104 research outputs found

    The effect of crop residue layers on evapotranspiration, growth and yield of irrigated sugarcane†

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    A layer of harvest residues from the previous crop can reduce wasteful evaporation from the soil surface and thereby increase the efficiency of use of limited water resources for agricultural production. The practice of harvesting sugarcane green and leaving crop residues in the field, as opposed to burning the residue, has been re-adopted in many sugarcane industries worldwide. However, a better understanding of the dynamic impacts of residue layers on various aspects of the cropping system is required to (1) enable the formulation of sets of best management practices for specific production scenarios, and (2) promote the use of residue layers in areas where it is desirable and has not been adopted, such as irrigated sugarcane production in South Africa. The objective of this study, therefore, was to quantify the effect of 2 different types of residue layers on crop growth, cane yield and evapotranspiration of fully irrigated sugarcane. A layer of cane tops and dead leaves (Trash) and a layer of green tops (Tops) were applied to the soil surface of sugarcane crops (plant crop and first ratoon crop of variety N14) grown on lysimeters at Pongola, South Africa. Observations of crop growth (stalk population, stalk height, canopy cover), cane yield and evapotranspiration for these treatments were compared to that of a bare soil treatment. The data were also used to derive values of crop evaporation coefficients for different development phases and these were compared to FAO56 recommendations. Initial stalk population in the plant crop and radiation capture in the plant and ratoon crop were affected negatively by crop residue layers, but without significantly reducing final stalk population and cane yield. Peak stalk population occurred later in crops grown in residue layers, but peak and final stalk populations were unaffected. Evapotranspiration was reduced by both residue layers, mainly due to a slower developing canopy (reduced transpiration) and reduced evaporation from the soil, during the pre-canopy phases. Increased drainage was observed under residue layers, emphasising the importance of accurate irrigation scheduling to avoid water logging. The FAO56 methodology for calculating crop evaporation coefficient values for the initial, development and late season phases are supported by the results obtained here. Crop evaporation coefficient values were significantly reduced by residue layers. It is important that irrigation scheduling practices be adjusted to realise the potential water savings of sugarcane production systems that make use of residue layers. This study provides the information required to do that. The information could also be used to improve the ability of the crop models to accurately simulate crop growth and evapotranspiration in a residue layer cropping system.Keywords: water use, irrigation, stalk population, canopy development, lysimeter, crop evaporation coefficient, trash blanke

    Modelling and monitoring for strategic yield gap diagnosis in the South African sugar belt

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    AbstractThis paper revisits the diagnostic use of industry-wide sugarcane (Saccharum sp. hybrid) modelling and monitoring in South Africa for gaining a better understanding of production trends and the strategies required to address temporal and spatial yield variation.Such reviews have been conducted annually since 2008, by comparing the ratio of actual to simulated (potential) average sugarcane yields for 14 sugar mills with that of preceding seasons (since 1980). Actual yields are determined from total amount of cane crushed at the mill and the estimated area harvested as determined from mill records and grower surveys. Potential yields are determined by using the Canesim model with daily weather data for 48 homogenous agro-climatic zones. Widening yield gaps in some key producing regions and significant differences between regions indicated the need to investigate the impact of non-climatic factors such as pests, diseases, and sub-optimal agronomic management, even though this analysis is still qualitative and incomplete, and not fully objective. Factors that were highlighted as likely causes of suboptimal production were damaging effect of a new pest (sugarcane thrips), inadequate nutrition and inadequate replanting, apparently linked to unfavourable socio-economic conditions; even more so for small-scale growers than for large-scale growers. In addition to providing a service that is valued by the industry, the annual reviews have contributed to strengthening co-operation between researchers of distinct disciplines as well as between researchers and canegrowers, and to help identify priorities for further research. The quality of the analysis could be further improved by more accurate and timely estimates of the area harvested, improved resolution of yield data and extended surveys of pests, diseases and other yield limiting or reducing factors

    Irrigation scheduling research: South African experiences and future prospects

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    Many scheduling approaches have been developed with Water Research Commission funding over the past 4 decades and deployed with varying levels of success; 2 approaches have won prestigious international awards. Soil-based approaches which include measurement of matric potential (tensiometry), water content (neutron probes, capacitance sensors) and depth of wetting (wetting front detectors) have been relatively well accepted by farmers. Atmospheric-based approaches apply, through biophysical modelling of the soil-crop-atmosphere system, thermodynamic limits to the amount of water that can evaporate from a cropped surface under particular environmental conditions. Modelling approaches have been quite empirical or somewhat more mechanistic, generic or crop specific, with pre-programmed (e.g. irrigation calendars) or real-time output. Novel mechanisms have been developed to deliver recommendations to farmers, including resource-poor irrigators. Although general adoption of objective irrigation scheduling in South Africa is still low, the high cost of electricity and nitrogen, and scarcity of water is reviving the interest of consultants and irrigators in the application of these tools to use water more efficiently. Where adoption has been relatively high, intensive support and farmer-researcher-consultant interactions have been key contributing factors. We propose 4 avenues in the R&D domain to ensure responsible water utilisation. Firstly, there is a need to continue to advance existing soil-water measurement technology; and secondly, to further develop new and emerging technologies, like the use of remote sensing. Thirdly, the user-friendliness should be improved as should systems that support existing scheduling tools; and finally, we need to appreciate that farmers are intuitively adaptive managers, and we need to develop simple monitoring tools and conceptual frameworks that enable structured learning.Keywords: BEWAB; CANESIM; PUTU; SWB; wetting front detecto

