Using degree‐days model to determine the optimum spray timing for the codling moth <i>Cydia pomonella</i> (L.) (Lep., Olethreutidae)

Ahmad, Tanvir; Ali, Muhammad Asghar; Hamad, B. S.

doi:10.1111/j.1439-0418.1995.tb01260.x

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…Monitoring of grapevine pests, their natural enemies, and diseases during the phenological development of the plants is locally being carried out by IPM teams, named Atrias, which co‐operate with the grape farmers and the agricultural administrations to determine the best moments to perform phytosanitary treatments. Therefore, in order to optimise grapevine management, it would be extremely useful to have a predicting model for the flight activity and the different generation times of L. botrana , in a similar way as described by Ahmad and Ali (1995) and Ahmad et al. (1995) for other lepidopteran species, such as Ephestia spp.…”

Section: Introductionmentioning

confidence: 99%

Forecasting the flight activity of Lobesia botrana (Denis & Schiffermüller) (Lepidoptera, Tortricidae) in Southwestern Spain

Gallardo

Ocete

López

et al. 2009

J Applied Entomology

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This study aimed at elaborating a forecasting tool of the phenology of the serious pest Lobesia botrana in Southwestern Spanish vineyards, by analysing data on male catches in sex pheromone traps recorded over a 12‐year period. Our data confirmed the minor importance of the first generation which appears during flowering time, both in terms of male trap catches and damage of L. botrana to the inflorescences. Therefore, data related to the first flight were not further processed, although they were considered for the computation of degree‐days of the following generations. The outcome of the elaboration of temperature accumulations and data on male captures for the second and third flights was a statistically acceptable linear behaviour obtained by properly transforming the variables. The models established proved to be efficient and may represent a useful tool to improve the efficacy of integrated pest management strategies targeting L. botrana in the studied region.

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Section: Introductionmentioning

confidence: 99%

Forecasting the flight activity of Lobesia botrana (Denis & Schiffermüller) (Lepidoptera, Tortricidae) in Southwestern Spain

Gallardo

Ocete

López

et al. 2009

J Applied Entomology

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“…In spite of this, some grapevine growers do treat, generally with chlorpyrifos, provoking possible negative effects on the agroecosystem. Forecasting tools are of great interest in integrated pest management in order to improve the effectiveness of insecticide application (Ahmad et al ., 1995; Jud & Gardiner, 1997). In the case of K. flavicollis , forecasting is fundamental, as only the alates constitute a target for control, owing to their exposure and to their high sensitivity.…”

Section: Resultsmentioning

confidence: 99%

Logistic model for describing the pattern of flight of Kalotermes flavicollis in sherry vineyards

2003

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Kalotermes flavicollis is a serious pest in southern Spanish vineyards. The development of this termite is hidden inside galleries excavated along the wood of the vines. Dispersion is by the sexual adults, which emerge in autumn between September and November. These winged individuals constitute the main target to control the pest in integrated production. A logistic model based on the relationship existing between catches in sticky traps over 4 years and degree–days has been fitted for this termite in sherry vineyards in Andalucía. The results show that, above 548 accumulated degree–days, approximately 50% of winged individuals emerge. This information can help farmers to take control decisions.

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“…To further improve efficacy and economic feasibility of codling moth control, pest forecasting models (1,5,24,30,32) may be used to adjust the timing of insecticide applications to pest population dynamics. Since organically approved fungicides (primarily sulfur and copper compounds) provide less effective protective control compared with systemic fungicides commonly used in integrated and conventional orchards (17,18), improved insect control is essential in the brown rot management of organic apple orchards.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Relationships Between Different Injury Factors and Development of Brown Rot Caused byMonilinia fructigenain Integrated and Organic Apple Orchards

Holb¹,

Scherm²

2008

Phytopathology®

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In a 4-year study, the incidence of various types of injuries (caused by insects, birds, growth cracks, mechanical wounding, and other, unidentified factors) was assessed in relation to brown rot development (caused by Monilinia fructigena) on fruit of three apple cultivars (Prima, Jonathan, and Mutsu) in integrated and organic blocks of two apple orchards in Hungary. In addition, populations of male codling moths (Cydia pomonella) were monitored with pheromone traps season-long in both management systems. On average, injury incidence on fruit at harvest was 6.1 and 19.2% in the integrated and organic treatments, respectively. Insect injury, which was caused primarily by C. pomonella, had the highest incidence among the five injury types, accounting for 79.4% of the total injury by harvest in the organic blocks and 36.6% in the integrated blocks. Levels of all other injury types remained close to zero during most of the season, but the incidence of bird injury and growth cracks increased markedly in the final 3 to 5 weeks before harvest in both production systems. Brown rot developed more slowly and reached a lower incidence in the integrated (6.4% final incidence on average) compared with the organic blocks (20.1% average incidence). In addition, the disease developed later but attained higher levels as the cultivar ripening season increased from early-maturing Prima to late-maturing Mutsu. Overall, 94.3 to 98.7% of all injured fruit were also infected by M. fructigena, whereas the incidence of brown-rotted fruit without visible injury was very low (0.8 to 1.6%). Correlation coefficients (on a per plot basis) and association indices (on a per-fruit basis) were calculated between brown rot and the various injury types for two selected assessment dates 4 weeks preharvest and at harvest. At both dates, the strongest significant (P < 0.05) relationships were observed between brown rot and insect injury and between brown rot and the cumulative number of trapped C. pomonella. At the harvest assessment, two additional significant correlations were between brown rot and bird injury and between brown rot and growth cracks. In every case, correlation coefficients were larger in organic than in integrated blocks. Although it is well established that brown rot in pome fruits is closely associated with fruit injuries, this is the first study to provide season-long progress data on different injury types and quantitative analyses of their relative importance at different times in the growing season and across two distinct management systems.

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Using degree‐days model to determine the optimum spray timing for the codling moth Cydia pomonella (L.) (Lep., Olethreutidae)

Cited by 7 publications

References 9 publications

Forecasting the flight activity of Lobesia botrana (Denis & Schiffermüller) (Lepidoptera, Tortricidae) in Southwestern Spain

Forecasting the flight activity of Lobesia botrana (Denis & Schiffermüller) (Lepidoptera, Tortricidae) in Southwestern Spain

Logistic model for describing the pattern of flight of Kalotermes flavicollis in sherry vineyards

Quantitative Relationships Between Different Injury Factors and Development of Brown Rot Caused byMonilinia fructigenain Integrated and Organic Apple Orchards

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