Predicting Yield Losses in Corn from Southern Corn Leaf Blight

Gregory, L; Ayers, J. E.; Nelson, Ricky

doi:10.1094/phyto-68-517

Cited by 20 publications

(7 citation statements)

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“…Single point models have been used for several diseases including, corn leaf southern blight (Bipolaris maydis) (Gregory et al 1978), potato late blight (Phytophthora infestans) (Olofson 1968). Integral model was used for wheat stem rust (Puccinia graminis) crop loss assessment for the first time (Teng 1987).…”

Section: Resultsmentioning

confidence: 99%

Measuring and Modeling Crop Loss of Wheat Caused by Septoria Leaf Blotch in Seven Cultivars and Lines in Iran

Mojerlou¹,

Safaie²,

Alizadeh³

et al. 2009

Journal of Plant Protection Research

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Septoria leaf blotch caused by Septoria tritici, is one of the most important diseases of wheat worldwide including Iran. To determine yield reduction caused by this disease in Golestan province, field experiments were carried out in randomized complete block design with four replications and five wheat cvs. Tajan, Zagros, Shiroodi, Koohdasht, Shanghai and two lines N-80-6 and N-80-19 at Gorgan Research Station. Artificial inoculation was performed using spore suspension at three growth stages (Zadoks scale) including tillering (GS 37), stem elongation (GS 45) and flag leaf opening (GS 53). Control plots were sprayed with water. In this study, the 1 000 kernel weight (TKW), grain yield and area under disease progress curve (AUDPC) during growth season were measured. Statistical analysis showed that the levels of yield reduction was different in various studied wheat cultivars and lines and was reduced by 30 to 50%. The highest losses were observed for cvs. Zagros and Tajan with 48.86% and 47.41% of grain yield reduction, respectively. There was a positive correlation between grain yield reduction and AUDPC. The results of crop loss modelling using integral and multiple point regression models showed that the integral model (L = 1230.91+1.37AUDPC) in which AUDPC and crop loss percentages were independent and dependent variables, respectively, could explain more than 95% of AUDPC variations in relation to crop loss in all cultivars in two years. In the study of integral model for each cultivar, cv. Shiroodi showed the highest fitness. In multiple point models, disease severity at various dates was considered as independent variables and crop loss percentage as dependent variable. This model with the highest coefficient of determination had the best fitness for crop loss estimation. Besides, the results showed that the disease severity at GS37, GS53 and GS91 stages (Zadok's scale) was more important for crop loss prediction than that in other phenological stages.

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Section: Resultsmentioning

confidence: 99%

Measuring and Modeling Crop Loss of Wheat Caused by Septoria Leaf Blotch in Seven Cultivars and Lines in Iran

Mojerlou¹,

Safaie²,

Alizadeh³

et al. 2009

Journal of Plant Protection Research

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“…A case in point is the southern corn leaf blight epiphytotic of 1970, caused by Bipolaris maydis (Y. Nisik. & C. Miyake) Shoemaker, 1959, which affected maize hybrids containing the Texas type (T) cytoplasm in the US Cornbelt, leading to the loss of billions of dollars (Gregory et al, 1978).…”

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confidence: 99%

Combining Ability of Yellow Lines Derived from CIMMYT Populations for Use in Subtropical and Tropical Midaltitude Maize Production Environments

et al. 2018

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The introduction and utilization of new maize (Zea mays L.) germplasm from sources, such as the International Maize and Wheat Improvement Center (CIMMYT), can be valuable for broadening the genetic base of breeding populations through the introgression of new alleles. Twenty‐five inbred lines, derived from CIMMYT breeding populations, were selected on the basis of grain color, resistance to turcicum leaf blight, and per se line performance in Yunnan. To use the lines effectively, information on their performance in hybrid combinations and on general combining ability (GCA) and specific combining ability (SCA) needed to be obtained. The objectives of this study were (i) to evaluate these lines for grain yield (GY) in hybrid combinations and determine GCA of parental lines and SCA of crosses between the 25 introduced lines and six testers using North Carolina Design II; and (ii) to classify the lines into different maize heterotic groups. The field testing at three locations identified crosses with lines from Cateto and Population 147 (P147) as having significantly higher GY than those from SA3 and other introduced populations, and the high GY was largely attributable to their high positive GCA effects. Lines from the same population were not necessarily classified into same maize heterotic group. Lines selected at S4 or a later generation would be expected to have more stable GCA effects than lines selected in earlier generations.

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“…maydis can cause a very significant loss in yield of corn with cms-T (2,13). Gregory et al (1978) reported that disease severity at the dough stage was critical in yield loss prediction (13). They derived the best regression equation between yield loss and disease severity from the disease assessment made at this stage of the crop.…”

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confidence: 99%