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Article

Exploring the Possible Role of Semiochemicals in Quince (Cydonia oblonga Mill.): Implications for the Biological Behavior of Cydia pomonella

by
María Pía Gomez
1,2,†,
Flavia Jofré Barud
1,2,†,
Sayra Jaled
1,2,
Silvina Garrido
3,
Liliana Cichón
3 and
María Liza López
1,2,*
1
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1425FQB, Argentina
2
Estación Experimental Agropecuaria, INTA San Juan, San Juan J5429XAB, Argentina
3
Sanidad Vegetal, INTA Alto Valle, Allen 8328, Argentina
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2026, 16(3), 331; https://doi.org/10.3390/agronomy16030331
Submission received: 19 December 2025 / Revised: 21 January 2026 / Accepted: 24 January 2026 / Published: 28 January 2026
(This article belongs to the Special Issue Advancing Sustainable Agriculture: Biopesticides and the Biological Control for Pest Management)
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Abstract

The codling moth (Cydia pomonella L.) is a major pest of pome fruits worldwide, guided by semiochemicals to locate hosts and oviposition sites. Quince (Cydonia oblonga Mill.), although less studied, is also affected by this pest. This study aimed to identify behaviorally active compounds for codling moth by characterizing the volatilome of quince cultivars. Volatile profiles were analyzed across four phenological stages (flowering, unripe, growth, and ripe fruit) using solid-phase microextraction and GC–MS. The cultivars evaluated were Champion, INTA 37, INTA 117, and INTA 147. Female oviposition behavior and neonate larval host choice were also assessed. Identified volatiles included esters, sesquiterpenes, monoterpenes, alcohols, aldehydes, and norisoprenoids. Among monoterpenes, limonene, consistently detected across all cultivars and stages, emerged as a key kairomone. Volatile composition varied across phenological stages, with the fruit growth stage exhibiting the highest diversity and abundance of compounds previously reported as behaviorally active. This pattern coincided with peak female oviposition and larval host selection. Females oviposited mainly on leaf surface, whereas during ripening, eggs were deposited on fruit lacking pubescence. Overall, INTA 147 was the most preferred cultivar. These findings highlight quince volatiles, particularly Limonene, as potential candidates for the development of semiochemical-based tools to improve codling moth management.

Graphical Abstract

1. Introduction

The codling moth (Cydia pomonella L.) is an oligophagous pest whose main hosts include apple, pear, quince, and walnut [1,2]. This pest causes severe damage to fruit crops and reduces production quality in most regions where these hosts are cultivated [3,4]. After mating, female codling moths locate host plants and recognize a suitable oviposition site. This process involves the integration of multiple sensory cues, including visual, tactile, and volatile semiochemical signals [5,6,7,8]. Accurate host location is critical for the survival and development of neonate larvae and, consequently, for the continuation of the species’ life cycle [7,9,10]. Codling moth exhibits clear host preferences, with apple being more preferred than pear, quince, and walnut [8,11,12].
Host-emitted volatiles play a central role in stimulating female pheromone production, calling and mating behavior with males, and subsequent oviposition [13,14,15]. During early phenological stages, most eggs are laid on leaves near the fruit, while later in the season, oviposition occurs directly on the fruits [6,7,8,16]. Females preferentially oviposit on smooth surfaces, avoiding pubescent ones [5,7,8,16,17]. Neonate larvae survive only briefly without feeding and must therefore rapidly locate and penetrate the fruit [7,18,19,20]. During fruit localization, larvae display searching behaviors guided by the perception of plant-emitted kairomones [19,21,22]. Once larva enter the fruit, control through insecticides or natural enemies becomes ineffective [23].
Studies on host localization have emphasized the relevance of kairomones, particularly for monitoring purposes using traps or in combination with insecticides [23,24,25]. The main codling moth kairomones are (E,E)-α-farnesene and the pear ester, both of which attract adults and larvae [23,24,26]. Exposure to specific doses of pear ester [20,27], as well as to (E,E)-α-farnesene and apple extracts [19], induces arrestment behavior in neonate larvae and prolongs wandering prior to fruit entry. At high concentrations, (E,E)-α-farnesene acts as a repellent for mated females [28]. Female codling moths are attracted to volatile cues emitted by host plants. In wind tunnel assays [29] and olfactometer tests [13], mated females were attracted to apple fruits and apple volatiles. Several studies have examined these volatile compounds and their interactions between codling moth and its primary hosts, apple and pear. More than three hundred compounds have been identified in apple [30], even across different phenological stages [31].
In quince (Cydonia oblonga Mill.), the major volatile compound is (E,E)-α-farnesene [32,33,34,35,36], whereas pear ester occurs in smaller proportions [36]. Olfactometer assays have demonstrated that mated females are attracted to quince volatiles; however, neonate larvae have not shown significant discrimination among quince cultivars in dual-choice tests [37].
Changes in pesticide use for codling moth control have been reported due to restrictions on insecticide applications and the development of resistance [38,39,40]. Pest dynamics are also influenced by climate change [25,40], which similarly affects crop systems [41,42,43]. Therefore, it is essential to develop new, more effective pest control methods and, above all, more environmentally sustainable [44,45,46].
The application of semiochemicals capable of inducing female repellence or attraction, or prolonging the exposure time of neonate larvae, represents a promising strategy for field pest management. In this context, identifying recognized antennally active volatiles or kairomones in quince volatilome may contribute to the development of novel management tools with potential applicability to other hosts species.

2. Materials and Methods

2.1. Plant Material

The quince cultivars selected for this study were Champion, INTA 37, INTA 117, and INTA 147, all belonging to the INTA San Juan Experimental Station, Argentina (31°35′33.96″ S, 68°35′31.53″ W; 622 m elevation). All cultivars were subjected to identical agricultural practices. To prevent the codling moth infestation, branches were enclosed in cylindrical bags made of white voile fabric (0.80 m × 0.35 m Ø). The fabric mesh effectively prevents the entry and exit of neonate larvae and adult codling moths, as well as other species, while allowing light penetration and air circulation. Photosynthetically active radiation (PAR) transmittance of the bags was 0.78 ± 0.03. Bagging was performed once 50% of the flowers reached anthesis, ensuring successful pollination, fertilization, and fruit set. Branches were selected from the mid-to-upper canopy of each plant, considering the flight behavior of codling moths. Only branches exhibiting uniform vegetative development were selected. Four branches per plant were bagged (two on the eastern side and two on the western side of the row), resulting in a total of 32 bagged branches per cultivar maintained throughout the production cycle. At the time of bagging, flower density was high; however, following natural fruit drop during the immature stage, the number of fruits per branch was reduced to five or six. A leaf-to-fruit ratio of four to five leaves per fruit was observed.
Phenological stages were defined following the criteria established by Martínez-Valero et al. [47] as follows: flowering: 80–90% of flowers open; fruit setting: 10–60 days after flowering (DAF); fruit growth: approximately 150 DAF; and fruit ripening: fruit color transition from yellowish-green to golden yellow, occurring between 200 and 220 DAF.

