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Article

Monitoring and Occurrence Prediction of the Migration Population of Helicoverpa armigera (Hübner) Based on Adult Semiochemical Attractants

by
Wei He
1,2,
Chunyang Lv
2,
Haowen Zhang
2,
Xinzhu Cang
2,
Bo Chu
3,
Xianming Yang
2,
Gemei Liang
2 and
Kongming Wu
2,*
1
State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2
State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
3
College of Plant Protection, Henan Agricultural University, Zhengzhou 450002, China
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(7), 1497; https://doi.org/10.3390/agronomy14071497
Submission received: 11 June 2024 / Revised: 7 July 2024 / Accepted: 8 July 2024 / Published: 10 July 2024
(This article belongs to the Section Pest and Disease Management)
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Versions Notes

Abstract

:
Helicoverpa armigera (Hübner) is a destructive agricultural pest. Facultative migration usually causes regional catastrophes; therefore, developing a simple and easy new technology for the monitoring and early warning of immigrant populations is urgent. Between 2021 and 2023, we conducted a population-monitoring study on H. armigera immigrants in Xundian County, Yunnan Province, where the migration pathway for pests from southeast Asia extends to southwest China. Based on the differences in the reproductive organ development parameters of H. armigera at different ages, we established an adult age discrimination model. The monitoring results of field populations with semiochemical attractants and sex pheromones between 2021 and 2023 showed that the daily average age of the adult population of H. armigera fluctuated above 6 days, and the trapping dynamics with semiochemical attractants and sex pheromones were the same. Both trapping methods yielded H. armigera males of different ages and had identical age structures, indicating that the H. armigera population primarily migrated from other regions. The trajectory analysis showed that the H. armigera population that migrated to Xundian between May and September was primarily from South Kunming, and after October, it was primarily the southward-migrating population north of Qujing City, Yunnan Province. Based on the relationship between the daily average fecundity and the age of H. armigera, a dynamic prediction model for the fecundity of the immigrant population was established. In this study, the prediction models and methods based on semiochemical attractants could potentially be used in the surveillance and population alerting of H. armigera.

1. Introduction

Helicoverpa armigera (Hübner), a member of the Noctuidae family within Lepidoptera, poses a significant threat to global agriculture [1]. Though it is widespread in Asia, Africa, Europe, and Oceania, recent invasions have occurred in many countries in South America [2,3,4]. H. armigera is a polyphagous pest that infests over 30 families and 200 plants, including corn, soybeans, sunflowers, sorghum, key crops, vegetables, and fruits [5,6]. The young larvae initially consume the host’s tender stems, leaves, and buds. Subsequently, the mature larvae detrimentally affect the reproductive organs and fruits of the plant [7]. The adults’ migratory capability, coupled with their high fertility, exacerbates global infestations of H. armigera, threatening global agriculture [8,9,10,11,12]. H. armigera inflicts over USD billion in annual damage globally [13].
H. armigera infestation in immigrant regions causes considerable damage to local crop yields, with rapid and severe effects on regional economies and ecosystems [14]. Pest monitoring is a pivotal part of an integrated pest management framework that provides timely pest infestation insights to agricultural practitioners, guiding precise control measures and avoiding large-scale pest outbreaks [15]. Therefore, effective and accurate methods for monitoring migratory populations within H. armigera-invasive regions are crucial. H. armigera migration begins at the early stage of reproductive organ development and ends at the mature stage [16]. In immigrant areas, the reproductive organs of most adult H. armigera are more mature. Previous methods for monitoring migrating H. armigera populations involved dissecting many adults captured using lights and sex pheromones to observe their reproductive organ development and determine their immigrant status [8,16,17]. However, light trapping often involves high-temperature baking devices, killing numerous pests and beneficial insects, complicating their classification [18,19,20,21]. Sex pheromone monitoring targets only males, making it impractical to predict the larvae of the next generation based on female fecundity dynamics [22].
Previous studies have shown that some host plant volatiles, such as 2-phenylethanol, benzaldehyde, and (Z)-3hexenyl salicylate, have a significant role in attracting H. armigera adults [23,24]. Following the evolution of chemical analysis technologies, various volatile plant compounds attractive to H. armigera have been isolated and identified [25,26]. Semiochemical attractants are a type of adult behavior regulator developed based on the host plant volatiles’ preferences for herbivorous pests [22,26,27]. It can synergistically lure both sexes, offering convenience and eco-safety. These attributes position them favorably for H. armigera monitoring applications, with substantial potential [24,25,26].
A field test of H. armigera semiochemical attractants revealed their efficiency in monitoring insect population dynamics. This tool can further elucidate population reproductive development dynamics [28]. Methods for monitoring and predicting migratory H. armigera populations using semiochemical-based bait are lacking. Influenced by the offshore southwest monsoon, China’s Yunnan Province experiences winter northwest winds, whereas the summers experience a predominant southwest wind, forming a significant migration channel for pests from southeast Asian countries to migrate into southwest China [29]. Xundian County in northeastern Yunnan Province falls along the migratory channel, experiencing arid winters, spring droughts, and wet summers and falls. An ideal environment for insects supports abundant plant life and the survival of various species. In this study, semiochemical attractants were used to trap adult immigrant populations of H. armigera in Xundian County between 2021 and 2023. The methods for monitoring and predicting adult immigrant populations were investigated using trajectory analyses and reproductive system dissections. The aim was to develop an accurate monitoring and forecasting framework for H. armigera, utilizing semiochemical attractants and enhancing regional monitoring and comprehensive control strategies.

2. Materials and Methods

2.1. Analysis of Reproductive Organ Development and Fecundity of Immigrant and Local Adult H. armigera Populations

2.1.1. Insects

In late June 2023, the local population of H. armigera was collected from the corn fields of farmers in Jinyuan Township (Xundian County), Yunnan, China (25°50′34.5′′ N, 103°7′12.2′′ E). Based on the morphological characteristics of H. armigera larvae described in reference [30], over 50 6th-instar or older larvae of H. armigera were accurately identified and sampled from the corn fields and placed in plastic boxes (22 × 15 × 8 cm). Then, the H. armigera larvae were transferred to artificial climate boxes (MGC-450HP, Yiheng Technology Instrument Co., Ltd., Shanghai, China) and fed with an artificial diet in plastic cups (25 mL, 38 × 30 × 30 mm) for pupation [31]. Each plastic cup contained only one H. armigera larva. When eclosion was completed, the adults were moved to a cage (35 × 35 × 35 cm, 200 mesh) and reared with cotton balls containing a 5% (v/v) honey/water solution (Beijing Baihua Bee Products Technology and Development Co., Ltd., Beijing, China), and the offspring of the local population were procured after female H. armigera oviposition. During the peak period of H. armigera immigration in late June 2023, the female moths were trapped with semiochemical attractants in the cornfield, and their eggs were collected as the offspring of the immigrant population. The environmental parameters for the artificial climate boxes were established as follows: 25 ± 1 °C, 75 ± 5% RH, and a 16:8 (L:D) photoperiod.