    Negative effects of lodging on irrigated sugarcane productivity : an experimental and crop modelling assessment

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    Lodging lowers the productivity of sugarcane through a reduction in radiation use efficiency and stalkdamage. However, there are few reports of experiments specifically designed to quantify effects of lodg-ing in sugarcane. Efforts to model onset and progression of lodging, and the impact on crop productivity,have not been attempted. The objectives of this paper were to quantify effects of lodging on sugarcaneand to develop modeling capability in terms of predicting lodging onset, progression and impact. Fieldexperiments with irrigated ratoon crops were conducted at Pongola, South Africa. In one treatment thecane in each plot was allowed to grow through bamboo frames that prevented lodging. In the othertreatment, the cane was not supported and could lodge at any stage. The degree of lodging was capturedweekly by a rating that ranged from 1 to 9, where 1 = fully erect cane and 9 = completely lodged cane.At harvest estimated recoverable crystal percent (ERC %) of stalks and yield (cane and ERC) was mea-sured for each plot. Lodging resulted in decreased ERC yields of up to 20.6%. An algorithm for simulatinglodging when aboveground biomass (including rainfall and irrigation water retained on it) exceeds avariety-specific threshold, and which also considers wind speed and soil water content, was evaluatedfor predicting the extent and impact of lodging in the Pongola experiments, as well as for four deficitirrigation treatments of a field experiment conducted in Komatipoort, South Africa. The study showedthat the onset of lodging was simulated reasonably well for various soil/crop/atmospheric conditions,while the extent of lodging at harvest was simulated very accurately for all crops. Simulated lodging wasprimarily driven by crop size and lodging events were triggered by rainfall that added weight to the aerialmass of the crop, and reduced the anchoring ability of the soil through saturation of the top soil. Moreaccurate simulation of lodging, and its impacts on yield, will improve the accuracy of yield predictionsby crop models, increasing their value in applications such as crop forecasting, climate change studiesand exploring crop improvement and management options.South African Sugarcane Research Institute.http://www.elsevier.com/locate/fcr2016-08-31hb201

    International Standard ISO 9001–A Soft Computing View

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    In order to add value to ISO 9001, a Quality Management Systems that assess, measure, documents, improves, and certify processes to increase productivity, i.e., that transforms business at any level. On the one hand, this work focuses on the development of a decision support system, which will allow companies to be able to meet the needs of customers by fulfilling requirements that reflect either the effectiveness or the non-effectiveness of an organization. On the other hand, many approaches for knowledge representation and reasoning have been proposed using Logic Programming (LP), namely in the area of Model Theory or Proof Theory. In this work it is followed the proof theoretical approach in terms of an extension to the LP language to knowledge representation and reasoning. The computational framework is centered on Artificial Neural Networks to evaluate customer’s satisfaction and the degree of confidence that one has on such a happening

    The importance of crop growth modeling to interpret the Δ14CO2 signature of annual plants

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    [1] The 14C/C abundance in CO2(¿14CO2) promises to provide useful constraints on regional fossil fuel emissions and atmospheric transport through the large gradients introduced by anthropogenic activity. The currently sparse atmospheric ¿14CO2 monitoring network can potentially be augmented by using plant biomass as an integrated sample of the atmospheric ¿14CO2. But the interpretation of such an integrated sample requires knowledge about the day¿to¿day CO2 uptake of the sampled plants. We investigate here the required detail in daily plant growth variations needed to accurately interpret regional fossil fuel emissions from annual plant samples. We use a crop growth model driven by daily meteorology to reproduce daily fixation of ¿14CO2 in maize and wheat plants in the Netherlands in 2008. When comparing the integrated ¿14CO2 simulated with this detailed model to the values obtained when using simpler proxies for daily plant growth (such as radiation and temperature), we find differences that can exceed the reported measurement precision of ¿14CO2(~2‰). Furthermore, we show that even in the absence of any spatial differences in fossil fuel emissions, differences in regional weather can induce plant growth variations that result in spatial gradients of up to 3.5‰ in plant samples. These gradients are even larger when interpreting separate plant organs (leaves, stems, roots, or fruits), as they each develop during different time periods. Not accounting for these growth¿induced differences in ¿14CO2 in plant samples would introduce a substantial bias (1.5–2¿ppm) when estimating the fraction of atmospheric CO2 variations resulting from nearby fossil fuel emission
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