Modeling Yield Losses Caused by Alfalfa Foliar Diseases

 

J. Guan, F. W. Nutter, Jr.1, A. R. Gotlieb2, C. R. Grau3, and L. H. Rhodes4

1Department of Plant Pathology, Iowa State University, Ames, IA 50011, 2Department of Plant and Soil, University of Vermont, Burlington, VT 05405; 3Department of Plant Pathology, University of Wisconsin, Madison, WI 53706; and 4Department of Plant Pathology, Ohio State University, Columbus, Ohio 43210

 

To quantify the yield losses caused by foliar diseases of alfalfa, field experiments were condcuted in Iowa, Ohio, Vermont, and Wisconsin using fungicides as a tool to obtain a range of foliar disease epidemics in alfalfa. Alfalfa foliar diseases caused significant yield losses in all four states (22 out of 48 growth cycles (harvests)). Out of the 16 harvests conducted in Iowa, 10 harvests had significant yield losses compared to the nonfungicide treated control plots. Overall, yield losses in Iowa ranged from 1.7 to 33.9 % with an average loss of 16.5 % per growth cycle. In Ohio, 3 out of the 10 harvests had significant yield losses with yield losses ranging from 3.0 to 23.0 % (average loss of 9.6 %). In Vermont, 8 out of 14 harvests had significant yield losses with losses ranging from 0.4 to 23.4 % (average loss of 15.0 %). In Wisconsin, only 1 out the 8 harvests had a significant yield loss (14.7 %). To quantify the relationships between disease intensity assessments and alfalfa yield, disease incidence, disease severity, and percentage defoliation were visually assessed each week. The percentage of sunlight reflected from alfalfa canopies was also measured every week using a hand-held, multispectral radiometer (CROPSCAN, Rochester, MN). Both visual and percentage reflectance assessments were used as the independent variable in linear regression models (Iowa data) to elucidate disease intensity-yield relationships in alfalfa. On average, 48 % of the variation in yield was explained by visual disease assessments, whereas percentage reflectance assessments explained 76 % of the variation in alfalfa yield. Thus, percentage reflectance measurements explained 18 % more of the variation in alfalfa yield than visual disease assessments.

 

References

 

Nilsson, H. E. 1995. Remote sensing and image analysis in plant pathology. Annu. Rev. Phytopathol. 15:489 527.

Nutter, F. W., Jr., and Gaunt, R. E. 1996. Recent developments in methods for assessing disease losses in forage/pasture crops. Pages 93-118 in: S. Chakraborty, D. T. Leath, R. A. Skipp, G. A. Pederson, R. A. Bray, G. C. M. Latch, and F. W. Nutter, Jr. (eds.) Pasture and Forage Crop Pathology. American Soc. Agronomy, Crop Sci. Soc. America and Soil Sci. Soc. America, Madison, WI.

 

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