994 resultados para crop yield maps
Resumo:
The effects of both barley and Lolium rigidum densities on weed growth and spike production and on crop yield were examined in five field experiments carried out in the Mediterranean drylands of Spain and Western Australia. The aim was to check the consistency of the competitiveness of the crop in different environmental and management conditions. L. rigidum reduced barley yields in most of the experiments (between 0 and 85%), the number of ears per m2 being the most affected. It was found that increasing the barley seeding rate did not reduce the crop losses but did limit weed biomass (between 5 and 61%) and spike production (between 24 and 85%). The variability observed in crop yield losses between sites and seasons was related to rainfall at the beginning of the season. The most sensitive component of yield to weed competition was the number of ears per plant.
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El objetivo de la presente investigación fue analizar la correspondencia entre los resultados de una evaluación de tierras con la distribución real de los cultivos. Para ello la aptitud biofísica de las tierras se comparó con diferentes tipologías de frecuencia de ocurrencia de los cultivos y rotaciones derivadas de mapas de cultivos multitemporales. La investigación fue llevada a cabo en el distrito de riego de Flumen (33.000 ha), localizado en el valle del Ebro (NE España). La evaluación de tierras se basó en una cartografía de suelos 1:100.000, según el esquema FAO, para los principales cultivos presentes en el área de estudio (alfalfa, cereales de invierno, maíz, arroz y girasol). Se utilizaron tres mapas de frecuencia de cultivos y un mapa de rotaciones, derivado de una serie temporal de imágenes Landsat TM y ETM+ del periodo 1993-2000, y se compararon con los mapas de aptitud de tierras para los diferentes cultivos. Se analizó estadísticamente (Pearson χ2, Cramer V, Gamma y Somers D) la relación entre los dos tipos de variables. Los resultados muestran la existencia de una relación significativa (P=0,001) entre la localización de los cultivos y la idoneidad de las tierras, excepto de cultivos oportunistas como el girasol, muy influenciado por las subvenciones en el periodo estudiado. Las rotaciones basadas en la alfalfa muestran los mayores porcentajes (52%) de ocupación en las tierras más aptas para la agricultura en el área de estudio. El presente enfoque multitemporal de análisis de la información ofrece una visión más real que la comparación entre un mapa de evaluación de tierras y un mapa de cultivos de una fecha determinada, cuando se valora el grado de acuerdo entre las recomendaciones sobre la aptitud de las tierras y los cultivos realmente cultivados por los agricultores.
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Precision Viticulture (PV) is a concept that is beginning to have an impact on the wine-growing sector. Its practical implementation is dependant on various technological developments: crop sensors and yield monitors, local and remote sensors, Global Positioning Systems (GPS), VRA (Variable-Rate Application) equipment and machinery, Geographic Information Systems (GIS) and systems for data analysis and interpretation. This paper reviews a number of research lines related to PV. These areas of research have focused on four very specific fields: 1) quantification and evaluation of within-field variability, 2) delineation of zones of differential treatment at parcel level, based on the analysis and interpretation of this variability, 3) development of Variable-Rate Technologies (VRT) and, finally, 4) evaluation of the opportunities for site-specific vineyard management. Research in these fields should allow winegrowers and enologists to know and understand why yield variability exists within the same parcel, what the causes of this variability are, how the yield and its quality are interrelated and, if spatial variability exists, whether site-specific vineyard management is justifiable on a technical and economic basis.
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Through the site-specific management, the precision agriculture brings new techniques for the agricultural sector, as well as a larger detailing of the used methods and increase of the global efficiency of the system. The objective of this work was to analyze two techniques for definition of management zones using soybean yield maps, in a productive area handled with localized fertilization and other with conventional fertilization. The sampling area has 1.74 ha, with 128 plots with site-specific fertilization and 128 plots with conventional fertilization. The productivity data were normalized by two techniques (normalized and standardized equivalent productivity), being later classified in management zones. It can be concluded that the two methods of management zones definition had revealed to be efficient, presenting similarities in the data disposal. Due to the fact that the equivalent standardized productivity uses standard score, it contemplates a better statistics justification.
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The penetration resistance (PR) is a soil attribute that allows identifies areas with restrictions due to compaction, which results in mechanical impedance for root growth and reduced crop yield. The aim of this study was to characterize the PR of an agricultural soil by geostatistical and multivariate analysis. Sampling was done randomly in 90 points up to 0.60 m depth. It was determined spatial distribution models of PR, and defined areas with mechanical impedance for roots growth. The PR showed a random distribution to 0.55 and 0.60 m depth. PR in other depths analyzed showed spatial dependence, with adjustments to exponential and spherical models. The cluster analysis that considered sampling points allowed establishing areas with compaction problem identified in the maps by kriging interpolation. The analysis with main components identified three soil layers, where the middle layer showed the highest values of PR.