2.2. HS-SPME Collection

Leaves were sampled at all phenological stages, whereas the presence of flowers and fruits varied according to developmental stage. All samples were collected in the field 1 h before sunset, between 6:00 and 7:00 p.m., in accordance with the biological and reproductive behavior of codling moth [3,7]. The extraction procedures were carried out immediately after sampling. At the flowering stage, a total of 20 flowers per cultivar were collected, from which a subsample of four flowers was selected. In addition, 20 leaves were collected, and six whole leaves were selected, unwashed and uncut. At the fruit setting stage, eight fruits per cultivar were collected; from these, a random subsample of four fruits was selected, and a 1 cm3 portion, including the skin, was excised from each unwashed fruit. The four portions were weighed and placed in a vial. Also, 20 leaves were collected, and six whole leaves were selected, unwashed and uncut. At the fruit-growth and fruit-ripening stage, fruits and leaves samples were processed following the same procedures used at the fruit-setting stage.
All plant material was weighed to ensure a homogeneous selection and comparables quantities among cultivars. A 40 mL amber glass vial, (Supelco®, Bellefonte, PA, USA) was filled to one-third of its volume and immediately closed with a screw cap fitted with a Teflon-coated silicone septum (Supelco®, Bellefonte, PA, USA). Samples were processed individually. Each vial was placed in a thermostated water bath at 30 °C for 30 min (equilibrium time).
Volatile extraction was performed by solid-phase microextraction (SPME) using a DVB/CAR/PDMS fiber (divinylbenzene/carboxen/polydimethylsiloxane, 2 cm long and 50/30 μm phase thickness, Supelco®, Bellefonte, PA, USA). The fiber was exposed to the vial headspace and maintained at 30 °C for 15 min (extraction time). During this period, volatiles were adsorbed onto the fiber. Following extraction, the fiber was immediately inserted into the injection port of a gas chromatograph coupled to a mass spectrometer and desorbed for 5 min [32,36].

2.3. Gas Chromatography and Mass Spectrometry (GC-MS) Proceedings

Volatile compounds were analyzed using a PerkinElmer® Clarus® 580 gas chromatograph (GC, PerkinElmer, Shelton, CT, USA) equipped with a DB-5 MS capillary column (30 m × 0.25 mm i.d.; Agilent, Santa Clara, CA, USA), operated in splitless injection mode and coupled to a PerkinElmer® Clarus® SQ 8 mass spectrometer (MS, PerkinElmer, Shelton, CT, USA). The oven temperature program was as follows: initial temperature of 50 °C (held for 5 min), increased at 1 °C min−1 to 70 °C (held for 4 min), and then increased at 6 °C min−1 to a final temperature of 200 °C. Helium was used as the carrier gas at a pressure of 49.6 psi. Injector and flame ionization detector (FID) were maintained at 250 °C, and the GC transfer line was held at 200 °C. Ionization was performed by electron impact (EI) at 70 eV under high-vacuum conditions. Chromatograms were obtained in quadruple scan modes from 50 m/z to 300 m/z (scan time: 0.2 s, inter-scan time: 0.1 s) [36].

2.4. Qualitative and Quantitative Volatile Identification

Volatile compounds were identified by comparing experimental Kovats retention indices, calculated relative to a C6–C18 n-alkane series, with published literature values, and by matching mass spectra against the NIST [48] and Adams [49] libraries using AMDIS software (version 2012). Compound abundance was expressed as relative peak area percentages within each chromatogram. Among the detected volatiles, compounds previously reported in the literature as electroantennography-active (EAG+) or behaviorally active (kairomones/K) for female codling moths were identified.
Principal component analysis (PCA) was performed to explore the relationships among volatile chemical groups and quince cultivars during the phenological stages. Each chemical group corresponded to the mean relative abundance (%) of volatile compounds from leaves and flowers or leaves and fruits of each cultivar. Similarity among cultivars was assessed using the Euclidean distance. All multivariate analyses were conducted using InfoStat software (version 2020p).

2.5. Insects

Codling moth eggs deposited on wax paper were obtained from laboratory colony maintained at the Plant Health Laboratory, INTA Alto Valle, Río Negro, Argentina. Larvae were reared on an artificial diet based on the formulation proposed by Poitout et al. [50], with modifications. The colony was maintained at 25 °C under natural light conditions. Adults were paired in oviposition chambers lined with wax paper and supplied with a sugary-water solution [51]. Wax paper sheets were replaced every two days and incubated at 27 °C until eggs hatched.

2.6. Female Oviposition Through Quince Phenology

Oviposition preference was evaluated using pairwise combinations of cultivars. One branch per cultivar, including fruit and leaves, was selected and placed in a vial containing water to prevent dehydration during the assay. A 14 L plastic container covered with white voile fabric served as the experimental arena, into which four pairs of adult codling moths were released, along with a water source (Figure 1). After four days, eggs were counted and oviposition sites were recorded as follows: leaves (upper and lower surfaces), flowers, fruits, and/or branches. Each cultivar combination was replicated six times. Experiments were conducted at room temperature (24–25 °C), 70% relative humidity, and under natural light conditions. Assays were performed during the fruit setting, fruit growth, and fruit ripening stages, following codling moth generations. No oviposition assays were conducted during flowering, as no adult codling moths were captured in the experimental field at that state.
Oviposition preference was analyzed using the Chi-square goodness-of-fit test (p < 0.05). Oviposition patterns across phenological stages and cultivars were analyzed using a generalized Poisson model. All analysis was performed using InfoStat software (version 2020p).