2.1.2. Experimental Methods

A total of 800 F1-generation larvae from local and immigrant H. armigera populations were reared in plastic cups (25 mL, 38 × 30 × 30 mm) filled with an artificial diet (15 × 15 × 15 mm) in the artificial climate boxes, respectively. Each cup was reared one 1st instar larvae from the local or immigrant population until pupation. Throughout the daily observations, the freshness of the artificial feed was assessed. If spoilage occurred, it was promptly replaced with a fresh supply. Upon adult emergence, both the female and male adults were distinguished based on differences in their external genitalia [7]. Adults from the same population with identical eclosion times (eclosion time disparity < 6 h) were relocated to the cages (35 × 35 × 35 cm, 200 mesh). A total of 20 adults were arranged per case (♀:♂ = 1:1) and offered a daily diet of 5% honey water-soaked cotton balls, and the eclosion timings were marked on the cases. For the adult males and females aged 1–12 days, the reproductive organs were dissected, and the reproductive development status (i.e., ovarian development level, egg load, or testis major axis length) was assessed. At ages 1–12 days, in the local and immigrant H. armigera populations, over 10 females and 20 males were dissected for each age. We used the method of He et al. [28] for reproductive organ dissection. Under a stereomicroscope (TS-75X, Shanghai Shangguang New Optical Technology Co., Ltd., Shanghai, China), the body wall was torn open from the abdomen using anatomical forceps, excess tissue was removed, and the testes and ovaries were separated. The ovarian development level was assessed according to the classification by He et al. [28]. The dissected testes were positioned in a 3 cm saline-filled plastic Petri dish. The major axis length of the testes was measured using an OLD-SGD imaging system (Shanghai Shangguang New Optical Technology Co., Ltd., Shanghai, China) under a stereomicroscope platform.
A total of 240 F1-generation larvae each from the local and immigrant H. armigera populations were reared using the feeding methods described above. Each population consisted of 80 H. armigera larvae and was replicated three times. Upon adult emergence, the adults of local and immigrant populations were separately maintained in 500 mL transparent plastic cups (♀:♂ = 1:1; a pair of adults/cup) and fed daily with 5% (v/v) honey water. The cup mouths were covered with sterile gauze (10 × 10 cm) to allow the female adults to lay eggs. The cups were labeled with female and male numbers (1–240). Adult oviposition and mortality were monitored each day, and new sterile gauzes were replaced on the cup mouths daily. Based on the number of females in the cups, the sterile gauzes with eggs were placed in 12 × 17 cm clear plastic self-sealed bags marked with the same number for fecundity assessment, respectively. The daily fecundity of each female was counted, with subsequent calculations of the daily mean fecundity of different H. armigera populations.

2.2. Monitoring Methods for the Quantitative Dynamics and Reproductive Development State of H. armigera in the Field

2.2.1. Field Monitoring Materials

The monitoring materials included bucket traps (consisting of four parts: rain cover, lure hanger, inverted funnel, and insect collecting bucket; Figure S1), boat-shaped traps (consisting of three parts: a boat-shaped plastic upper cover, a lure hanger, and removable sticky liners; Figure S1) [22], fixed rods (2 m), H. armigera semiochemical attractants, and sex pheromones. The semiochemical attractants consisted of a blend of benzaldehyde, salicylaldehyde, n-heptanal, n-octanol, phenylethanol, and benzyl acetate, with a total of 4.5 g of the blend of compounds provided on a polyester fiber solid [22]. The sex pheromones were composed of Z11-16:Ald and Z9-16:Ald at a 93:7 ratio, with 12 mg of active ingredient provided on a polyvinyl chloride capillary [32]. The traps were baited only with the blend of semiochemical attractants or with sex pheromones in the capillaries alone. The monitoring materials were obtained from Shenzhen Bioglobal Agricultural Science Co., Ltd. (Shenzhen, China).

2.2.2. Field Monitoring Methods

A field monitoring study was conducted in both corn and wheat fields at Jinyuan Township of Xundian County in Yunnan, China, between 2021 and 2023. This region benefits from abundant water and light, with an agricultural area of 192.50 hectares. The main crops grown here are corn, rice, and wheat. Corn and rice are cultivated between May and September, whereas wheat is sown between October and April of the subsequent year. The 3-year field monitoring experiment was conducted between 1 May and 5 November 2021, 15 June and 15 November 2022, and 18 May and 5 November 2023. During the 2021 monitoring, four corn plots of equivalent size (2001 m2), consistently cultivated and uniformly managed, were selected in Jinyuan Township, with a plot separation exceeding 1 km. Our previous studies confirmed that using semiochemical attractant solids in boat-shaped traps and capillaries containing sex pheromones in bucket traps was the most efficient technique for trapping H. armigera [22,28]. Six boat-shaped traps, each with a semiochemical attractant, were positioned at 30 m intervals throughout each corn plot. Simultaneously, a bucket trap incorporating a capillary containing sex pheromones was established 50 m away from boat-shaped traps as the trial control. A total of 24 boat-shaped and four bucket traps were placed in four corn plots. The boat-shaped traps were affixed to the upper 20 cm of the corn, and their height was modified based on the crop growth height, whereas the bucket traps were always set 1.5 m above the soil level. The semiochemical attractants and sex pheromones were replaced every 20 or 30 days, respectively. After the September corn harvest, all traps were relocated to an adjacent wheat field during the tillering phase, following the previous trap arrangement. The experimental plot count was expanded to five in 2022 and 2023, maintaining identical trap placement standards as those in 2021. Over a 3-year monitoring period, daily morning counts were conducted for male and female H. armigera within all traps. The trapped H. armigera species were transferred to the laboratory for the dissection of the reproductive organs and an assessment of the reproductive development state. A total of 20 males and females (per bait type) were dissected daily, and all were dissected if the capture count fell below 25.
By dissecting the H. armigera trapped using the semiochemical and sex attractants and bringing the reproductive developmental parameters (ovarian development level, egg load, and testis major axis length) into models (1) or (2), the age of the trapped adults could be obtained. We used the trapping adult age in the field to judge the immigrant or local populations. More specifically, if the adults trapped using semiochemical attractants are older than 3 days for more than a few days, this indicates that they are immigrant populations. If the age of adult trapping increases periodically from a low age (1–2 days old) to a high age (≥8 days old), this indicates a local population [22,28].
Because the samples of H. armigera trapped by semiochemical attractants in May were not preserved at low temperatures in time, the samples had decomposed and could not be dissected; the anatomical data of the samples began to be recorded in mid-June. In 2021, since the samples of the males of H. armigera trapped by sex pheromones were not collected, male H. armigera samples using sex pheromones were not dissected; therefore, the ages of the males trapped using sex pheromones for that year were not analyzed. In 2023, randomly selected samples of 100 males captured via semiochemical baiting and 100 males trapped using sex pheromones were analyzed for age composition.

