Modelling systems of disease and yield loss in cereals

Teng, P. S.; Gaunt, R. E.

doi:10.1016/0308-521x(80)90025-6

Cited by 52 publications

(19 citation statements)

References 32 publications

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“…A similar model was developed for stem rust in spring wheat, where yield loss was estimated as a function of the slope of the epidemic line and the growth stage of the host at time of epidemic onset (Calpouzos et al, 1976). This type of model, represented by response surface, provides a conceptual framework based on a knowledge of epidemiology and physiology for modelling disease-loss systems (Teng & Gaunt, 1981). Our model does not incorporate the influence of variables such as plant stand, weather, soil type, plant compensation and others, and cannot be used to make accurate predictions in different situations.…”

Section: Discussionmentioning

confidence: 99%

The influence of verticillium wilt epidemics on cotton yield in southern Spain

et al. 1997

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Experiments were conducted in the Guadalquivir Valley of Andalucía, southern Spain, in 1986 and 1987, using field plots naturally infested with different inoculum densities of the defoliating and nondefoliating pathotypes of Verticillium dahliae to determine the influence of verticillium wilt epidemics on yield of cotton cultivar Coker 310. The total number of bolls, the number of open bolls, and seed cotton yield were related to the growth stage of plants at first appearance of foliar symptoms, and to inoculum density and virulence of the V. dahliae pathotype prevailing in the soil. For the three yield components, the greatest reduction was observed in plants showing symptoms before opening of first flowers (about 650 degree-days after sowing). Yield increased with delay in the development of foliar symptoms during the crop season, and the effect of the wilt epidemics on yield was small or nil for plants that developed symptoms after opening of the first bolls (1400-1500 degree-days after sowing). A multiple regression equation was derived that related yield reduction to the physiological time accumulated from the time of sowing until the appearance of foliar symptoms and to the rate of disease intensity increase over physiological time. This multiple point model explained about 70% of the variation in cotton yield loss due to verticillium wilt.

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Section: Discussionmentioning

confidence: 99%

The influence of verticillium wilt epidemics on cotton yield in southern Spain

et al. 1997

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“…Establishment of these diseases was delayed by seed dressing, as found by Sheridan et al (1985), but, particularly in the autumn sown crops, establishment was rapid once the effect of the seed dressing wore off. It may be possible to develop spray programmes for these diseases based on predictive simulation models (Teng & Gaunt 1980), but in the longer term, resistant cultivars are likely to be the best answer to fungal diseases (Coles 1983).…”

Section: Preventative Disease and Pest Controlmentioning

confidence: 99%

Management of Triumph’ barley for high yield and malting quality on light soils in Canterbury, New Zealand

Martin

Daly²

1993

New Zealand Journal of Crop and Horticultural Science

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This 4-year study was initiated to formulate a management package for producing high yields of high quality malting barley and involved large-scale trials comparing the levels and interactions of nitrogen (N), irrigation, and disease and pest control on yield and quality. One ha each of autumn and spring sown crops were sown in mid Canterbury each year. In the first 3 years, low and high levels of irrigation (flood irrigation when gravimetric soil moisture in the top 150 mm of soil fell to either 15% or 20%) and two levels of disease and pest control (curative and preventative) were compared at different levels of N fertiliser (100, 200, and 300 kg N/ha in Year 1, and 0, 50, 100, and 200 kg N/ha in Years 2 and 3). In the fourth year, four levels of disease control (nil, curative, half preventative, and preventative) were compared along with four levels of N fertiliser (0, 50, 100, and 150 kg N/ha). The treatment means from all eight trials (but only the first six trials in the instance of malt extract, ears/m 2 , and grains/ear) were then analysed together to determine the overall effect of treatments and treatment combinations. This combined analysis H92048

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“…Preliminary data gathering from each site is helpful in being able to focus on key variables. There is also a need to remove autocorrelation between variables (Teng and Gaunt 1980;Stynes 1980). Data are then taken over several seasons on a welldefined set of variables.…”

Section: Methodsmentioning

confidence: 99%

“…The number of spikelets/m 2 is determined by the number of tillers/m 2 and spikelets per tiller. The number of grains per spikelet is related to the number of spikelet primordia, the percentage of primordia that develop flowers, the number of florets per spikelet, and the percentage which set (Teng and Gaunt 1980). Each of these physiological processes occurs at a particular time during the growth of the crop.…”

Section: Physiology Of Yield Lossmentioning

confidence: 99%

Crop Loss Assessment in Rice

Litsinger¹

1991

Springer Series in Experimental Entomology

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Modelling systems of disease and yield loss in cereals

Cited by 52 publications

References 32 publications

The influence of verticillium wilt epidemics on cotton yield in southern Spain

The influence of verticillium wilt epidemics on cotton yield in southern Spain

Management of Triumph’ barley for high yield and malting quality on light soils in Canterbury, New Zealand

Crop Loss Assessment in Rice

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