with differences generally within +/- 300 kg ha(-1). For 1996, the model predicted low grain yields (1167 kg ha(-1)) compared with measured (8928 kg ha(-1)) because the model does not account for horizontal water movement within the landscape or water contributions from a water table. Under nonlimiting water conditions, the model performed well (average of 8717 vs. 8948 kg ha(-1)) but under-estimated the measured yield variability.

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The present study set out to test the hypothesis through field and simulation studies that the incorporation of short-term summer legumes, particularly annual legume lablab (Lablab purpureus cv. Highworth), in a fallow-wheat cropping system will improve the overall economic and environmental benefits in south-west Queensland. Replicated, large plot experiments were established at five commercial properties by using their machineries, and two smaller plot experiments were established at two intensively researched sites (Roma and St George). A detailed study on various other biennial and perennial summer forage legumes in rotation with wheat and influenced by phosphorus (P) supply (10 and 40 kg P/ha) was also carried out at the two research sites. The other legumes were lucerne (Medicago sativa), butterfly pea (Clitoria ternatea) and burgundy bean (Macroptilium bracteatum). After legumes, spring wheat (Triticum aestivum) was sown into the legume stubble. The annual lablab produced the highest forage yield, whereas germination, establishment and production of other biennial and perennial legumes were poor, particularly in the red soil at St George. At the commercial sites, only lablab-wheat rotations were experimented, with an increased supply of P in subsurface soil (20 kg P/ha). The lablab grown at the commercial sites yielded between 3 and 6 t/ha forage yield over 2-3 month periods, whereas the following wheat crop with no applied fertiliser yielded between 0.5 to 2.5 t/ha. The wheat following lablab yielded 30% less, on average, than the wheat in a fallow plot, and the profitability of wheat following lablab was slightly higher than that of the wheat following fallow because of greater costs associated with fallow management. The profitability of the lablab-wheat phase was determined after accounting for the input costs and additional costs associated with the management of fallow and in-crop herbicide applications for a fallow-wheat system. The economic and environmental benefits of forage lablab and wheat cropping were also assessed through simulations over a long-term climatic pattern by using economic (PreCAPS) and biophysical (Agricultural Production Systems Simulation, APSIM) decision support models. Analysis of the long-term rainfall pattern (70% in summer and 30% in winter) and simulation studies indicated that ~50% time a wheat crop would not be planted or would fail to produce a profitable crop (grain yield less than 1 t/ha) because of less and unreliable rainfall in winter. Whereas forage lablab in summer would produce a profitable crop, with a forage yield of more than 3 t/ha, ~90% times. Only 14 wheat crops (of 26 growing seasons, i.e. 54%) were profitable, compared with 22 forage lablab (of 25 seasons, i.e. 90%). An opportunistic double-cropping of lablab in summer and wheat in winter is also viable and profitable in 50% of the years. Simulation studies also indicated that an opportunistic lablab-wheat cropping can reduce the potential runoff+drainage by more than 40% in the Roma region, leading to improved economic and environmental benefits.

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Field studies were conducted over 5 years on two dairy farms in southern Queensland to evaluate the impacts of zero-tillage, nitrogen (N) fertiliser and legumes on a winter-dominant forage system based on raingrown oats. Oats was able to be successfully established using zero-tillage methods, with no yield penalties and potential benefits in stubble retention over the summer fallow. N fertiliser, applied at above industry-standard rates (140 vs. 55 kg/ha.crop) in the first 3 years, increased forage N concentration significantly and had residual effects on soil nitrate-N at both sites. At one site, crop yield was increased by 10 kg DM/ha. kg fertiliser N applied above industry-standard rates. The difference between sites in fertiliser response reflected contrasting soil and fertiliser history. There was no evidence that modifications to oats cropping practices (zero-tillage and increased N fertiliser) increased surface soil organic carbon (0-10 cm) in the time frame of the present study. When oats was substituted with annual legumes, there were benefits in improved forage N content of the oat crop immediately following, but legume yield was significantly inferior to oats. In contrast, the perennial legume Medicago sativa was competitive in biomass production and forage quality with oats at both sites and increased soil nitrate-N levels following termination. However, its contribution to winter forage was low at 10% of total production, compared with 40% for oats, and soil water reserves were significantly reduced at one site, which had an impact on the following oat production. The study demonstrated that productive grazed oat crops can be grown using zero tillage and that increased N fertiliser is more consistent in its effect on N concentration than on forage yield. A lucerne ley provides a strategy for raising soil nitrate-N concentration and increasing overall forage productivity, although winter forage production is reduced.

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Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.

