Relationship between male moths of Cryptoblabes gnidiella (Millière) (Lepidoptera: Pyralidae) caught in sex pheromone traps and cumulative degree-days in vineyards in southern Uruguay
© Vidart et al.; licensee Springer. 2013
Received: 29 May 2013
Accepted: 6 June 2013
Published: 10 June 2013
Cryptoblabes gnidiella (Millière) (Lepidoptera: Pyralidae) has been known in Uruguay for 30 years and only in vineyards, despite being polyphagous. In recent years, this pest has caused sporadic but serious damage on some grapevine cultivars. Understanding the insect’s phenology and developing a monitoring program are essential aspects of integrated pest management. We monitored males using sexual pheromone traps on four cultivars of vine, Pinot noir, Tannat, Gewürztraminer, and Cabernet Sauvignon, in two vine-growing establishments in the Department of Canelones and compiled data on the accumulated effective temperatures for the southern area of Uruguay. We determined that this species undergoes three generations per year and overwinters without diapause as larvae on dried grapes remaining after harvest. Using the proportion of cumulative male moths caught from December to May from 2003–2007 on the four cultivars and the sum of effective temperatures above two previously-published lower-threshold temperatures for development, 12.26°C and 13°C, statistically significant logistic models were estimated. Predictions based on the resulting models suggested that they would be acceptable tools to improve the efficiency of integrated management of this pest in Uruguay.
In Uruguay, vineyards have undergone sustained plant replacement. In the past 20 years, most of the country's 8,000 hectares of vineyards have been replaced by newer, healthier, and higher-quality grapevine cultivars. Eighty-nine percent of the wine growing area is concentrated in southern Uruguay, especially in Canelones Department (MGAP–DIEA 2011). Unlike in other wine-producing areas of the world, pests have been a minor problem in Uruguay's vineyards, eliminating the need for widespread applications of insecticides (Bentancourt and Scatoni 1999).
Cryptoblabes gnidiella (Millière) (Lepidoptera: Pyralidae) has become a sporadic pest in Uruguay capable of causing significant damage to some grapevine cultivars in certain years and areas (Bentancourt and Scatoni 2006). This polyphagous moth, is native to the Mediterranean regions of Europe and reported from Africa, Asia, New Zealand, North and South America (Bagnoli and Lucchi 2001, Ioriatti et al. 2012). It has been known in Uruguay for 30 years, but only reported from vineyards (Scatoni and Bentancourt 1983). Since its appearance, it has displaced in importance two other grape pests: Argyrotaenia sphaleropa (Meyrick) and Bonagota salubricola (Meyrick) (Lepidoptera: Tortricidae). The larvae feed on grape cluster, especially at the end of season when the fruits are already mature. Feeding damage produces conditions conducive to the development of rots. The economic losses become more significant when harvest is delayed, due to an increase in population and a potential additional generation. Also, rainfall and high humidity create conditions suitable for rots causing further deterioration of the clusters (Bentancourt and Scatoni 2006).
Knowing pest phenology is an essential aspect of developing a management program. The identification of the sex pheromone of C. gnidiella provided a monitoring tool for adults now widely used (Bjostad et al. 1981, Anshelevich et al. 1993). Monitoring of adults as well as degree-days (DD) allows the prediction of pest phenological events for management purposes. Numerous reports have correlated species catches with DD for several species of Lepidoptera; as an example, these relationship have been studied for Lobesia botrana (Lepidoptera: Tortricidae), the main vineyard pest in Europe (Del Tio et al. 2001, Milonas et al. 2001). The thermal constant and lower thresholds of development for C. gnidiella were determined by Avidov and Gothilf (1960) for Israel and by Ringenberg et al. (2005) for Brazil. There is, however, no information available about the relationship between DD and catch levels.
Understanding a pest's phenology and monitoring its populations are essential aspects of integrated pest management. The objective of this research was to better understand the phenology of this insect in Uruguay and the damage it inflicts on cultivars with different maturity dates to develop a forecasting system that uses pheromone traps and the accumulation of effective temperatures. For these purposes, population’s growth models were run for each cultivar and for all cultivars.
Materials and methods
Vineyard design at Progreso and Juanicó, Uruguay
Planting distance (m)
3.00 × 1.00
3.00 × 1.25
3.00 × 1.25
3.00 × 1.00
Adult populations were monitored with delta traps baited with 1 mg of synthetic sex pheromone (Z11-16: Ald and Z13-18: Ald, 1:1, Yogev® Ltd, Rishon Le’zion, Israel). Traps were placed 1.5 m above the ground and checked weekly. In Juanicó, three traps were placed 200 m apart on Pinot noir, Tannat, and Gewürztraminer cultivars and were monitored from December 2003 to June 2007. In Progreso, one trap was placed on Cabernet Sauvignon from October 2004 to June 2007. Each cultivar occupied an area of about one hectare and the trap was placed in the middle of the plot. Pheromone lures were replaced weekly and sticky bottom whenever necessary.