2.3. Simulation Method for the Migration Trajectory of H. armigera

The trajectory analysis of migrant populations of H. armigera was performed using the Hybrid Single-Particle Lagrangian Integrated Trajectory model developed by the National Oceanic and Atmospheric Administration and the Bureau of Meteorology [33]. The trajectory analysis model involved using the US National Oceanic and Atmospheric Administration Air Resources Laboratory Global Data Assimilation System meteorological dataset, featuring a global resolution of one latitude and one longitude. By using the Xundian experimental site as a starting point for the trajectory analysis, 12 h backward flight trajectories were computed on the peak H. armigera migration days (i.e., the dates of high trap counts). The H. armigera migration parameters were established based on studies by Feng et al. [8] on the radar monitoring of H. armigera high-altitude flight: (1) assuming the active flight capacity of H. armigera was neglected, downstream migration was postulated; (2) H. armigera commenced flight 1 h post-sunset and concluded 1 h before sunrise (by accounting for local dawn and dusk times, the H. armigera ascent and descent times were 20:30 and 5:30, respectively); (3) H. armigera flight altitude was programmed at 100–1000 m above ground, with an interval of 100 m across 10 altitude gradients; (4) the presumed suitable host plants and crops followed the migration route, aiding with potential take-offs and landings; (5) when the upper air temperature was <10 °C, the H. armigera adults stopped flying, and the trajectory simulation was terminated [34]. ArcGIS Pro 3.0 (Esri, CA, USA) was used to visualize the migration trajectory of H. armigera.

2.4. Prediction and Verification Method for the Fecundity of Trapped Adults in the Field

The fecundity of the local population was estimated using the integral prediction of the local population fecundity. In contrast, the immigrant population fecundity was calculated using the integral of the immigrant population fecundity prediction. To forecast the daily mean fecundity (total number of eggs laid from the trapped adult age to death) of adults trapped using semiochemical attractants, the lower limit (a) of the integral of the daily average fecundity function was the daily average age of those adult H. armigera trapped using semiochemical attractants, and the upper limit (b) was the age upon the death of H. armigera in the field. By assuming the same lifespan for the H. armigera in the field (as in the laboratory), based on the average adult lifespan in the fecundity analysis of local and immigrant populations, we set the lifespan of the local and immigrant populations of adult H. armigera in the field to 15 and 18 days, respectively. According to the different H. armigera populations, the upper predicted integrals of the daily average fecundity function were set at 15 and 18.
The occurrence of H. armigera in the field was investigated to verify the accuracy of the fecundity prediction. The investigation commenced in May and ended in November annually in 2022 and 2023. Every 7 days, five traps and three unprocessed (500 m away from the trapping plots) plots were investigated. During the corn seedling stage, the H. armigera larvae mainly damage leaves [35]. The pilot survey involved a 5-point sampling method, interviewing 50 maize plants and examining selected critical damage sites, such as the leaf surface and underside, tassel, and fruit regions. After the corn harvest in October, the wheat fields were investigated using the same method. The data were carefully recorded, including H. armigera larva counts and larval development stages per plant.

2.5. Statistical Analyses

SPSS 26.0 (IBM, Armonk, NY, USA) was used for statistical analysis and model fitting. Before statistical testing, the normality and homogeneity of variance were confirmed. Nonparametric analysis was performed if the normality criteria were not met. The percentage data were transformed into the square roots of the arc sine before variance assessment. A two-way analysis of variance (two-way ANOVA) was used to assess the ovarian development level, egg load, and testis major axis length in H. armigera across populations and ages. As a post hoc test, we used Tukey’s honest significant difference (HSD) test. A t-test was used to analyze the significant differences in the average daily number of H. armigera attracted by a single trap between semiochemical attractants and sex pheromones. Chi-square analysis was used to assess the differences in sex ratio (female-to-male ratio: 1:1) and male age structure among the individuals captured in baited traps containing semiochemical attractants or sex pheromones. Similarly, we used Spearman’s correlation analysis to associate the number of H. armigera males and adults (males and females) in the semiochemical bait traps with the males in the sex pheromone-baited traps and to associate the predicted fecundity dynamics from 23 May to 3 July and 14 August to 24 September in 2023 with the population dynamics of H. armigera larvae in the field. The relationship between the ovarian development level, egg load, testis major axis length, average daily fecundity, and age of adult H. armigera was fitted using curvilinear models. The R2 values of various curve models were compared, and the model with the R2 value closest to 1 and the simplest model parameters was selected as the fitting model.

3. Results

3.1. Construction of Adult Age Determination Model and Daily fecundity Model

There were no significant differences in the ovarian development level, egg load, or testis major axis length between the local and immigrant populations (Table 1; Figure 1A–C). No significant interplay was found between population and age (Table 1). However, significant differences were observed in the ovarian development level, egg load, and testis major axis length of H. armigera across various ages (Figure 1A–C). The ovarian development level of females increased gradually with age (Figure 1A), and the egg load increased before decreasing with age (Figure 1B). The functional relationship between ovarian development level, egg load, and female age was captured according to the following:
y = −0.0020x1 + 1.7953x2 + 1.5228 (F2,239 = 886.345, p < 0.001, R2 = 0.9186)
where y is the age, x1 is the egg load, and x2 is the ovarian development level. The major axis length of the male testes decreased with age (Figure 1C). This functional relationship was captured as:
y = 6.802x2 − 172.031x + 2678.256 (F2,471 = 866.932, p < 0.001; R2 = 0.7871)
where y is the testis major axis length, and x is the age.
The daily average fecundity of H. armigera in the local and immigrant populations increased before decreasing with age (Figure 1D,E). The functional relationship between the daily mean fecundity of the local population and female age was captured as:
y = 164.9 − 218.5x + 77.50x2 − 9.467x3 + 0.4754x4 − 0.0085x5 (p < 0.001, R2 = 0.9263)
where y is the daily mean fecundity, and x is the female age. The functional relationship between the daily mean fecundity of the immigrant population and female age was captured as:
y = −57.86 + 41.81x − 3.847x2 + 0.095x3 (p < 0.001, R2 = 0.8989)
where y is the daily mean fecundity, and x is the female age.

3.2. Age Dynamics of H. armigera Population Trapped Using Semiochemical Attractants in the Field

By dissecting the H. armigera trapped using semiochemical and sex attractants and bringing the reproductive developmental parameters (ovarian development level, egg load, and testis major axis length) into model (1) or (2), the age of the trapped adults could be obtained. In 2021, 228 H. armigera adults trapped using semiochemical attractants were dissected. In 2021, the maximum daily average age of the captured adults was 12.00 ± 0.00 days. The minimum was 2.69 ± 0.54 days, and the daily average age of the adults trapped was over 6 days on most days. The mean age of the H. armigera trapped using semiochemical attractants was 2.69 ± 0.54 days on 3 August, and the daily average age gradually increased with time (Figure 2A).
Age dynamics analysis was not performed in 2022 because the number of H. armigera trapped using semiochemical attractants was low. A total of 1235 male H. armigera trapped using sex pheromones were dissected in 2022. The highest and lowest daily mean ages of the trapped males were 12.00 ± 0.00 d and 6.30 ± 0.66 days, respectively, consistently fluctuating by 6 days (Figure 2C).
In 2023, 222 adults trapped in the semiochemical lures were dissected. The maximum and minimum daily mean ages of the adults trapped were 12.00 ± 0.00 and 6.17 ± 1.05 days, respectively, with the daily mean ages exceeding 6 days (Figure 2B). A total of 1512 males trapped using sex pheromones were dissected. The highest and lowest daily mean ages of trapped males were 12.00 ± 0.00 and 7.5 ± 1.57 days, respectively, most of which fluctuated above 8 days (Figure 2D). The H. armigera field populations at the Xundian experimental site throughout the monitoring periods of 2021, 2022, and 2023 were predominantly migrant individuals, with a few local populations.
The trapped adults’ age composition results showed that the semiochemical attractants- and sex pheromones-trapped males aged 3–12 days and not 1–2 days. The largest number of males were trapped using the semiochemical attractants and sex traps at 12 days, accounting for 64% and 61%, respectively (Figure 2E). There were no significant differences in the age structure of the males trapped between the two trapping methods (χ2 = 8.483, p = 0.486).