2.7. Neonate Larvae Choice Through Quince Phenology

Dual-choice assays for larval behavior were conducted following the methodology of Andreadis et al. [52] and Gomez et al. [37], with modifications. Filter paper arenas were divided into areas as illustrated in Figure 2. Unfed neonate first-instar larvae were used immediately after hatching or within 1 h. A total of 80 larvae were tested, one per cultivar pair. Each larva was placed at the center of the arena and allowed 600 s to make a choice. After every five larvae, the filter paper and plant material were replaced. Recorded variables included time to choice, final cultivar selected, and behavioral responses such as arrest near a cultivar and wandering. Assays were conducted at room temperature (24–25 °C), 70% relative humidity, and under artificial light conditions. Experiments were performed during the fruit-setting, fruit-growth, and fruit-ripening stages.
Preference and behavioral responses were analyzed using a Chi-square Goodness-of-Fit test (p < 0.05). Choice time was analyzed using the Wilcoxon (Mann–Whitney U) test (p < 0.05). Larval choice frequency across phenological stages was analyzed using a generalized Poisson model. All statistical analyses were performed with InfoStat software (version 2020p).

3. Results

3.1. Volatilome Profiling of Quince Cultivars

3.1.1. Volatilome Profile at the Flowering Stage

A total of thirty-eight volatile compounds were identified from flowers and leaves samples. Across all cultivars, flowers exhibited a slightly higher number of compounds than leaves. Champion showed the greatest chemical diversity, whereas INTA 147 exhibited the lowest. The mean total identified area across cultivars was 93.53%. The complete volatile profile identification at flowering stage is presented in Table S1.
The PCA conducted explained 93.10% of the total variability among the samples (Figure 3). In the first principal component (PC1: 64.8%), sesquiterpenes and alcohols were dominant in the cultivars Champion and INTA 117. The second component (PC2: 28.3%) was characterized by the predominance of hydrocarbons and esters in INTA 147, while monoterpenes and aldehydes were more representative in INTA 37. Based on the chemical group profiles, Champion and INTA 117 displayed greater similarity, whereas INTA 37 and INTA 117 were the most dissimilar cultivars.
Of the entire volatiloma at flowering stage, twelve compounds with antennal activity were recorded (Table 1). Among them, limonene, β-caryophyllene, and (E,E)-α-farnesene are considered kairomones according to the literature. Leaves of the Champion cultivar had a greater diversity of EAG+/Kairomonal compounds than those of INTA 147. (E,E)-α-farnesene was the most abundant and widely distributed compound across cultivars, with the highest levels detected in flowers. β-caryophyllene was detected at lower proportions and was mainly detected in the leaves. The highest abundance was recorded in Champion leaves and INTA 117 flowers. Limonene was detected at lower amounts, with higher abundance in INTA 37 flowers and was not detected in INTA 147.
The most abundant biologically active volatile, excluding known kairomones, was (Z)-3-hexenyl acetate. This compound was highly represented in leaf tissues of all cultivars, particularly in INTA 147 and INTA 37. (Z)-3-Hexenol was detected at lower levels in all cultivars, with the highest values in leaves. (E)-β-ocimene was most abundant in the floral tissues of all INTA cultivars, reaching its highest levels in INTA 37 flowers. Champion was the only cultivar in which germacrene D and (3Z)-hexenyl benzoate were both detected exclusively in leaves. In addition, decanal was detected only in leaves of INTA 37.

3.1.2. Volatilome Profile at the Fruit Setting Stage

A total of twenty-five volatile compounds were identified in fruit and leaf samples of all cultivars collected during the fruit setting stage. Overall, fruits exhibited a greater diversity of volatiles than leaves. INTA 37 showed the greatest diversity of compounds, whereas INTA 147 showed the lowest. The mean total identified area across cultivars was 98.99%. The complete volatile profile identification at fruit setting stage is presented in Table S2.
PCA explained 80% of the total variability among volatile chemical groups and cultivars (Figure 4). In the first principal component (PC1: 48.5%), esters and sesquiterpenes were predominant in the cultivars INTA 117 and INTA 147. The second component (31.4%) highlighted the predominance of alcohols and hydrocarbons in INTA 37, while monoterpenes were most representative in Champion. Based on the chemical group profiles, INTA 117 and INTA 147 exhibited greater similarity, whereas Champion and INTA 117 were the most dissimilar in terms of volatile composition.
In the fruit-setting stage volatilome, nine compounds with antennal activity were detected (Table 2). Limonene was the only compound with kairomonal activity detected in all cultivars. It was detected in higher levels in fruits than in leaves, with the highest proportion in INTA 147 fruits.
The most abundant antennally active compound was (Z)-3-hexenyl acetate. This compound was detected across all cultivars and tissues. It was consistently dominant in leaves, reaching its highest proportion in INTA 147. In fruits, its abundance ranged from high levels in INTA 147 to lower levels in Champion. (Z)-3-hexenol was detected in both tissues, with consistently higher levels in fruits across all cultivars. (E)-β-ocimene was detected exclusively in fruit tissues of all cultivars and reached its highest levels in Champion. Benzaldehyde was present only in fruits of all cultivars. In addition, β-myrcene was uniquely detected in INTA 117 fruits. (Z,E)-α-farnesene was present in high proportions in INTA 147 fruits.

3.1.3. Volatilome Profile at the Fruit Growth Stage

A total of seventy-six volatile compounds were identified in fruit and leaf samples collected during the fruit growth stage. Leaves of INTA cultivars exhibited a greater diversity of volatiles than fruits. INTA 117 showed the greatest chemical diversity, whereas Champion showed the lowest. The mean total identified area across cultivars was 95.40%. The complete identification in growth stage is presented in Table S3.
PCA accounted for 85.90% of the total variability among chemical groups and cultivars (Figure 5). In the first principal component (PC1: 66.8%), aldehydes, ketones, monoterpenes and aromatics were predominant in cultivars INTA 37 and INTA 117, whereas esters were more abundant in Champion. The second component (PC2: 19.1%) was defined by alcohols in INTA 147 and hydrocarbons in Champion. Based on the chemical group profiles, INTA 37 and INTA 117 were the most similar, whereas Champion and INTA 117 were the most dissimilar cultivars.
In the fruit growth stage volatilome, fifteen compounds with antennal activity were detected (Table 3). Limonene was the most abundant and widespread kairomone, occurring predominantly in leaf tissues, with the highest levels in INTA 147. (E,E)-α-farnesene was detected in all cultivars, with higher proportions in fruits than in leaves. The highest proportion was detected in INTA 117 fruits.
(Z)-3-hexenyl acetate was detected in all cultivars, with notably higher abundance in Champion leaf. (Z)-3-hexenol was detected in both tissues and reached its highest levels in fruits. (E)-β-ocimene was detected in all tissues and cultivars and was more abundant in INTA 37 fruits. Hexyl acetate was detected only in fruit tissues and was most abundant in Champion. Methyl salicylate was detected exclusively in Champion.