Larvae were monitored from December until leaf fall. For each of the cultivars where adult traps were placed, 90 clusters (two per vine) were collected at random every 2 weeks. In the laboratory, we recorded the presence of damage and the number of larvae and pupae per cluster. Insects collected were stored in boxes with the clusters and kept until either adults or parasitoids emerged. To understand the behavior of the overwintering larvae, after harvest we collected 60 infested clusters per year from each cultivar and stored them in 25 × 30 cm netting cloth bags in the laboratory for 24 h. The bags were returned to the vineyard the following day and hung from the wires of the lyre. Bags were checked every fortnight to verify larval development and adult emergence per cultivar. In addition, during the plants’ dormancy period we directly observed beneath the rhytidome and in other places where the larvae might be (leaf litter, dead leaves).
Daily maximum and minimum temperatures were taken from the Experimental Station of National Agricultural Research Institute Las Brujas from 2003–2007. This station is located 10 and 12 km, respectively, from the Progreso and Juanicó vineyards. Degree-days were estimated using the Baskerville and Emin (1969) method based on maximum and minimum air temperature.
To estimate the mean generation time under field conditions, we used the cumulative sum of effective temperatures (DD) between the start of one generation's flight and the next. The beginning of the overwintering flight was taken as the first date on which male moths were caught on consecutive days; this occurred in early December in all 4 years of the study. For this reason we used December 1st as the biofix. A similar method was used to set the biofix of Cydia pomonella ( Riedl et al. 1976) and other Tortricidae (Knight and Croft 1991). To set the start of subsequent generations, we used the dates on which number of male moths caught were high after periods of consistently declining or zero catches. According to Avidov and Gothilf (1960), C. gnidiella requires a minimum temperature of 13°C for development and 500 DD to complete a generation. However, Ringenberg et al. (2005) suggest a lower threshold of development of 12.26°C and 570 DD to complete a generation.
Mathematical models were adjusted using the accumulation of DD and the proportion of cumulative catches at the two sites for the 4 years and four grapevine cultivars. These models can be used to predict how the population will develop as a function of DD accumulated over time. We used one logistic model: logit (p) = a + bx; where logit (p) = log (p / (1–p)), p is the cumulative proportion of adult males associated with x, a and b are parameters of the model, and x is the cumulative DD. Estimation was done in the framework of generalized linear models (McCullagh and Nelder 1999) assuming a binomial distribution and a logit link function. To test the hypotheses of equality of the model parameters, we compared confidence limits, (when two intervals overlapped, the parameters were considered to be equal; otherwise they were defined as different). Finally, to compare the averages of weekly catches, we applied likelihood ratio and Tukey–Kramer tests. These comparisons of mean values were made in framework of the generalized linear model (McCullagh and Nelder 1999). Analyses were done using the GLIMMIX procedure in SAS v. 9.2 (SAS Institute Inc 2009).
Degree-days accumulated by generation of Cryptoblabes gnidiella in Uruguay from 2003–2007
500 ± 20
543 ± 19
1002 ± 10
1092 ± 04
Average number of male moths of Cryptoblabes gnidiella caught in pheromone traps at two sites in Uruguay
Average number of male moths/trap/week1
Percentage of clusters damaged by Cryptoblabes gnidiella on different grapevine cultivars in Uruguay at harvest time
Percent cluster damage
29-Jan to 5-Feb
5 to 15-March
5 to 19-March
12 to 20-March
In Progreso, damage on Cabernet Sauvignon and number of male moths caught were very low throughout the season, although this cultivar is harvested on mid-March (Table 4).
The average number of larvae per infested cluster was two on Tannat, five on Cabernet Sauvignon, and four on Gewürztraminer. Larvae were more abundant close to harvest, however at that time, a single larva was enough to degrade the cluster quality, due to colonization of fungi that cause rot. The maximum number of larvae found on a cluster was 85, on 5 March 2005 on Gewürztraminer. In no case did parasitoids emerge from larvae or pupae collected in the field and reared individually in the laboratory.
Larvae and pupae overwinter under the rhytidome or in clusters and dry leaves that persist on the plant and develop slowly due to cold temperatures. Some adults emerged sporadically inside the cloth bags, but most did so when the traps registered the first catch.
Logistic models estimated for each grapevine cultivar and for all cultivars in a joint model
95% Confidence limits
95% Confidence limits
Estimated proportions of cumulative catches for the average DD values of the logistic curve for four grapevine cultivars in Uruguay and at the end of the first generation in the joint model
Models for each cultivar
Average 742 DD
Average 833 DD
95% Confidence limits
95% Confidence limits
End of the first generation 500 DD
End of the first generation 570 DD
95% Confidence limits
95% Confidence limits
C. gnidiella presents three generations in southern Uruguay, the same as Ringerberg et al. (2005) estimated for southern Brazil, while Bagnoli and Lucchi (2001) and Coscolla-Ramon (2004) mentioned three to four generations in the wine regions of Tuscany, Italy, and Cadiz, Spain, respectively. The first generation does not cause economic damage because the berries are green. However, the second generation is responsible for the majority of the damage because it coincides with berry ripening.