3.3. Quantitative Dynamics and Trajectory of the Migration Population of H. armigera

During the 2021 field monitoring, five critical H. armigera trapping peaks using semiochemical attractants occurred in mid-May, early June, early July, mid-August, and mid-October (Figure 3A). There were three peak periods for sex pheromone trapping: early June, early July, and mid-August (Figure 3A). Because the monitoring time for sex pheromones in 2021 was between 5 June and 27 August, the occurrence of H. armigera in May and October was not recorded. In 2022, the number of H. armigera trapped using the semiochemical attractants was lower, and dynamic analysis was not performed. There were two peak periods for sex pheromone trapping in 2022: mid-late July and mid-October (Figure 3B). There were four peak trapping periods for the semiochemical attractants in 2023: late May, late June, early August, and late September to early October (Figure 3C). Sex pheromone trapping peaked in late May, early July, late September, and mid-October 2023 (Figure 3C). In 2021 and 2023, the number of males trapped using the semiochemical attractants was correlated with that caught in pheromone-based traps (2021: r = 0.220, p = 0.044; 2023: r = 0.217, p = 0.005). A similar trend was observed for the total number of adults (males and females) (2021: r = 0.221, p = 0.046; 2023: r = 0.211, p = 0.006).
During the 3-year monitoring period, the semiochemical attractant traps caught average daily numbers of 0.33 ± 0.03 (2021), 0.04 ± 0.02 (2022), and 0.27 ± 0.3 (2023) H. armigera adults per trap. In contrast, the sex pheromone traps yielded average daily numbers of 2.01 ± 0.31 (2021), 5.04 ± 0.47 (2022), and 12.26 ± 0.61 (2023) H. armigera adults per trap. The sex pheromone traps consistently yielded a higher daily catch than the semiochemical attractant traps (2021: t = 5.357, p < 0.001; 2022: t = 10.739, p < 0.001; 2023: t = −19.70, p < 0.001).
The semiochemical-based traps yielded 153 females and 172 males in 2021, 10 females and 14 males in 2022, and 49 females and 182 males in 2023. Over the 3 years, the females trapped using semiochemical attractants accounted for 47.08% (2021), 41.67% (2022), and 21.21% (2023) of the total trap catches. The number of males trapped using semiochemical baits in 2023 surpassed that of females, whereas no significant differences were observed between the females and males trapped in 2021 and 2022 (2021: χ2 = 1.111, p = 0.292; 2022: χ2 = 0.667, p = 0.414; 2023: χ2 = 76.576, p < 0.001).
Based on the peak period of monitoring semiochemical attractants and sex pheromones between 2021 and 2023, the trajectory of the H. armigera immigrant population was analyzed to infer the place of origin. During the 2021 monitoring, trajectory analysis was conducted based on the peak days of H. armigera trapping on 12–18 May, 5–12 June, 2–8 July, 13–19 August, and 11–17 October. When trapping peaked in May, June, July, and August, the H. armigera population primarily migrated northward, whereas in October, it migrated southward (Figure 4A). The northward-migrating population was primarily from the central region of Kunming City and Chuxiong City of Yunnan Province and the southern part of Qujing City in Yunnan Province, whereas the southward-migrating population was primarily from the northern part of Qujing (Figure 4D). During the 2022 monitoring, trajectory analysis was performed based on the peak days of H. armigera trapping on 21–30 July and 10–18 October. The H. armigera population primarily migrated northward in July and southward in October (Figure 4B). The northward-migrating population primarily originated from the central part of Kunming City, whereas the southward-migrating population originated from the northern part of Qujing City (Figure 4E). During the 2023 monitoring period, a trajectory analysis was performed based on the peak days of H. armigera trapping on 23–29 May, 22–29 June, 6–12 August, and 24 September to 2 October. When trapping peaked in May, June, and August, the H. armigera population migrated primarily northward, whereas, between September and October, it was a mixture of northward and southward migrations (Figure 4C). The northern migration population was primarily from the central part of Kunming and the southern part of Chuxiong, whereas the southward migration population was primarily from the central part of Qujing City (Figure 4F).

3.4. Prediction and Verification of the Fecundity of Trapped Adults in the Field

By integrating daily fecundity models (3) and (4), the fecundity prediction models of different populations could be established:
∫ a b 164.9 − 218.5 x + 77.50 x 2 − 9.467 x 3 + 0.475 x 4 − 0.0085 x 5 d x
∫ a b − 57.86 + 41.81 x − 3.847 x 2 + 0.095 x 3 d x
In the fecundity prediction models of the local (5) and immigrant (6) H. armigera populations, a and b refer to the age of adult H. armigera, and the fecundity of the corresponding age range can be obtained by introducing two ages into integral models (5) or (6).
As the H. armigera population in Xundian primarily comprised immigrants, the average daily age of adults trapped using the semiochemical attractants was included in model (6) to predict the fecundity of the H. armigera population in the field. The results showed that, during the 2021 monitoring, the predicted fecundity of the H. armigera population was highest (781.80) on 3 August and lowest (159.01) on 8 July and 12 October. In 2021, the predicted fecundity in the field was low on 8 July, 13 August, and 12 October and increased before decreasing with time (Figure 5A). In 2023, the H. armigera population exhibited maximum fecundity (581.86) on 20 July and minimum fecundity (152.92) on 2 October. In 2023, predicted fecundity increased before decreasing from 23 May to 3 July and 14 August to 21 September (Figure 5B). Field survey data from 2023 indicated that the number dynamics of H. armigera larvae in the field increased before decreasing from 22 May to 3 July and 14 August to 24 September (Figure 5C). The predicted fecundity from 22 May to 3 July and 14 August to 24 September in 2023 was significantly correlated with the number of H. armigera larvae in the field (From 22 May to 3 July: r = 0.750, p = 0.043; From 14 August to 24 September: r = 0.982, p < 0.001). The number dynamics of H. armigera larvae in the field from 22 May to 3 July and 14 August to 24 September in 2023 were approximately consistent with the predicted fecundity dynamics, validating the accuracy of the fecundity prediction result in 2023.