3.1.4. Volatilome Profile at the Fruit Ripening Stage

A total of fifty-two volatile compounds were identified in fruit and leaf samples collected during the ripening stage. Leaves exhibited a slightly higher number of compounds than fruits across cultivars. The mean total identified area was 96%. The complete identification in the ripening stage is presented in Table S4.
PCA explained 85.40% of the total variability among volatile chemical groups and cultivars (Figure 6). In the first principal component (PC1: 57.6%), esters and norisoprenoids were predominant in cultivars INTA 117 and INTA 147, whereas monoterpenes were dominant in INTA 37. PC2 (27.8%) was defined by thiols and sesquiterpenes in Champion and aldehydes in INTA 37. INTA 117 and INTA 147 showed the highest similarity in volatile profiles, while INTA 37 and INTA 147 were the most dissimilar.
In the fruit ripening stage volatilome, ten compounds with antennal activity were detected (Table 4). Among the kairomonal volatiles, limonene showed relatively high abundance in leaves tissues of all cultivars. (E,E)-α-farnesene was abundant in fruits of all cultivars, with higher levels in Champion and INTA 37 and lower levels in INTA 147.
(Z)-3-hexenol was detected exclusively in leaves with high levels. Minor volatiles such as β-myrcene, 6-methyl-5-hepten-2-one and benzaldehyde were detected only in leaf tissues. Hexyl acetate was detected exclusively in fruits. (E)-β-ocimene was detected in both tissues, with slightly higher proportions in fruits. Germacrene D was detected exclusively in INTA 147 fruits.

3.2. Female Oviposition and Neonate Larvae Choice Through Quince Phenology

3.2.1. Female Codling Moth Oviposition

Fruit setting stage. The number of eggs differed significantly among all cultivar combinations (Champion vs. INTA37: G2 = 11.06; p = 0.0009; Champion vs. INTA117: G2 = 7.39; p = 0.0065; Champion vs. INTA147: G2 = 4.21; p = 0.0402; INTA37 vs. INTA117: G2 = 10.62; p = 0.0011; INTA37 vs. INTA147: G2 = 43.07; p < 0.0001; INTA117 vs. INTA147: G2 = 8.93; p = 0.0028) (Figure 7). In all comparisons involving INTA 147, this cultivar was the most preferred, recording the highest number of eggs. When Champion cultivar was included, oviposition occurred mainly on INTA cultivars. The sum of eggs laid on INTA 37 and Champion indicates that these cultivars were the least preferred.
A total of 805 eggs were recorded at this stage. In all cultivars, significantly more eggs were laid on the upper leaf surface than on the lower surface (Table 5). No eggs were recorded on fruit and branches.
Growth stage. Significant differences were observed for most cultivar combinations (Champion vs. INTA37: G2 = 7.89; p = 0.005; Champion vs. INTA147: G2 = 19.63; p < 0.0001; INTA37 vs. INTA117: G2 = 27.73; p < 0.0001; INTA37 vs. INTA147: G2 = 54.2; p < 0.0001; INTA117 vs. INTA147: G2 = 11.22; p = 0.0008), except for Champion vs. INTA 117 (G2 = 0.3; p = 0.5844) (Figure 8). INTA 147 was the most-preferred cultivar when tested against Champion and INTA 37, whereas INTA 117 was preferred over INTA 37 and INTA 147. INTA 37 was the least preferred in all combinations.
A total of 2404 eggs were recorded. Most eggs were laid on the upper leaf surface, whereas only a few were deposited on branches lacking pubescence (Table 6).
Ripening. Oviposition differed significantly among all cultivar combinations (Champion vs. INTA37: G2 = 23.51; p < 0.0001; Champion vs. INTA117: G2 = 8.91; p = 0.0028; Champion vs. INTA147: G2 = 13.06; p = 0.0003; INTA37 vs. INTA117: G2 = 5.82; p = 0.0158; INTA37 vs. INTA147: G2 = 43.86; p < 0.0001; INTA117 vs. INTA147: G2 = 15.23; p = 0.0001) (Figure 9). INTA 147 was the most-preferred cultivar, followed by Champion, whereas INTA 37 was the least preferred.
A total of 615 eggs were recorded. When analyzing oviposition on different parts of the quince, it was observed that the number of eggs laid was significantly higher on the upper leaf surface than on the lower leaf surface (Table 7). Eggs were deposited on fruits only at this stage, specifically in areas where pubescence had been lost, with the highest number recorded on INTA 147 fruits.
Oviposition across phenological stages. Considering all cultivars together, oviposition differed significantly among phenological stages (Figure 10). Egg number increased from fruit setting to fruit growth and declined at ripening stage.
The high pubescence of all cultivars and organs tested is notable. It was observed that pubescence on both sides of the leaves decreased as the quince tree progressed through the phenological stages (Figure S1). Also, Figure S1 shows the pubescence on ripe fruit (G), the upper leaf surface (H), and the lower leaf surface (I).

