994 resultados para Crop yield forecasting
Resumo:
This paper presents the results of four field experiments carried out with the objetive of evaluating the feaibility of irrigation by porous capsule method, from 1979 to 1983, at Bebedouro Experiment Station, EMBRAPA-CPATSA, Petrolina, PE, Brazil. The irrigation system consisted of fulcrum of cone shaped porous capsules, interconnected with conduit pipe and installed in the soil at equidistance and 0.10 m deep along contour lines. The hydrostatic pressures studies did not significantly influence the crop yield, but influenced, at 0.10 level, the daily water release from porous unit. The mean yields for watermelon (Citrullus vulgaris Shard), var. Charleston Gray, for muskmelon (Cucumis melo L.) var. Valenciano Amarelo, and for maize (Zea mays L.), var. Centralmex, estimated in ton/2,500 units/ha or in cobs/2,500 units/ha, were 28.5, 10 and 17,500, respectively. The water consumption for watermelon, musk melon and maize was, respectively, 60 mm, 60 mm and 100 mm in a deep sandy yellow-red latosol. The cost of the system was US$ 1.677,41/ha.
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Banana is one of the most consumed fruits in the world, which is grown in most tropical countries. The objective of this work was to evaluate the main attributes of soil fertility in a banana crop under two cover crops and two root development locations. The work was conducted in Curaçá, BA, Brazil, between October 2011 and May 2013, using a randomized block design in split plot with five repetitions. Two cover crops were assessed in the plots, the cover 1 consisting of Pueraria phaseoloid es, and the cover 2 consisting of a crop mix with Sorghum bicolor, Ricinus commun is L., Canavalia ensiform is, Mucuna aterrima and Zea mays, and two soil sampling locations in the subplots, between plants in the banana rows (location 1) and between the banana rows (location 2). There were significant and independent effects for the cover crop and sampling location factors for the variables organic matter, Ca and P, and significant effects for the interaction between cover crops and sampling locations for the variables potassium, magnesium and total exchangeable bases. The cover crop mix and the between-row location presented the highest organic matter content. Potassium was the nutrient with the highest negative variation from the initial content and its leaf content was below the reference value, however not reducing the crop yield. The banana crop associated with crop cover using the crop mix provided greater availability of nutrients in the soil compared to the coverage with tropical kudzu.
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Water is one of the most important factors influencing crop production in rainfed cropping systems. In tropical regions, supplemental irrigation reduces the risk of yield losses associated to water deficit due to insufficient rainfall. Water deficit in regions with irregularities in rainfall may be overcome with the use of supplemental irrigation, a technique based on the application of water at amounts below the crop?s evapotranspiration (ETc). We investigated the potential of supplemental irrigation as a strategy to increase yield of maize grown under tropical conditions. We used the CSM-CERES-Maize model of the Decision Support System for Agrotechnology Transfer (DSSAT) to simulate irrigation strategies of maize in six counties in the state of Minas Gerais, Brazil. Our results indicate significant differences on simulated crop yield in response to supplemental irrigation. As a consequence, water productivity was improved with reductions of 10% and 15% of full irrigation depths in one of the six counties while in two the water productivity was higher when full irrigation was applied.
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Composting is a useful way of transforming livestock waste into organic fertilizer, which is proven to increase soil nutrient levels, and thus crop yield. Remains from production and slaughter of small ruminants can become a source of important elements for plant growth, such as N, after microorganism-driven decomposition.The aim of this investigation was to evaluate the effects of this compost on soil fertility and on the nutritional status and yield of the corn crop. The experiment was conducted in a Haplic Luvisol in a randomized block design with six treatments and five application rates of the organic compound in Mg ha-1: 3 (half the standard rate), 6 (standard rate), 9 (one and a half times the standard rate), 12 (twice the standard rate), and 24 (four times the standard rate) and an additional treatment with mineral fertilizers (110, 50 e 30 kg ha-1 of N, P2O5 and K2O, respectively), with four blocks. Evaluations were performed for two harvests of rainfed crops, measuring soil fertility, nutritional status, and grain yield. The compost increased P, K, Na and Zn values in the 0.00-0.20 m layer in relation of mineral fertilization in 616, 21, 114 and 90 % with rate 24 Mg ha-1 in second crop. Leaf N, Mg, and S contents, relative chlorophyll content, and the productivity of corn kernels increased in 27, 32, 36, 20 e 85 %, respectively, of low rate (3 Mg ha-1) to high rate (24 Mg ha-1) with of application of the compost. Corn yield was higher with application of organic compost in rate of 24 Mg ha-1 than mineral fertilizer combination in second crop.
Forecasting regional crop production using SOI phases: an example for the Australian peanut industry
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Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.