4. Discussion

Pest monitoring provides precise pest information, enables informed pest control decisions, and mitigates crop losses [36]. Furthermore, a scientific forecasting system can be established based on monitoring data to implement effective control measures to manage future pest outbreaks. In this study, an adult age discrimination model of H. armigera based on reproductive development was established, which can be used to determine adult age and investigate the source properties of the H. armigera population in the field. We demonstrated the migration paths of H. armigera over various years using annual population monitoring data with semiochemical attractants. Finally, we analyzed the fecundity of local and immigrant H. armigera populations, built a prediction model of fecundity for diverse populations, and confirmed this using field investigation data. In this study, the prediction models and methods based on semiochemical attractants could potentially be used in the surveillance and population alerting of H. armigera.
Insect reproductive development state influences adult migration, mating, spawning behavior, and the regulation of population change [37,38]. This study showed that ovarian development level, egg load, and testis major axis length did not vary significantly across H. armigera populations. Yet, there were significant differences in these parameters among adults of different ages. Previous studies have shown that there are significant differences in the ovarian development level, egg load, and testis major axis length at different ages in Spodoptera frugiperda and H. armigera [22,28]. This study corroborates previous studies, indicating that age is a primary determinant of reproductive organ development in H. armigera, with an insignificant influence on population variation. Thus, a functional model for H. armigera reproductive organ development linked to age may be used to estimate the ages of adult populations. The previous monitoring methods usually judged the migration or emigration of H. armigera populations according to the maturity of reproductive organ development [16], but reproductive organ development is a continuous process, and it is not accurate to use this to predict the migration or emigration of H. armigera populations. The age discrimination model established in this study can more accurately monitor the migration or emigration of H. armigera populations based on the age structure of a population.
In this study, the average age of the adult population of H. armigera in Xundian fluctuated above 6 days, indicating a primarily immigrant population. In Xinxiang City, Henan Province, China, the lowest daily average age of the H. armigera population trapped using semiochemical attractants (local population) was approximately 1 day and showed an increasing trend from low age (1 day old) to high age (over 8 days old) in the generation cycle [28]. The results of this study differ significantly from those of Xinxiang’s H. armigera monitoring, possibly owing to population differences. The adult occurrence stages of H. armigera in the local population include eclosion, peak, and end stages, and the age of adults gradually increases from low to high. However, individuals in the immigrant population have completed autologous development, and the number of young (<3 days old) individuals is low or nonexistent [39,40]. Notably, the mean trapping age of adult H. armigera using semiochemical attractants was merely 2.69 days around 3 August 2021, and the adult trapping age progressively advanced over time. Nevertheless, there was no apparent peak in trapping on 3 August, indicating that the day marked the peak eclosion period for the local population, contributing to the lower age of the adults trapped. Similarly, we compared the age structures of the males trapped using semiochemical attractants and sex pheromones. The results showed that the two trapping methods could be used to trap 3–12-day-old adults, and there were no significant differences in the age structure of the trapped males; however, 12-day-old males were mostly trapped using both, whereas younger males were less frequently trapped. This may be because the H. armigera population in the field was predominantly comprised of immigrants. The immigrant population primarily constituted mature males, causing a higher proportion of older males.
The monitoring data indicated that semiochemical attractant monitoring had the potential to reflect the field trends observed using sex pheromone monitoring. However, the average daily catch using semiochemical traps was less than one compared to the sex pheromone traps. This discrepancy may be attributed to interference from background odors in the field. The volatiles released by plants in the field can compete with and inhibit the components of semiochemical attractants, thereby affecting their efficacy. For example, a high concentration of benzaldehyde in a tea garden can overlap with the benzaldehyde in the semiochemical attractant for Empoasca pirisuga, reducing its attractiveness [41]. In addition, the release rate of volatile compounds in semiochemical attractants and the application method can influence their insect-trapping ability. Moreover, using unmanned aerial vehicles to spray liquid semiochemical attractants with insecticides on the top leaves of the crop shows that each spray belt (length 10–20 m; width 0.05–0.1 m) can kill more than 50 adults H. armigera per day [42]. Therefore, future field monitoring experiments should focus on optimizing the composition ratio of semiochemical attractants and selecting more suitable application methods to enhance the trapping efficiency of semiochemical attractants for H. armigera.
Furthermore, the study revealed no significant differences in the number of females and males trapped using semiochemical attractants between 2021 and 2022, and the proportion of females trapped in 2023 was only 21.21%, which was significantly lower than that of males. By using semiochemical attractants to trap H. armigera in the field, He et al. [28] showed that the sex ratio was close to 1:1, which is similar to the results of our study in 2021–2022. The large difference in the numbers of females and males trapped in 2023 may be related to the migration of female H. armigera. For example, S. frugiperda females terminate migration prematurely because of mating and oviposition, significantly reducing the proportion of light traps that catch females [43].
The results of 3-year monitoring showed that H. armigera migrated to Xundian between May and October yearly, and the peak migration period varied with the year. The trajectory analysis showed that H. armigera migrated to the Xundian monitoring site between May and September, primarily from South Kunming, and after October, it was primarily the southern migration population in North Qujing City. The trajectory analysis of S. frugiperda in the Xundian region showed that migration primarily occurred northward between May and September and southward in mid-October [22]. Our results are similar to the migration patterns of S. frugiperda in Xundian County, which may be related to high-altitude airflow. The southwest wind prevails in Yunnan Province during the summer half-year, which is conducive to the northward migration of insects that can migrate independently, whereas the northwest wind prevails during the winter half-year, causing southward insect migration [29].
Our field larva population survey data in 2023 may verify the accuracy of the fecundity prediction result in 2023. However, one year’s worth of field survey data alone is insufficient to verify the accuracy of the fecundity prediction model. In the future, we will conduct long-term monitoring and field investigations over multiple years to further verify and optimize the fecundity prediction model. Previous studies often relied on historical meteorological and trapping adult records to establish statistical models for predicting the fecundity of the H. armigera populations in the field [44,45,46,47]. However, these models do not account for the variation in fecundity of female H. armigera with age. Our study demonstrated that the fecundity of female H. armigera varies significantly with age, indicating that a prediction model that incorporates both the age and fecundity of females may offer greater accuracy.
Our previous research established an age discrimination model based on the reproductive development rules of the laboratory populations of H. armigera and predicted the spawning status of female H. armigera based on the egg load of trapped female adults [28]. However, there may be differences in reproductive development rules between the laboratory and field populations, so the age discrimination model based on laboratory populations may not be accurate enough. In addition, the egg load of female adults continues to increase with the development of the female adult ovaries. Therefore, it may not be accurate to predict the egg-laying status of H. armigera females based on the egg load of trapped females. In this study, we established a more accurate age discrimination model by investigating reproductive development patterns in local and immigrant populations. Furthermore, we also established a more accurate fecundity prediction model based on the age and fecundity of female H. armigera. Our study showed that boat-shaped traps baited with semiochemical attractants could further predict the fecundity of H. armigera populations in the field and might be more promising in monitoring H. armigera. Therefore, in the future, when monitoring the dynamics of H. armigera immigrant populations, it may be possible to consider using boat-shaped traps with semiochemical attractants.

5. Conclusions

We established a monitoring and prediction methodology via adult H. armigera population trapping using semiochemical attractants. The monitoring method further delineated the migratory trajectories and source areas of the H. armigera immigrant population. We also developed models to forecast the fecundity of field H. armigera populations. Our investigation can guide the use of nonchemical and preventive measures in the source area and migration region of H. armigera, provide accurate control, avoid the excessive use of chemical controls, and contribute to developing regional pest monitoring and early warning systems.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy14071497/s1, Figure S1: Trapping of H. armigera with boat-shaped (A) and bucket traps (B) in the field.