3.2.2. Neonate Larvae Dual-Choice

Larval choice was recorded when individuals contacted the fruit. Wandering behavior referred to larvae moving throughout the arena without contacting fruit, whereas “arrest near a cultivar” described larvae remaining within a few millimeters of a fruit or near the release point. Head lifting was observed; however, this behavior was not consistently recorded across assays.
Fruit setting stage. Cultivar choice did not differ significantly in most combinations (Figure 11). A significant preference was observed only in the Champion–INTA 147 (G2 = 4.61; p = 0.0317), with more larvae selecting Champion. Mean choice time was 313.53 s, with no significant differences among treatments (Table S5). INTA 147 consistently recorded the shortest choice times, whereas the presence of Champion was associated with longer choice times. No significant differences were found in arrest near a cultivar (Table S6), although in combinations including Champion, more larvae were arrested near INTA cultivars. When all behaviors were considered, significant differences were detected among all combinations (Table 8). Behavior within the cultivar-dominant area ranged from 44% in the Champion–INTA 37 combination to 51% in Champion–INTA 147. In contrast, behavior in the area distant from the cultivar ranged from 49% in Champion–INTA 147 to 56% in INTA 37–INTA 147.
Fruit Growth stage. No significant differences in cultivar choice were detected (Figure 12). Although not statistically significant, the frequencies suggest that INTA 117 and INTA 147 were the most preferred, whereas Champion was consistently the least preferred when tested against INTA cultivars. Larvae required an average of 323.60 s to make a definitive choice, with no significant differences among combinations (Table S7). The shortest choice times were recorded for INTA 37, while INTA 147 exhibited the longest. Arrest near a cultivar behavior did not differ significantly in most comparisons (Table S8), except in the INTA 117–INTA 147 combination, where more larvae were arrested near INTA 147 (G2 = 5.06; p = 0.0245). Significant differences were observed when all behaviors were analyzed together (Table 9). Behavior within the cultivar-dominant area ranged from 59% in the INTA 37–INTA 147 combination to 78% in Champion–INTA 37. In contrast, behavior in the area distant from the cultivar ranged from 23% in Champion–INTA 37 to 41% in INTA 37–INTA 147.
Ripening. At the final phenological stage, no significant differences in cultivar choice were detected (Figure 13). Despite this, Champion tended to be more frequently preferred when tested against INTA 37 and INTA 117. Mean choice time was 367.77 s, with no significant differences among combinations (Table S9). Shorter choice times were associated with INTA 147, while INTA 37 showed the longest. Arrest near a cultivar behavior did not differ significantly (Table S10). However, analysis of all behaviors revealed significant differences (Table 10). Behavior within the cultivar-dominant area ranged from 21% in the INTA 37–INTA 147 combination to 58% in Champion–INTA 37. In contrast, behavior in the area distant from the cultivar ranged from 43% in Champion–INTA 37 to 79% in INTA 37–INTA 147.
Neonate Larvae responses across phenological stages. Larval choice responses differed significantly among phenological stages (Figure 14). The frequency of choice increased after the fruit setting stage, peaked during fruit growth and declined during fruit ripening.