Pinot noir escapes economic damage even in years when the number of male moths caught was very high because it is harvested early. Similar results were observed on this cultivar by Bisotto-de-Oliveira et al. (2007) in Bento Gonçalves, Brazil. On Tannat, the damage is slight, depending on the year, but Gewürztraminer clusters are seriously affected at harvest time. The cultivar Gewürztraminer is over-ripened to obtain a higher-quality wine. Even in the years when Tannat and Gewürztraminer had similar male moths caught and harvest dates, damage was much higher in the latter, suggesting the insect prefers this cultivar. Plant volatiles and/or grape fermentation may act as chemical signals to the pests indicating places suitable for copulation and oviposition ( Bisotto-de-Oliveira et al. 2007). In Progreso, Cabernet Sauvignon damage and catches were very low throughout the season, although this cultivar is harvested as late as Gewürztraminer. We concluded that, there was no direct relationship between male cumulative capture from December to harvest time and damage, nor was there a relationship with the maturity date of the late cultivars. Moth detection in pheromone traps enables early prediction of the start of larval feeding on clusters, but the intensity of damage is more closely related to cultivar than with adult catches.
Our results show that C. gnidiella does not have a winter diapause in southern Uruguay and does not require an alternate winter host; it can complete its entire life cycle in the vineyard. Ben-Shaul et al. (1991–1992) found similar results when they studied the overwintering of this species in avocado in Israel; larvae remained all winter in dried fruits. The low abundance of flights from the overwintering generation was probably related to the larvae mortality caused by low temperature during the winter months. Depending on the year, average temperatures were below 12°C on 52–60% of winter days. In the 2005–2006 season, spring and early summer had very low populations, despite high male moths caught at the end of the previous autumn. This resulted from a tornado that struck the area in August 2005 and killed larvae and pupae, which was confirmed by observing the remains of clusters inside the cloth bags.
According to our results, the natural parasitism does not appear as an effective measure to reduce populations. Bagnoli and Lucchi (2001), in a review of the current status of biological control in this species, reported small numbers of parasitoids in different areas of the world where the pest is widespread, although Bisotto-de-Oliveira et al. (2007) identified five species of parasitoid associated with C. gnidiella in Brazil.
Based on phenological models and population monitoring, although we use two temperatures as lower-threshold and two thermal constants, we identify three generations in both cases. Avidov and Gothilf (1960) determined the development thresholds and thermal constants from larvae fed on grapes, while Ringenberg et al. (2005) estimated those parameters from larvae fed an artificial diet, which could explain the different values. Nevertheless, both sets of values were suitable to estimate the onset and duration of C. gnidiella generations in Uruguay. The completion of the first generation was estimated with a maximum error of 2 or 3 days and the second with an error of 6 or 7 days, depending on year, regardless of the development thresholds used. Overlapping stages of development at the end of the season would explain the greater error in the second generation. The DD model could provide adequate forecasts and facilitate monitoring of insect activity in the field. Therefore, one can calculate how the pest population will develop until the harvest and take the necessary measures to prevent damage to the grapevines.
The predictive capacity of models is especially interesting when simulating population dynamics (Holt and Cheke 1997) and our models should contribute to determining the best times to implement different pest control strategies targeted at the first generation of C. gnidiella to prevent damage before harvest. The efficacy of pesticides is related to the percentage of emergent adults and to egg hatch, particularly in species with hidden larval stages (Butcher and Haynes 1960). Conventional control of this pest in its larval stage has not been very efficacious (Bisotto-de-Oliveira et al. 2007). This model could be very useful to improve the efficacy of insect-growth-regulator pesticides, which require precisely timed applications (Ascher et al. 1983), and facilitate the application of insecticides at the egg stage. However, additional data will be needed to validate the model. Analysis by cultivar, despite having no repetitions in space, allowed to verify that population growth was not affected by the specific characteristics of one cultivar. Therefore, we could analyse the pool of information to get a single model where "the cultivar" became a repetition in space. This is the first contribution of a widest line of research planned to study the spatial distribution of C. gnidiella in the whole area of viticulture production in Uruguay.
We express our thanks to the Comisión Sectorial de Investigación Científica (CSIC) of the Universidad de la República and to the Instituto Nacional de Vitivinicultura (INAVI) for their financial support of this project. Special thanks go to the Juanicó and Pisano establishments for allowing and helping with this research in their vineyards.
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