Author Contributions

Conceptualization, W.H., C.L., H.Z., X.C., B.C., X.Y., G.L. and K.W.; methodology, W.H. and K.W.; software, W.H., C.L., H.Z., X.C. and B.C.; validation, W.H., X.Y., G.L. and K.W.; writing—original draft preparation, W.H.; writing, W.H., C.L., H.Z., X.C., B.C., X.Y., G.L. and K.W; visualization, W.H., C.L., H.Z., X.C., B.C., X.Y., G.L. and K.W; supervision, K.W.; project administration, K.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the STI 2030—Major Projects (2022ZD04021) and the National Modern Agricultural Industry Technology System Construction Fund of China (CARS-02).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Riaz, S.; Johnson, J.B.; Ahmad, M.; Fitt, G.P.; Naiker, M. A review on biological interactions and management of the cotton bollworm, Helicoverpa armigera (Lepidoptera: Noctuidae). J. Appl. Entomol. 2021, 145, 467–498. [Google Scholar] [CrossRef]
  2. Murúa, M.G.; Scalora, F.S.; Navarro, F.R.; Cazado, L.E.; Casmuz, A.; Villagrán, M.E.; Lobos, E.; Gastaminza, G. First record of Helicoverpa armigera (Lepidoptera: Noctuidae) in Argentina. Fla. Entomol. 2014, 97, 854–856. [Google Scholar] [CrossRef]
  3. Castiglioni, E.; Clérison, R.P.; Chiaravalle, W.; Jonas, A.; Ugalde, G.A.; Jerson, V.C.G. Primer registro de ocurrencia de Helicoverpa armigera (Hübner, 1808) (Lepidoptera: Noctuidae) En Soja, En Uruguay. Agrociencia 2016, 20, 31–35. [Google Scholar] [CrossRef]
  4. Arnemann, J.A.; James, W.J.; Walsh, T.K.; Guedes, J.V.C.; Smagghe, G.; Castiglioni, E.; Tay, W.T. Mitochondrial DNA COI characterization of Helicoverpa armigera (Lepidoptera: Noctuidae) from Paraguay and Uruguay. Genet. Mol. Res. 2016, 15, 1–8. [Google Scholar] [CrossRef] [PubMed]
  5. Fitt, G.P. The ecology of Heliothis species in relation to agroecosystems. Annu. Rev. Entomol. 1989, 34, 17–53. [Google Scholar] [CrossRef]
  6. Arnemann, J.A.; Roxburgh, S.H.; Walsh, T.; Guedes, J.V.; Gordon, K.H.; Smagghe, G.; Tay, W.T. Multiple incursion pathways for Helicoverpa armigera in Brazil show its genetic diversity spreading in a connected world. Sci. Rep. 2019, 9, 19380. [Google Scholar] [CrossRef] [PubMed]
  7. Zalucki, M.; Murray, D.; Gregg, P.; Fitt, G.; Twine, P.; Jones, C. Ecology of Helicoverpa armigera (Hubner) and Heliothis punctigera (Wallengren) in the inland of Australia larval sampling and host plant pelationships during winter and spring. Aust. J. Zool. 1994, 42, 329–346. [Google Scholar] [CrossRef]
  8. Feng, H.Q.; Wu, X.F.; Wu, B.; Wu, K.M. Seasonal Migration of Helicoverpa armigera (Lepidoptera: Noctuidae) over the Bohai Sea. J. Econ. Entomol. 2009, 102, 95–104. [Google Scholar] [CrossRef] [PubMed]
  9. Jones, C.M.; Papanicolaou, A.; Mironidis, G.K.; Vontas, J.; Yang, Y.; Lim, K.S.; Oakeshott, J.G.; Bass, C.; Chapman, J.W. Genomewide transcriptional signatures of migratory flight activity in a globally invasive insect pest. Mol. Ecol. 2015, 24, 4901–4911. [Google Scholar] [CrossRef]
  10. Dalal, P.K.; Arora, R. Fecundity and life-table parameters of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) on tomato crop under alternating temperature regimes: Implications for pest monitoring in sub-tropical India. Int. J. Trop. Insect Sci. 2021, 41, 2851–2865. [Google Scholar] [CrossRef]
  11. Urúa, M.G.; Ogliata, S.V.; Errero, M.I.; Era, M.; Asmuz, A.S.; Omez, D. Biological and reproductive parameters of Helicoverpa armigera and Helicoverpa zea reared on artificial diet in Argentina. Bull. Insectology 2021, 74, 55–64. [Google Scholar]
  12. Specht, A.; Sosa-Gómez, D.R.; Rios, D.A.M.; Claudino, V.C.M.; Paula-Moraes, S.V.; Malaquias, J.V.; Silva, F.A.M.; Roque-Specht, V.F. Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) in Brazil: The big outbreak monitored by light traps. Neotrop. Entomol. 2021, 50, 53–67. [Google Scholar] [CrossRef] [PubMed]
  13. Haile, F.; Nowatzki, T.; Storer, N. Overview of pest status, potential risk, and management considerations of Helicoverpa armigera (Lepidoptera: Noctuidae) for U.S. soybean production. J. Integr. Pest Manag. 2021, 12, 1–10. [Google Scholar] [CrossRef]
  14. Tay, W.T.; Soria, M.F.; Walsh, T.; Thomazoni, D.; Silvie, P.; Behere, G.T.; Anderson, C.; Downes, S. A brave new world for an old world pest: Helicoverpa armigera (Lepidoptera: Noctuidae) in Brazil. PLoS ONE 2013, 8, e80134. [Google Scholar] [CrossRef] [PubMed]
  15. Magor, J. Forecasting migrant insect pests. In Insect Migration: Tracking Resources through Space and Time; Drake, V.A., Gatehouse, A.G., Eds.; Cambridge University Press: Cambridge, UK, 1995; pp. 399–426. [Google Scholar]
  16. Zhang, J.; Ma, J.H.; Xu, Y.C.; Wang, X.; Wang, P.L.; Omar, G.; Lv, Z.Z. Migration behavior of cotton bollworm in Xinjiang of Northwest China based on the ovarian development characteristics of adult females. Chin. J. Ecol. 2013, 32, 1428–1432. [Google Scholar]
  17. Sun, G.J.; Liu, S.H.; Luo, H.L.; Feng, Z.L.; Yang, B.J.; Luo, J.; Tang, J.; Yao, Q.; Xu, J.J. Intelligent monitoring system of migratory pests based on searchlight trap and machine vision. Front. Plant Sci. 2022, 13, 897739. [Google Scholar] [CrossRef] [PubMed]
  18. Keszthelyi, S.; Nowinszky, L.; Szeőke, K. Different catching series from light and pheromone trapping of Helicoverpa armigera (Lepidoptera: Noctuidae). Biologia 2016, 71, 818–823. [Google Scholar] [CrossRef]
  19. Thein, P.P.; Choi, S.W. Forest insect assemblages attracted to light trap on two high mountains (Mt. Jirisan and Mt. Hallasan) in South Korea. J. For. Res. 2016, 27, 1203–1210. [Google Scholar] [CrossRef]
  20. Cohnstaedt, L.W.; Gillen, J.I.; Munstermann, L.E. Light-emitting diode technology improves insect trapping. J. Am. Mosq. Control Assoc. 2008, 24, 331–334. [Google Scholar] [CrossRef]
  21. Yao, Q.; Feng, J.; Tang, J.; Xu, W.; Zhu, X.; Baojun, Y.; Lü, J.; Xie, Y.; Yao, B.; Wu, S.; et al. Development of an automatic monitoring system for rice light-trap pests based on machine vision. J. Integr. Agric. 2020, 19, 2500–2513. [Google Scholar] [CrossRef]
  22. He, W.; Wang, L.Y.; Lv, C.Y.; Ge, S.S.; Zhang, H.W.; Jiang, S.; Chu, B.; Yang, X.M.; Wyckhuys, K.A.G.; Wu, K.M. Use of food attractants to monitor and forecast Spodoptera frugiperda (J. E. Smith) Seasonal Abundance in Southern China. J. Pest Sci. 2023, 96, 1509–1521. [Google Scholar] [CrossRef]