4. Discussion

As phenological development progresses, a natural succession of volatile compounds is generally expected, with aldehydes predominating initially, followed by their reduction to alcohols and the subsequent formation of esters [30,53]. However, this pattern was not observed in the present study. Instead, monoterpene emission increased, whereas sesquiterpene emission decreased throughout quince phenological development. The biosynthesis of these compound classes occurs through distinct yet interconnected metabolic pathways that depend on carbon flux [54,55]. Alcohols and aldehydes increased until the fruit growth stage and then declined during ripening, whereas esters increased from flowering to fruit setting and decreased sharply toward ripening.
Flowering plays a key ecological role in attracting pollinating insects [55,56,57]. Among the compounds identified at this stage, several have been reported as attractants for honeybees, including (Z)-3-hexenol and (E,E)-α-farnesene [58], as well as benzaldehyde and (E)-β-ocimene [58,59]. Bumblebees and carpenter bees are attracted to (E,E)-α-farnesene and limonene [58,60]. No oviposition or larval choice assays were conducted during the flowering stage. To our knowledge, this study provides the first characterization of the volatile profile of Cydonia oblonga flowers.
The availability of compounds with antennal activity and kairomonal function increased from fruit set to fruit growth and then declined toward ripening. Across these stages, (Z)-3-hexenol, benzaldehyde, β-myrcene, hexyl acetate, limonene, and (E)-β-ocimene were consistently detected. Many of these antennally active compounds have also been reported in other host plants of Cydia pomonella. (Z)-3-hexenol emitted by apples elicits consistent antennal responses in females [31,61], in contrast to the weaker responses recorded by Casado et al. [62]. (E)-β-ocimene, present in apples, pears, and walnuts, elicits antennal responses in females [15]. Apple volatiles, such as hexyl acetate induce stronger female responses than β-myrcene, limonene, benzaldehyde, and (Z)-3-hexenol [62].
(Z)-3-hexenyl acetate and nonanal were common to the fruit-setting and growth stages, whereas 6-methyl-5-hepten-2-one, decanal, and (E,E)-α-farnesene were detected during both the growth and ripening stages. Apple volatiles such as (Z)-3-hexenyl acetate elicit stronger antennal responses than (Z)-3-hexenol [62], whereas 6-methyl-5-hepten-2-one produces slightly lower female antennal responses than (E,E)-α-farnesene [62]. In walnut extracts, nonanal elicits strong antennal responses and attraction in olfactometer assays [63]. In addition, decanal and nonanal have been shown to elicit antennal responses that are stronger than those induced by (E,E)-α-farnesene [62]. According to Preti et al. [64], both (Z)-3-hexenyl acetate and (Z)-3-hexenol may act as repellents, as they reduce female trap captures. It should be noted that cutting apples, pears, or quinces can artificially increase the measured levels of (Z)-3-hexenol and (Z)-3-hexenyl acetate, as both compounds are synthesized de novo as an immediate response to mechanical damage [65,66]. In the present study, only fruits were cut to fit the sampling vials, whereas leaves were analyzed intact.
The volatile profile observed at the fruit-growth stage was the most diverse, comprising the highest number of compounds with reported antennal activity and kairomonal function. 2-hexenal, octanal, methyl salicylate, and β-pinene were detected exclusively during the fruit growth stage. Among these compounds, octanal elicits the strongest antennal responses in females, followed by 2-hexenal, methyl salicylate, and β-pinene [62]. Conversely, other studies report hexyl acetate [67], nonanal, benzaldehyde and β-pinene as repellents of mated females [14].
In quince, germacrene D was detected exclusively during the flowering and fruit-growth stages This compound emitted by apples elicits antennal responses in females [31,68], and serves as a biosynthetic precursor of several sesquiterpenes [69].
Oviposition in quince increased from fruit setting to fruit growth and then declined toward ripening. This pattern agrees with previous reports of reduced oviposition during early developmental stages [6,8,9,12,16]. Early stages are characterized by low volatile emissions, which increase later in the phenological cycle and influence female orientation and oviposition site selection [14,31,70]. At the fruit-setting quince stage, (E,E)-α-farnesene, the main kairomone of codling moth, was not detected. However, (Z,E)-α-farnesene was present in quince, and has been reported with antennal activity in female codling moths [31,68,71]. The coincidence of maximum oviposition and maximum volatile emission during the fruit-growth stage has also been documented in apple [6,8,9,12,14,16].
The reduced oviposition observed during the ripening stage may be associated with a lower availability of chemical signaling cues compared with growing quince fruit. In addition to chemical signals, changes in physical and biochemical fruit traits during ripening, such as firmness, size, and secondary metabolite composition, may also modulate oviposition behavior. In apple, less firm and larger fruits are less susceptible to damage [72], and variation in secondary metabolites, including polyphenols and quercetin, influences codling moth infestation and female fecundity [72,73]. Available evidence strongly supports that oviposition in Cydia pomonella is guided by the perception of host-derived volatiles. Females are consistently attracted to fruit odors or to the fruit itself, as demonstrated in olfactometry assays [37,63,67] and flight tunnel experiments [29,68]. Moreover, exposure to host volatiles activates and advances female calling behavior associated with mating [13]. In this work, we propose that oviposition responses were primarily dominated by volatile quince signals.
Overall, females showed a preference for INTA cultivars, with INTA 147 being the most selected and INTA 37 the least preferred. This contrasts with Gómez et al. [37], who report greater oviposition on Champion than on Portugal, Smyrna, and INTA 147 during ripening. Preference for INTA 147 remained consistent from fruit setting to ripening and may be partially attributed to the presence of limonene, which was detected at all phenological stages. This cultivar also exhibited (Z,E)-α-farnesene during fruit setting, a compound known to elicit antennal responses comparable to those of (E,E)-α-farnesene [31]. In addition, (E,E)-α-farnesene acts as a repellent to mated females at high doses [28]. This may explain the observed preference for INTA 147 during ripening, when the relative proportion of (E,E)-α-farnesene was likely attractive rather than repellent. Notably, germacrene D was detected exclusively in this cultivar during ripening.
Cydia pomonella exhibits a stronger preference for apple than for pear, quince, or walnut, with the apple cultivar ‘Golden Delicious’ being the most susceptible [8,11,12]. Differences in oviposition among quince cultivars may therefore be regulated by the relative proportions of compounds within the volatile bouquet, rather than by the presence of a single compound [37,62,74]. It is worth noting that antennal responses detected by electroantennography do not necessarily imply attraction [23,62]. (E,E)-α-farnesene alone does not fully explain attraction in C. pomonella. Moreover, its emission under natural field conditions is short-lived [75], highlighting the need to identify additional volatile compounds [23]. Therefore, identifying compounds suitable for female attraction and mass trapping remains of interest [76].
Contact surface characteristics also influenced oviposition behavior. Quince leaves, branches, and fruits remain pubescent for much of the phenological cycle. Across stages, oviposition occurred predominantly on the upper leaf surface, consistent with observations in apple. During ripening, eggs were deposited on fruit areas where pubescence had been lost. Differences in oviposition behavior are associated with trichome density and surface pubescence [9,12,77], as well as natural surface waxes [8,9,12]. Oviposition on fruits of cultivar INTA 147 was higher than on those of the other cultivars, possibly due to more attractive volatile emissions or lower pubescence density. It remains unknown whether pubescence differs among quince cultivars. This aspect was not evaluated in the present study, and such variation could represent an important factor contributing to the differential oviposition preferences observed among cultivars.
No strong larval preference was detected at any phenological stage, possibly due to competitive volatile emissions among cultivars. This finding is consistent with Gómez et al. [37], who reported no larval preference among quince cultivars, and with Landolt et al. [78], who observed that neonate larvae did not discriminate among apple cultivars. In quince, larval choice frequency increased from fruit setting to fruit growth and declined during ripening. Arrest behavior predominated during fruit setting, whereas wandering behavior was more frequent during ripening. Certain kairomones, depending on their relative proportions, may induce larval arrest and disrupt host localization [19,20,27,37,79]. Several major pear volatiles, including butyl acetate, hexyl acetate, (Z)-3-hexenyl acetate, and (E)-β-ocimene, are not attractive to neonate larvae in olfactometer assays [24]. During fruit setting in quince, hexyl acetate and (E)-β-ocimene were detected exclusively in fruits, whereas (Z)-3-hexenyl acetate occurred at high proportions in both fruits and leaves. These compounds, at the concentrations emitted, may therefore have contributed to the larval arrest observed at this stage.
During the fruit growth stage, the highest female oviposition coincided with the greatest larval cultivar choice. Blomefield and Giliomee [80] report maximum oviposition during summer, when temperatures are more stable than in spring, followed by a decline toward the end of the season. In addition to thermal and photoperiodic influences, C. pomonella responses may reflect synchronization with the volatile bouquet emitted by the host as a feeding cue. Sensitivity to volatile cues varies by developmental stage and sex: males are generally more responsive than females [76], whereas neonate larvae possess distinct odorant receptors [81]. Alternatively, the absence of strong larval preference among cultivars or hosts may represent a survival strategy, supported by the ability of larvae to synthesize carbohydrates independently of the host on which they feed [82]. Neonate larvae are unable to actively choose among potential hosts because they move only over very short distances and survive for a limited period without feeding [7,18]. Consequently, host selection among quince cultivars is largely determined by female codling moth oviposition preferences.
Among the compounds identified, limonene emerged as a consistent component of the quince volatilome and a potential kairomone influencing codling moth behavior. Its presence across all organs and phenological stages. R-(+)-limonene has been proposed as a potential kairomone for field trapping [83] and as an attractant for mated females in olfactometer assays [14]. The findings of Schmera et al. [84] demonstrate that limonene acts, at least, as a potent synergistic kairomone within the pheromonal communication system, suggesting that it could enhance mating disruption or attract-and-kill formulations when combined with codlemone. The specific isomer was not confirmed in our study. The identifications performed were intended solely to explore potential candidate compounds for future field evaluations. For future laboratory and field evaluations, we propose testing mixtures with a fixed dose of commercial codlemone (1 x) combined with decreasing doses of R-(+)-limonene (1, 0.1, and 0.01 mg) to assess adult attraction in field traps and responses of neonate larvae.
Volatile emissions vary with phenological stage, environmental conditions, geographic location, genetic background among species or cultivars, and agronomic management practices, including fertilization and chemical treatments [30,85,86]. Methodological factors, such as extraction techniques and plant part analyzed, may also influence results [87,88]. Biotic stress, such as water deficit, can reduce volatile emissions [35,89,90]. Circadian rhythms further modulate emission patterns, with differences observed between daytime and nighttime in pome fruits and walnut trees [57,62,91,92]. For practical, temporal, and economic reasons, biological assays are often simplified, and certain variables remain unmeasured.
Considering the body of literature on Cydia pomonella, it is noteworthy that females possess a refined ability to detect key signals within complex volatile blends. In this context, examining interactions with a comparatively understudied host such as quince provides valuable insights into host–insect chemical ecology.