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Sorghum is the main dryland summer crop in NE Australia and a number of agricultural businesses would benefit from an ability to forecast production likelihood at regional scale. In this study we sought to develop a simple agro-climatic modelling approach for predicting shire (statistical local area) sorghum yield. Actual shire yield data, available for the period 1983-1997 from the Australian Bureau of Statistics, were used to train the model. Shire yield was related to a water stress index (SI) that was derived from the agro-climatic model. The model involved a simple fallow and crop water balance that was driven by climate data available at recording stations within each shire. Parameters defining the soil water holding capacity, maximum number of sowings (MXNS) in any year, planting rainfall requirement, and critical period for stress during the crop cycle were optimised as part of the model fitting procedure. Cross-validated correlations (CVR) ranged from 0.5 to 0.9 at shire scale. When aggregated to regional and national scales, 78-84% of the annual variation in sorghum yield was explained. The model was used to examine trends in sorghum productivity and the approach to using it in an operational forecasting system was outlined. (c) 2005 Elsevier B.V. All rights reserved.
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This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.
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Seasonal climate forecasting offers potential for improving management of crop production risks in the cropping systems of NE Australia. But how is this capability best connected to management practice? Over the past decade, we have pursued participative systems approaches involving simulation-aided discussion with advisers and decision-makers. This has led to the development of discussion support software as a key vehicle for facilitating infusion of forecasting capability into practice. In this paper, we set out the basis of our approach, its implementation and preliminary evaluation. We outline the development of the discussion support software Whopper Cropper, which was designed for, and in close consultation with, public and private advisers. Whopper Cropper consists of a database of simulation output and a graphical user interface to generate analyses of risks associated with crop management options. The charts produced provide conversation pieces for advisers to use with their farmer clients in relation to the significant decisions they face. An example application, detail of the software development process and an initial survey of user needs are presented. We suggest that discussion support software is about moving beyond traditional notions of supply-driven decision support systems. Discussion support software is largely demand-driven and can compliment participatory action research programs by providing cost-effective general delivery of simulation-aided discussions about relevant management actions. The critical role of farm management advisers and dialogue among key players is highlighted. We argue that the discussion support concept, as exemplified by the software tool Whopper Cropper and the group processes surrounding it, provides an effective means to infuse innovations, like seasonal climate forecasting, into farming practice. Crown Copyright (C) 2002 Published by Elsevier Science Ltd. All rights reserved.
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Spatial and temporal variability in wheat production in Australia is dominated by rainfall occurrence. The length of historical production records is inadequate, however, to analyse spatial and temporal patterns conclusively. In this study we used modelling and simulation to identify key spatial patterns in Australian wheat yield, identify groups of years in the historical record in which spatial patterns were similar, and examine association of those wheat yield year groups with indicators of the El Nino Southern Oscillation (ENSO). A simple stress index model was trained on 19 years of Australian Bureau of Statistics shire yield data (1975-93). The model was then used to simulate shire yield from 1901 to 1999 for all wheat-producing shires. Principal components analysis was used to determine the dominating spatial relationships in wheat yield among shires. Six major components of spatial variability were found. Five of these represented near spatially independent zones across the Australian wheatbelt that demonstrated coherent temporal (annual) variability in wheat yield. A second orthogonal component was required to explain the temporal variation in New South Wales. The principal component scores were used to identify high- and low-yielding years in each zone. Year type groupings identified in this way were tested for association with indicators of ENSO. Significant associations were found for all zones in the Australian wheatbelt. Associations were as strong or stronger when ENSO indicators preceding the wheat season (April-May phases of the Southern Oscillation Index) were used rather than indicators based on classification during the wheat season. Although this association suggests an obvious role for seasonal climate forecasting in national wheat crop forecasting, the discriminatory power of the ENSO indicators, although significant, was not strong. By examining the historical years forming the wheat yield analog sets within each zone, it may be possible to identify novel climate system or ocean-atmosphere features that may be causal and, hence, most useful in improving seasonal forecasting schemes.