  23. Gregg, P.C.; Del Socorro, A.P.; Henderson, G.S. Development of a synthetic plant volatile-based attracticide for female Noctuid moths. II. Bioassays of synthetic plant volatiles as attractants for the adults of the cotton bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae). Aust. J. Entomol. 2010, 49, 21–30. [Google Scholar] [CrossRef]
  24. Del Socorro, A.P.; Gregg, P.C.; Alter, D.; Moore, C.J. Development of a synthetic plant volatile-based attracticide for female Noctuid moths. I. Potential sources of volatiles attractive to Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae). Aust. J. Entomol. 2010, 49, 10–20. [Google Scholar] [CrossRef]
  25. Gregg, P.C.; Del Socorro, A.P.; Hawes, A.J.; Binns, M.R. Developing bisexual attract-and-kill for polyphagous insects: Ecological rationale versus pragmatics. J. Chem. Ecol. 2016, 42, 666–675. [Google Scholar] [CrossRef] [PubMed]
  26. Gregg, P.C.; Del Socorro, A.P.; Landolt, P.J. Advances in attract-and-kill for agricultural pests: Beyond pheromones. Annu. Rev. Entomol. 2018, 63, 453–470. [Google Scholar] [CrossRef]
  27. Justiniano, W.; Fernandes, M.G. Effect of food attractants and insecticide toxicity for the control of Spodoptera frugiperda (Lepidoptera: Noctuidae) adults. J. Agr. Sci. 2019, 12, 129. [Google Scholar] [CrossRef]
  28. He, W.; Zhao, X.C.; Ali, A.A.; Ge, S.S.; Zhang, H.W.; He, L.M.; Wu, K.M. Population dynamics and reproductive developmental analysis of Helicoverpa armigera (Lepidoptera: Noctuidae) trapped using food attractants in the Field. J. Econ. Entomol. 2021, 114, 1533–1541. [Google Scholar] [CrossRef] [PubMed]
  29. Wu, Q.L.; Jiang, Y.Y.; Liu, J.; Hu, G.; Wu, K.M. Trajectory modeling revealed a southwest-northeast migration corridor for fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae) emerging from the North China Plain. Insect Sci. 2021, 28, 649–661. [Google Scholar] [CrossRef]
  30. Queiroz-Santos, L.; Casagrande, M.M.; Specht, A. Morphological characterization of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae: Heliothinae). Neotrop. Entomol. 2018, 47, 517–542. [Google Scholar] [CrossRef]
  31. Zhou, S.H.; Li, J.; Yao, R.X.; Zhang, X.; Yuan, Z.M. Optimization of chemically defined diet for larvae of the cotton bollworm (Helicoverpa armigera) based on uniform design and support vector regression. Acta Entomol. Sin. 2012, 55, 124–132. [Google Scholar]
  32. Kong, D.S.; Sun, H.M.; Zhao, Y.L.; Xu, L.; Hui, X.H.; Qu, M.J.; Lu, X.T. Control effect and benefit analysis of sex attractant and biological food attractant on Helicoverpa armigera in peanut field. Shandong Agric. Sci. 2016, 48, 102–105. [Google Scholar]
  33. Stein, A.F.; Draxler, R.R.; Rolph, G.D.; Stunder, B.J.B.; Cohen, M.D.; Ngan, F. NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull. Am. Meteorol. Soc. 2015, 96, 2059–2077. [Google Scholar] [CrossRef]
  34. Gao, Y.B.; Zhai, B.P. Active temperature selection of flying Helicoverpa armigera ( Lepidoptera: Noctuidae) moths. Acta Entomol. Sin. 2010, 53, 540–548. [Google Scholar]
  35. Chen, H.X.; Yang, R.; Yang, W.; Zhang, L.; Camara, I.; Dong, X.H.; Liu, Y.; Shi, W.P. Efficacy of Bt maize producing the Cry1Ac protein against two important pests of corn in China. Environ. Sci. Pollut. Res. Int. 2016, 23, 21511–21516. [Google Scholar] [CrossRef]
  36. Pedigo, L.P. Entomology and Pest Management; Waveland Press: Long Grove, IL, USA, 1989. [Google Scholar]
  37. Feng, B.; Guo, Q.S.; Zhu, F.; Wang, X.; Liu, W.C.; Jiang, Y.Y.; Zhong, L.; Du, Y.J. Ovarian development and synthetic sex pheromone lure trapping of adults of the rice leaf folder, Cnaphalocrocis medinalis (Lepidoptera: Pyralidae). Acta Entomol. Sin. 2017, 60, 211–221. [Google Scholar]
  38. Tigreros, N.; Davidowitz, G. Flight-fecundity tradeoffs in wing-monomorphic insects. Adv. Insect Physiol. 2019, 56, 1–41. [Google Scholar]
  39. Qi, G.J.; Lu, F.; Hu, G.; Wang, F.Y.; Gao, Y.; Lv, L.H. The application of ovarian dissection in the research on migratory insects in China. China Plant Prot. 2011, 31, 18–22. [Google Scholar]
  40. Zhang, X.X.; Lu, Z.Q.; Geng, J.G. Application of anatomy of female moth of Cnaphalocrocis medinalis (Lepidoptera: Pyralidae) in prediction. Insect Knowl. 1979, 3, 97–99. [Google Scholar]
  41. Cai, X.M.; Bian, L.; Xu, X.X.; Luo, Z.X.; Li, Z.Q.; Chen, Z.M. Field background odour should be taken into account when formulating a pest attractant based on plant volatiles. Sci. Rep. 2017, 7, 41818. [Google Scholar] [CrossRef]
  42. Wang, L.Y.; He, L.M.; Zhu, X.M.; Zhang, J.W.; Li, N.; Fan, J.F.; Li, H.F.; Sun, X.J.; Zhang, L.J.; Lin, Y.L.; et al. Large-area field application confirms the effectiveness of toxicant-infused bait for managing Helicoverpa armigera (Hübner) in maize fields. Pest Manag. Sci. 2023, 79, 5405–5417. [Google Scholar] [CrossRef]
  43. Ge, S.S.; Zhang, H.W.; Liu, D.Z.; Lv, C.Y.; Cang, X.Z.; Sun, X.X.; Song, Y.F.; He, W.; Chu, B.; Zhao, S.Y.; et al. Seasonal migratory activity of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) across China and Myanmar. Pest Manag. Sci. 2022, 78, 4975–4982. [Google Scholar] [CrossRef] [PubMed]
  44. Zhu, J.S.; Zhai, B.P.; Dong, B.X. Forecasting model for the oviposition peak day in the second generation of Helicoverpa armigera (Lepidoptera: Noctuidae) based on radial basis wavelet network. Acta Entomol. Sin. 2010, 53, 1429–1435. [Google Scholar]
  45. Li, Z.; Tang, B.S. Principal component analysis forecast model of Helicoverpa armigera based on precipitation index. Acta Agric. Boreali-Occident. Sin. 2017, 26, 1554–1558. [Google Scholar]
  46. Blum, M.; Nestel, D.; Cohen, Y.; Goldshtein, E.; Helman, D.; Lensky, I.M. Predicting Heliothis (Helicoverpa armigera) pest population dynamics with an age-structured insect population model driven by satellite data. Ecol. Model. 2018, 369, 1–12. [Google Scholar] [CrossRef]
  47. Feng, H.Q.; Gould, F.; Huang, Y.X.; Jiang, Y.Y.; Wu, K.M. Modeling the population dynamics of cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) over a wide area in northern China. Ecol. Model. 2010, 221, 1819–1830. [Google Scholar] [CrossRef]