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Water and fertilizer among the production factors are the elements that most restrict the production of cashew. The precise amount of these factors is essential to the success of the crop yield. This research aimed to determine the best factor-product ratio and analyze technical and economic indicators, of productivity of the cashew clone BRS 189 (Anacardium occidentale) to production factors water and potassium. The experiment was conducted from May 2009 to December 2009 in an experimental area of 56.0 m x 112.0 m in the irrigated Curu - Pentecoste, located in the municipality of Pentecoste, Ceará, Brazil. Production factors water (W) and potassium (K) were the independent variables and productivity (Y), the dependent variable. Ten statistical models that have proven satisfactory for obtaining production function were tested. The marginal rate of substitution was obtained through the ratio of the potassium marginal physical product and the water marginal physical product. The most suited model to the conditions of the experiment was the quadratic polynomial without intercept and interaction. Considering that the price of the water was 0.10 R$ mm -1, the price of the potassium 2.19 R$ kg -1 and the price of the cashew 0.60 R$ kg-1, the amounts of water and K2O to obtain the maximum net income were 6,349.1 L plant-1 of water and 128.7 g plant -1year, -1 respectively. Substituting the values obtained in the production function, the maximum net income was achieved with a yield of 7,496.8 kg ha-1 of cashew.
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The genus Euphorbia comprises about 2000 species ranging from annuals to trees, including C3, C4, and CAM species. Euphorbia species widely studied in agriculture includes E. antiquorum, E. carollata, E. dentata, E. dracunculoides, E. esula, E. geniculata, E. granulata, E. helioscopia, E. heterophylla, E. hierosolymitana, E. hirta, E. maculata, E. microphylla, E. nerifolia, E. piluifera, E. pulcherrima, E. royleana, E. supine, and E. thiamifolia. These species have been reported mainly in field crops/vegetables, orchards, pastures, and rangelands. Euphorbia plants may present allelopathic effect over desirable cereals, pulses, oilseeds, vegetables, forage plants, and nitrifying bacteria, posing a serious threat to livestock production on open range lands through the release of allelochemicals from roots, stems, leaves, and inflorescence in the rhizosphere. Leaves are reported to be more toxic than other plant parts. Competition of Euphorbia spp. against crop plants is the most important crop yield-limiting factor. The critical period for Euphorbia competition with crops is reported to take place between 17 to 70 days after emergence for most crops, depending on root development during the initial crop growth stage, crop height, tillering or branching capacity, whether weeds emerge at the same time as the crop or later after crop emergence; how quickly crop canopy develops and also on Euphorbia species. A yield reduction of 4-85% has been reported in field crops with different Euphorbia species and distinct occurrence densities. Euphorbia species decrease herbage production by 10 to 100% in pasture and rangelands, with many acting as natural insecticide, fungicide, nematidicide, immunopotentiator, or immunosuppressor.
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Weed management is a primary concern in direct seeded rice (DSR) cropping because weed growth becomes a major constraint on crop yield. A two year field study was set up to evaluate the effect of various weed control measures on crop growth, grain yield and grain quality of DSR. The experiment involved five different weed control measures: hand weeding, hoeing, inter-row tine cultivation, inter-row spike hoeing and herbicide treatment (Nominee 100 SC). The extent of weed control (compared to a non-weeded control) ranged from 50-95%. The highest crop yield was obtained using hand weeding. Hand weeding, tine cultivation and herbicide treatment raised the number of fertile rice tillers formed per unit area and the thousand grain weight. Tine cultivation provided an effective and economical level of weed control in the DSR crop.