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Decomposing crop residues in no-tillage system can alter soil chemical properties, which may consequently influence the productivity of succession crops. The objective of this study was to evaluate soil chemical properties and soybean, maize and rice yield, grown in the summer, after winter crops in a no-tillage system. The experiment was carried out in Jaboticabal, SP, Brazil (21 ° 15 ' 22 '' S; 48 ° 18 ' 58 '' W) on a Red Latosol (Oxisol), in a completely randomized block design, in strip plots with three replications. The treatments consisted of four summer crop sequences (maize monocrop, soybean monocrop, soybean/maize rotation and rice/bean/cotton rotation) combined with seven winter crops (maize, sunflower, oilseed radish, pearl millet, pigeon pea, grain sorghum and sunn hemp). The experiment began in September 2002. After the winter crops in the 2005/2006 growing season and before the sowing of summer crops in the 2006/2007 season, soil samples were collected in the layers 0-2.5; 2.5-5.0; 5-10; 10-20; and 20-30 cm. Organic matter, pH, P, K+, Ca2+, Mg2+, and H + Al were determined in each soil sample. In the summer soybean/maize rotation and in maize the organic matter contents and P levels were lower, in the layers 0-10 cm and 0-20 cm, respectively. Summer rice/bean/cotton rotation increased soil K levels at 0-10 cm depth when sunn hemp and oilseed radish had previously been grown in the winter, and in the 0-2.5 cm layer for millet. Sunn hemp, millet, oilseed radish and sorghum grown in the winter increased organic matter contents in the soil down to 30 cm. Higher P levels were found at the depths 0-2.5 cm and 0-5 cm, respectively, when sunn hemp and oilseed radish were grown in the winter. Highest grain yields for soybean in monoculture were obtained in succession to winter oilseed radish and sunn hemp and in rotation with maize, after oilseed radish, sunn hemp and millet. Maize yields were highest in succession to winter oilseed radish, millet and pigeon pea. Rice yields were lowest when grown after sorghum.
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The objective of this work was to evaluate the effects of preceding crops and tillage systems on the incidence of Fusarium wilt (Fusarium oxysporum f. sp. phaseoli) and common bean (Phaseolus vulgaris) yield. The cultivar BRS Valente was cultivated under center‑pivot irrigation in the winter seasons of 2003, 2004 and 2005, after several preceding crops established in the summer seasons. Preceding crops included the legumes Cajanus cajan (pigeon pea), Stylosanthes guianensis, and Crotalaria spectabilis; the grasses Pennisetum glaucum (millet), Sorghum bicolor (forage sorghum), Panicum maximum, and Urochloa brizantha; and a consortium of maize (Zea mays) and U. brizantha (Santa Fé system). Experiments followed a strip‑plot design, with four replicates. Fusarium wilt incidence was higher in the no‑tillage system. Higher disease incidences corresponded to lower bean yields in 2003 and 2004. Previous summer cropping with U. brizantha, U. brizantha + maize consortium, and millet showed the lowest disease incidence. Therefore, the choice of preceding crops must be taken into account for managing Fusarium wilt on irrigated common bean crops in the Brazilian Cerrado.
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The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km²), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km²). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives.
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The use of saline water and the reuse of drainage water for irrigation depend on long-term strategies that ensure the sustainability of socio-economic and environmental impacts of agricultural systems. In this study, it was evaluated the effects of irrigation with saline water in the dry season and fresh water in the rainy season on the soil salt accumulation yield of maize and cowpea, in a crop rotation system. The experiment was conducted in the field, using a randomized complete block design, with five replications. The first crop was installed during the dry season of 2007, with maize irrigated with water of different salinities (0.8, 2.2, 3.6 and 5.0 dS m-1). The maize plants were harvested at 90 days after sowing (DAS), and vegetative growth, dry mass of 1000 seeds and grain yield were evaluated. The same plots were utilized for the cultivation of cowpea, during the rainy season of 2008. At the end of the crop, cycle plants of this species were harvested, being evaluated the vegetative growth and plant yield. Soil samples were collected before and after maize and cowpea cultivation. The salinity of irrigation water above 2.2 dS m-1 reduced the yield of maize during the dry season. The high total rainfall during the rainy season resulted in leaching of salts accumulated during cultivation in the dry season, and eliminated the possible negative effects of salinity on cowpea plants. However, this crop showed atypical behavior with a significant proportion of vegetative mass and low pod production, which reduced the efficiency of this strategy of crop rotation under the conditions of this study.
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The objective of this study was to evaluate the use of subsoiling, gypsum and organic matter associated with the cultivation of cotton, sunflower and cowpea in crop rotation, seeking the reclamation and use of a saline-sodic soil. The treatments were arranged in a randomized block design in split plots with four replications, during two crop cycles (2009/2010 and 2010/2011). The plots were formed by the treatments: T1. Subsoiling (S); T2. S + 20 Mg ha-1 of gypsum; T3. S + 40 Mg ha-1 of organic matter; T4. S + 10 Mg ha-1 of gypsum + 20 Mg ha-1 of organic matter; T5. S + 20 Mg ha-1 of gypsum + 40 Mg ha-1 of organic matter and the sub-plots consisted of the cotton-cowpea (C/CP) and sunflower-cowpea (S/CP) crop rotation. The use of gypsum and organic matter contributed to decrease the soil salinity and sodicity. Cotton was not affected by the treatments, while the sunflower crop was favored by the application of amendments only in the second production cycle. Higher yields of cowpea in T5 treatment, during the 2009/2010 cycle, are indicative that higher doses of gypsum and organic matter applied in this treatment accelerate the reclamation process. For other treatments with amendment application there was a beneficial effect for this crop only in the second cycle, when the values of productivity were similar to T5.