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Em relação aos sistemas de manejo adotados pelo homem, a porosidade total e a densidade do solo são atributos ativamente alterados, refletindo decisivamente sobre a produtividade vegetal agrícola. No ano agrícola de 2005, na Fazenda Bonança, no município de Pereira Barreto, Estado de São Paulo, Brasil, foram analisadas a produtividade de forragem do milho outonal (MSF) no sistema plantio direto irrigado, a porosidade total (PT) e a densidade do solo (DS) em profundidade, em um Latossolo Vermelho distrófico. O objetivo foi estudar a variabilidade e as correlações lineares e espaciais entre os atributos da planta e do solo, visando selecionar um indicador da qualidade física do solo de boa representatividade para produtividade da forragem. Foi instalada a malha geoestatística, para coleta de dados do solo e planta, contendo 125 pontos amostrais, numa área de 2.500 m². Os atributos estudados, além de não terem variado aleatoriamente, apresentaram variabilidade dos dados entre média e baixa e seguiram padrões espaciais bem definidos, com alcance entre 6,8 e 23,7 m. Por sua vez, a correlação linear entre o atributo da planta e os do solo, em razão do elevado número de observações, foi baixa. As observações de melhor correlação com a MSF foram a DS1 e a PT1. Entretanto, do ponto de vista espacial, houve excelente correlação inversa entre a MSF e a DS1, assim como entre a DS1 e a PT1. Nos sítios onde a DS1 aumentou (1,45-1,64 kg dm-3) a MSF variou entre 11.653 e 14.552 kg ha-1; já naqueles onde diminuiu (1,35-1,45 kg dm-3) a MSF, ficou entre 14.552 e 17.450 kg ha-1. Portanto, a densidade global, avaliada na camada de 0-0,10 m (DS1), apresentou-se como satisfatório indicador da qualidade física do solo de Pereira Barreto (SP), quando destinado à produtividade de forragem do milho outonal.

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O conjunto de tecnologias aplicadas ao sistema de produção agrícola tem como características principais a verticalização da produtividade, diminuição de custos, melhoria nas características físicas, químicas e biológicas do solo para proporcionarem o crescimento sustentável do meio de produção. Desta forma, o trabalho teve como objetivo determinar a variabilidade e as correlações lineares e especiais entre os atributos da planta e do solo, visando selecionar um indicador da qualidade física do solo de boa representatividade para produção de forragem. No ano agrícola de 2006, na Fazenda Bonança, município de Pereira Barreto (SP), foram analisados a produtividade de forragem do milho outonal (FDM) em sistema plantio direto irrigado e os atributos físicos do solo, num Latossolo Vermelho distrófico. O objetivo foi estudar a variabilidade e as correlações lineares e espaciais entre os atributos da planta e os do solo, visando selecionar um indicador da qualidade física do solo de boa representatividade para a produtividade da forragem. Foi instalada a malha geoestatística, para coleta de dados do solo e planta, contendo 125 pontos amostrais, numa área de 2.500 m². Os atributos estudados, além de não terem variado aleatoriamente, apresentaram variabilidade dos dados entre baixa e muito alta e seguiram padrões espaciais bem definidos, com alcances entre 7,8 e 38,0 m. Por outro lado, a correlação linear entre os atributos da planta com o do solo foi baixa e extremamente significativa. Os pares Massa Seca de forragem versus Microporosidade e Diâmetro do colmo versus Densidade do Solo foram melhor correlacionados na camada de 0-0.10m, enquanto os outros pares - Massa Seca de Forragem versus Macroporosidade - e Porosidade Total - apresentaram correlação inversa para a mesma camada. Entretanto, do ponto de vista espacial, houve uma alta correlação inversa entre Massa Seca de Forragem com Microporosidade, de modo que a microporosidade na camada de 0-0.10m pode ser considerada um bom indicador de qualidade física do solo, tendo em vista a produção de forragem de milho.

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A porosidade do solo é de extrema importância à produtividade agrícola, uma vez que, em condições adversas, pode dificultar a penetração das raízes e, consequentemente, limitar o adequado aproveitamento dos nutrientes e da água disponível. Na Fazenda Bonança, em Pereira Barreto - SP, em 2005, foi analisada a produtividade de forragem do milho (MSF), a macroporosidade (MA), a microporosidade (MI) e a porosidade total (PT) de um Latossolo Vermelho distrófico (Acrustox Háplico), sob plantio direto, em três profundidades. O objetivo foi estudar as correlações lineares e espaciais entre os atributos da planta e do solo, na tentativa de selecionar, entre os do solo, um indicador da sua qualidade física de boa representatividade para a produtividade da forragem. Foi instalada a malha geoestatística para a coleta dos dados do solo e da planta, contendo 125 pontos amostrais numa área de 2.500 m². Os atributos estudados apresentaram variabilidade entre baixa e muito alta. Também, seguiram padrões espaciais claramente definidos, com alcances da dependência espacial entre 6,6 e 31,1 m. Apesar da correlação linear simples entre a MSF e a MI na profundidade de 0,10-0,20 m ter sido baixa, foi extremamente significativa. Contudo, do ponto de vista espacial, houve elevada correlação inversa entre tais variáveis. Assim, a MI2 apresentou-se como satisfatório indicador da qualidade física do solo de Pereira Barreto - SP, quando destinado à produtividade de forragem do milho.