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The present investigation on “Coconut Phenology and Yield Response to Climate Variability and Change” was undertaken at the experimental site, at the Regional Station, Coconut Development Board, KAU Campus, Vellanikkara. Ten palms each of eight-year-old coconut cultivars viz., Tiptur Tall, Kuttiadi (WCT), Kasaragod (WCT) and Komadan (WCT) were randomly selected.The study therefore, reinforces our traditional knowledge that the coconut palm is sensitive to changing weather conditions during the period from primordium initiation to harvest of nuts (about 44 months). Absence of rainfall from December to May due to early withdrawal of northeast monsoon, lack of pre monsoon showers and late onset of southwest monsoon adversely affect the coconut productivity to a considerable extent in the following year under rainfed conditions. The productivity can be increased by irrigating the coconut palm during the dry periods.Increase in temperature, aridity index, number of severe summer droughts and decline in rainfall and moisture index were the major factors for a marginal decline or stagnation in coconut productivity over a period of time, though various developmental schemes were in operation for sustenance of coconut production in the State of Kerala. It can be attributed to global warming and climate change. Therefore, there is a threat to coconut productivity in the ensuing decades due to climate variability and change. In view of the above, there is an urgent need for proactive measures as a part of climate change adaptation to sustain coconut productivity in the State of Kerala.The coconut productivity is more vulnerable to climate variability such as summer droughts rather than climate change in terms of increase in temperature and decline in rainfall, though there was a marginal decrease (1.6%) in the decade of 1981-2009 when compared to that of 1951-80. This aspect needs to be examined in detail by coconut development agencies such as Coconut Development Board and State Agriculture Department for remedial measures. Otherwise, the premier position of Kerala in terms of coconut production is likely to be lost in the ensuing years under the projected climate change scenario. Among the four cultivars studied, Tiptur Tall appears to be superior in terms of reproduction phase and nut yield. This needs to be examined by the coconut breeders in their crop improvement programme as a part of stress tolerant under rainfed conditions. Crop mix and integrated farming are supposed to be the best combination to sustain development in the long run under the projected climate change scenarios. Increase in coconut area under irrigation during summer with better crop management and protection measures also are necessary measures to increase coconut productivity since the frequency of intensity of summer droughts is likely to increase under projected global warming scenario.
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A field experiment was conducted under rainfed conditions in western Sudan at El-Obeid Research Farm and Eldemokeya Forest Reserve, North Kordofan State, during the growing seasons 2004/05 and 2005/06. The main objective was to investigate the soil physical and chemical properties and yield of groundnut (Arachis hypogea), sesame (Sesamum indicum) and roselle (Hibiscus sabdariffa) of an Acacia senegal agroforestry system in comparison with the sole cropping system. Data were recorded for soil physical and chemical properties, soil moisture content, number of pods per plant, fresh weight (kg ha^−1) and crop yield (kg ha^−1). The treatments were arranged in Randomized Complete Block Design (RCBD) and replicated four times. Significant differences (P < 0.05) were obtained for sand and silt content on both sites, while clay content was not significantly different on both sites. The nitrogen (N) and organic carbon were significantly (P < 0.05) higher in the intercropping system in Eldemokeya Forest Reserve compared with sole cropping. Soil organic carbon, N and pH were not significant on El-Obeid site. Yet the level of organic carbon, N, P and pH was higher in the intercropping system. Fresh weight was significantly different on both sites. The highest fresh weight was found in the intercropping system. Dry weights were significantly different for sesame and roselle on both sites, while groundnut was not significantly different. On both sites intercropping systems reduced groundnut, sesame and roselle yields by 26.3, 12 and 20.2%, respectively. The reduction in yield in intercropping plots could be attributed to high tree density, which resulted in water and light competition between trees and the associated crops.
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The impact of two crop planting methods and of the application of cyanobacterial inoculants on plant growth, yield, water productivity and economics of rice cultivation was evaluated with the help of a split plot designed experiment during the rainy season of 2011 in New Delhi, India. Conventional transplanting and system of rice intensification (SRI) were tested as two different planting methods and seven treatments that considered cyanobacterial inoculants and compost were applied with three repetitions each. Results revealed no significant differences in plant performance and crop yield between both planting methods. However, the application of biofilm based BGA bio-fertiliser + 2/3 N had an overall positive impact on both, plant performance (plant height, number of tillers) and crop yield (number and weight of panicles) as well as on grain and straw yield. Higher net return and a higher benefit-cost ratio were observed in rice fields under SRI planting method, whereas the application of BGA + PGPR + 2/3 N resulted in highest values. Total water productivity and irrigation water productivity was significantly higher under SRI practices (5.95 and 3.67 kg ha^(-1) mm^(-1)) compared to practices of conventional transplanting (3.36 and 2.44), meaning that using SRI method, water saving of about 34 % could be achieved and significantly less water was required to produce one kg of rice. This study could show that a combination of plant growth promoting rhizobacteria (PGPR) in conjunction with BGA and 2/3 dose of mineral N fertiliser can support crop growth performance, crop yields and reduces overall production cost, wherefore this practices should be used in the integrated nutrient management of rice fields in India.
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This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.
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This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.
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The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.
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It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop-climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change. To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop-climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.