5. Conclusions

In this study, limonene was consistently detected in all organs and phenological stages of quince and was associated with patterns of codling moth behavior, suggesting a potential role as a kairomonal cue in this species. However, causal relationships between specific volatiles and behavioral responses remain to be confirmed. Further field evaluation of limonene, alone and in combination with codlemone, would be useful to assess its attractiveness under orchard conditions.
Oviposition preference was higher on leaves, indicating that this organ may warrant greater attention during field monitoring of codling moth in quince orchards. The fruit growth stage was associated with higher oviposition levels and may therefore represent a period of increased crop susceptibility, during which monitoring and control strategies could be reinforced. The higher oviposition observed in cultivar INTA 147 suggests a greater susceptibility to infestation, although this response cannot be attributed to individual compounds and is likely related to the overall volatile bouquet and other plant traits.
The reduced oviposition recorded during the ripening stage may reflect synchronization between female codling moth behavior, crop phenology, and resource availability, rather than direct effects of specific volatiles. Further investigation of volatile compounds or blends detected during early developmental stages that may induce larval arrest would be valuable for exploring potential pest management strategies.
Overall, this study provides the first characterization of volatile compounds in quince across phenological stages and documents their association with female oviposition behavior and neonate larval responses in Cydia pomonella. These findings contribute to a broader understanding of host–location processes in a relatively understudied host and may support the future development of environmentally friendly semiochemical-based tools, pending experimental confirmation of causal mechanisms.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy16030331/s1, Figure S1: (A) Beginning of flowering. (B) Flowering. (C) Fruit set. (D) Immature fruit. (E) Fruit growth. (F) Fruit ripening. Images (A–F) were taken from the EEA San Juan quince cultivar collection. (G) Detail of pubescence on quince fruit. (H) Codling moth eggs on the upper leaf surface. (I) Detail of pubescence on the lower leaf surface. Images (G–I) were obtained using a 40× stereoscopic microscope. Prepared by the authors.; Table S1: Volatile profiles detected in flowers and leaves of four C. oblonga cultivars at the flowering stage, determined by HS-SPME and GC–MS. The abundance of each compound is expressed as a relative proportion of the total.; Table S2: Volatile profiles detected in flowers and leaves of four C. oblonga cultivars at the fruit setting stage, determined by HS-SPME and GC–MS. The abundance of each compound is expressed as a relative proportion of the total.; Table S3: Volatile profiles detected in flowers and leaves of four C. oblonga cultivars at the fruit growth stage, determined by HS-SPME and GC–MS. The abundance of each compound is expressed as a relative proportion of the total.; Table S4: Volatile profiles detected in flowers and leaves of four C. oblonga cultivars at the fruit ripening stage, determined by HS-SPME and GC–MS. The abundance of each compound is expressed as a relative proportion of the total.; Table S5: Mean time (s) taken by C. pomonella neonate larvae to make a choice among combinations of four C. oblonga cultivars at the fruit setting stage.; Table S6: Number of C. pomonella neonate larvae arrested near a cultivar for each combination of C. oblonga cultivars at the fruit setting stage.; Table S7: Mean time (s) taken by C. pomonella neonate larvae to make a choice among combinations of four C. oblonga cultivars at the fruit growth stage.; Table S8: Number of C. pomonella neonate larvae arrested near a cultivar for each combination of C. oblonga cultivars at the fruit growth stage.; Table S9: Mean time (s) taken by C. pomonella neonate larvae to make a choice among combinations of four C. oblonga cultivars at the fruit ripening stage.; Table S10: Number of C. pomonella neonate larvae arrested near a cultivar for each combination of C. oblonga cultivars at the fruit ripening stage.

Author Contributions

M.P.G.: Data curation; formal analysis; investigation; writing—original draft; writing—review and editing. F.J.B.: Data curation; formal analysis; investigation; writing—original draft; writing—review and editing. S.J.: formal analysis; writing—review and editing; S.G. and L.C.: investigation; writing—review and editing. M.L.L.: Conceptualization; funding acquisition; investigation; project administration; resources; supervision; writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

PD 106 Cartera Programática INTA 2023-PD 101—Cartera Programática INTA 2019.

Data Availability Statement

The original contributions presented in the study are included in the Article and Supplementary Materials; further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to acknowledge Liliana Cichón and Silvina Garrido of Sanidad Vegetal, INTA Alto Valle, Río Negro, Argentina, as well as EEA-INTA San Juan, Argentina.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
HS-SPMEHeadspace solid-phase microextraction
GC-MSGas chromatography–mass spectrometry