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Figure 1. Reproductive organ development and fecundity of the local and immigrant H. armigera populations. Ovarian development level (A), egg load (B), testis major axis length (C), and daily average fecundity in the local (D) and immigrant (E) populations. Different lowercase letters above the figures indicate significant differences in reproductive organ development at different ages. “ns” above the figures indicate non-significant variations in reproductive organ development between different populations (two-way ANOVA, Tukey’s HSD, p < 0.05).
Figure 1. Reproductive organ development and fecundity of the local and immigrant H. armigera populations. Ovarian development level (A), egg load (B), testis major axis length (C), and daily average fecundity in the local (D) and immigrant (E) populations. Different lowercase letters above the figures indicate significant differences in reproductive organ development at different ages. “ns” above the figures indicate non-significant variations in reproductive organ development between different populations (two-way ANOVA, Tukey’s HSD, p < 0.05).
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Figure 2. Age dynamics and structure of H. armigera trapped using the semiochemical attractants and sex pheromones. The age dynamics of adults trapped using the semiochemical attractants in 2021 (A) and 2023 (B); The age dynamics of males trapped using the sex pheromones in 2022 (C) and 2023 (D); The age structure of males trapped using the semiochemical attractants and sex pheromones in 2023 (E).
Figure 2. Age dynamics and structure of H. armigera trapped using the semiochemical attractants and sex pheromones. The age dynamics of adults trapped using the semiochemical attractants in 2021 (A) and 2023 (B); The age dynamics of males trapped using the sex pheromones in 2022 (C) and 2023 (D); The age structure of males trapped using the semiochemical attractants and sex pheromones in 2023 (E).
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Figure 3. Daily percentage of the H. armigera trapped using the semiochemical attractants and sex pheromones in 2021 (A), 2022 (B), and 2023 (C). “Daily percentage of trapped adults” means the daily proportion of adults caught to the total catch number of adults in the same type of traps during the whole monitoring period. Color codes indicate different trap types and adult sex.
Figure 3. Daily percentage of the H. armigera trapped using the semiochemical attractants and sex pheromones in 2021 (A), 2022 (B), and 2023 (C). “Daily percentage of trapped adults” means the daily proportion of adults caught to the total catch number of adults in the same type of traps during the whole monitoring period. Color codes indicate different trap types and adult sex.
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Figure 4. Backward migration trajectory and Kernel density analysis of H. armigera between 2021 and 2023. Backward migration trajectory analysis of H. armigera in 2021 (A), 2022 (B), and 2023 (C); Kernel density analysis of H. armigera migration trajectory in 2021 (D), 2022 (E), and 2023 (F).
Figure 4. Backward migration trajectory and Kernel density analysis of H. armigera between 2021 and 2023. Backward migration trajectory analysis of H. armigera in 2021 (A), 2022 (B), and 2023 (C); Kernel density analysis of H. armigera migration trajectory in 2021 (D), 2022 (E), and 2023 (F).
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Figure 5. Fecundity prediction and verification of field H. armigera population. Prediction of fecundity dynamics of field H. armigera population in 2021 (A) and 2023 (B); The number dynamics of H. armigera larvae on 100 crops in the field in 2023 (C).
Figure 5. Fecundity prediction and verification of field H. armigera population. Prediction of fecundity dynamics of field H. armigera population in 2021 (A) and 2023 (B); The number dynamics of H. armigera larvae on 100 crops in the field in 2023 (C).
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Table 1. Two-way analysis of variance of reproductive development state of H. armigera at different ages in the local and immigrant populations.
Table 1. Two-way analysis of variance of reproductive development state of H. armigera at different ages in the local and immigrant populations.
Target VariableSourceType III SSdfMSFp
Ovarian
development level		Population0.11110.1110.8920.346
Age258.0691123.461188.448<0.001
Population × Age0.846110.0770.6180.812
Error21.6622160.124
Total310123934,613.090
Egg loadPopulation34,613.09018,858,698.1150.9750.325
Age97,445,679.2621134,555.153249.452<0.001
Population × Age380,106.6881135,512.6640.9730.473
Error6,179,203.543216
Total254,492,221.000239
Testis major axis lengthPopulation42,970,736.200165,792.3252.8120.094
Age42,970,736.200113,906,430.564166.935<0.001
Population × Age159,955.2951114,541.3900.6210.811
Error10,483,613.69745723,400.923
Total1,885,921,063.503480
SS = sum of squares; MS = mean squares.
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MDPI and ACS Style

He, W.; Lv, C.; Zhang, H.; Cang, X.; Chu, B.; Yang, X.; Liang, G.; Wu, K. Monitoring and Occurrence Prediction of the Migration Population of Helicoverpa armigera (Hübner) Based on Adult Semiochemical Attractants. Agronomy 2024, 14, 1497. https://doi.org/10.3390/agronomy14071497

AMA Style

He W, Lv C, Zhang H, Cang X, Chu B, Yang X, Liang G, Wu K. Monitoring and Occurrence Prediction of the Migration Population of Helicoverpa armigera (Hübner) Based on Adult Semiochemical Attractants. Agronomy. 2024; 14(7):1497. https://doi.org/10.3390/agronomy14071497

Chicago/Turabian Style

He, Wei, Chunyang Lv, Haowen Zhang, Xinzhu Cang, Bo Chu, Xianming Yang, Gemei Liang, and Kongming Wu. 2024. "Monitoring and Occurrence Prediction of the Migration Population of Helicoverpa armigera (Hübner) Based on Adult Semiochemical Attractants" Agronomy 14, no. 7: 1497. https://doi.org/10.3390/agronomy14071497

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