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Figure 1. Schematic illustration of the oviposition assay showing a container with quince cultivars arranged in pairs.
Figure 1. Schematic illustration of the oviposition assay showing a container with quince cultivars arranged in pairs.
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Figure 2. Schematic illustration of the larval dual-choice arena showing a container with quince cultivars arranged in pairs.
Figure 2. Schematic illustration of the larval dual-choice arena showing a container with quince cultivars arranged in pairs.
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Figure 3. Principal component analysis of volatile chemical groups presents in four C. oblonga cultivars at the flowering stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and flowers of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
Figure 3. Principal component analysis of volatile chemical groups presents in four C. oblonga cultivars at the flowering stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and flowers of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
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Figure 4. Principal component analysis of volatile chemical groups presents in four C. oblonga cultivars at the fruit setting stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and fruits of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
Figure 4. Principal component analysis of volatile chemical groups presents in four C. oblonga cultivars at the fruit setting stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and fruits of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
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Figure 5. Principal component analysis of volatile chemical groups presents in the fruits and leaves of four C. oblonga cultivars at the fruit-growth stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and fruits of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
Figure 5. Principal component analysis of volatile chemical groups presents in the fruits and leaves of four C. oblonga cultivars at the fruit-growth stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and fruits of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
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Figure 6. Principal component analysis of volatile chemical groups presents in the fruits and leaves of four C. oblonga cultivars at the ripening stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and fruits of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
Figure 6. Principal component analysis of volatile chemical groups presents in the fruits and leaves of four C. oblonga cultivars at the ripening stage. Chemical groups represent the mean relative abundance (%) of volatiles from leaves and fruits of each cultivar. The analysis was performed using InfoStat software (v. 2020p).
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Figure 7. Percentage and number of eggs laid by C. pomonella according to quince cultivar combinations at the fruit-setting stage. The number of eggs differed significantly among cultivar combinations (*** p < 0.001, ** p < 0.01, * p < 0.05), as determined by the Chi-square MV-G2 test (α = 0.05). Cv. 1/Cv. 2 indicates the number of eggs laid on cultivar 1 and cultivar 2, respectively. The analysis was performed using InfoStat software (v. 2020p).
Figure 7. Percentage and number of eggs laid by C. pomonella according to quince cultivar combinations at the fruit-setting stage. The number of eggs differed significantly among cultivar combinations (*** p < 0.001, ** p < 0.01, * p < 0.05), as determined by the Chi-square MV-G2 test (α = 0.05). Cv. 1/Cv. 2 indicates the number of eggs laid on cultivar 1 and cultivar 2, respectively. The analysis was performed using InfoStat software (v. 2020p).
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Figure 8. Percentage and number of eggs laid by C. pomonella according to quince cultivar combinations at the fruit-growth stage. The number of eggs differed significantly among cultivar combinations (*** p < 0.001, ** p < 0.01,) or did not differ significantly (n.s., p > 0.05), as determined by the Chi-square MV-G2 test (α = 0.05). Cv. 1/Cv. 2 indicates the number of eggs laid on cultivar 1 and cultivar 2, respectively. The analysis was performed using InfoStat software (v. 2020p).
Figure 8. Percentage and number of eggs laid by C. pomonella according to quince cultivar combinations at the fruit-growth stage. The number of eggs differed significantly among cultivar combinations (*** p < 0.001, ** p < 0.01,) or did not differ significantly (n.s., p > 0.05), as determined by the Chi-square MV-G2 test (α = 0.05). Cv. 1/Cv. 2 indicates the number of eggs laid on cultivar 1 and cultivar 2, respectively. The analysis was performed using InfoStat software (v. 2020p).
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Figure 9. Percentage and number of eggs laid by C. pomonella according to quince cultivar combinations at the fruit-ripening stage. The number of eggs differed significantly among cultivar combinations (*** p < 0.001, ** p < 0.01, * p < 0.05) or did not differ significantly, as determined by the Chi-square MV-G2 test (α = 0.05). Cv. 1/Cv. 2 indicates the number of eggs laid on cultivar 1 and cultivar 2, respectively. The analysis was performed using InfoStat software (v. 2020p).
Figure 9. Percentage and number of eggs laid by C. pomonella according to quince cultivar combinations at the fruit-ripening stage. The number of eggs differed significantly among cultivar combinations (*** p < 0.001, ** p < 0.01, * p < 0.05) or did not differ significantly, as determined by the Chi-square MV-G2 test (α = 0.05). Cv. 1/Cv. 2 indicates the number of eggs laid on cultivar 1 and cultivar 2, respectively. The analysis was performed using InfoStat software (v. 2020p).
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Figure 10. Number of eggs laid by C. pomonella across phenological stages. N = 6 for all comparisons. Means were separated using the DGC post hoc test (p < 0.05). Black bars represent the standard error of the mean. Different letters above bars indicate significant differences (p < 0.05). Egg counts were fitted using a generalized linear model with a Poisson distribution. Analyses were performed using Infostat software (v. 2020p).
Figure 10. Number of eggs laid by C. pomonella across phenological stages. N = 6 for all comparisons. Means were separated using the DGC post hoc test (p < 0.05). Black bars represent the standard error of the mean. Different letters above bars indicate significant differences (p < 0.05). Egg counts were fitted using a generalized linear model with a Poisson distribution. Analyses were performed using Infostat software (v. 2020p).
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Figure 11. Percentage of C. pomonella neonate larvae choosing cultivar combinations at the fruit setting stage. N = 80. Larval choice frequencies differed significantly (* p < 0.05) or were not significant (n.s., p > 0.05) according to the chi-square MV-G2 test (α = 0.05). Analyses were performed using Infostat software (v. 2020p).
Figure 11. Percentage of C. pomonella neonate larvae choosing cultivar combinations at the fruit setting stage. N = 80. Larval choice frequencies differed significantly (* p < 0.05) or were not significant (n.s., p > 0.05) according to the chi-square MV-G2 test (α = 0.05). Analyses were performed using Infostat software (v. 2020p).
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Figure 12. Percentage of C. pomonella neonate larvae choosing cultivar combinations at the fruit-growth stage. N = 80. Larval choice frequencies were not significant (n.s., p > 0.05) according to the chi-square MV-G2 test (α = 0.05). Analyses were performed using Infostat software (v. 2020p).
Figure 12. Percentage of C. pomonella neonate larvae choosing cultivar combinations at the fruit-growth stage. N = 80. Larval choice frequencies were not significant (n.s., p > 0.05) according to the chi-square MV-G2 test (α = 0.05). Analyses were performed using Infostat software (v. 2020p).
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Figure 13. Percentage of C. pomonella neonate larvae choosing cultivar combinations at the fruit ripening stage. N = 80. Larval choice frequencies were not significant (n.s., p > 0.05) according to the chi-square MV-G2 test (α = 0.05). Analyses were performed using Infostat software (v. 2020p).
Figure 13. Percentage of C. pomonella neonate larvae choosing cultivar combinations at the fruit ripening stage. N = 80. Larval choice frequencies were not significant (n.s., p > 0.05) according to the chi-square MV-G2 test (α = 0.05). Analyses were performed using Infostat software (v. 2020p).
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Figure 14. Number of C. pomonella neonate larvae that make a choice by phenological stage. Means were separated using Fisher’s least significant difference (LSD) test (p < 0.05). Black bars represent the standard error of the mean. Different letters above the bars indicate a significant difference (p < 0.05). Larval choice frequency was fitted using a generalized linear model with a Poisson distribution. The analysis was performed using Infostat software (v. 2020p).
Figure 14. Number of C. pomonella neonate larvae that make a choice by phenological stage. Means were separated using Fisher’s least significant difference (LSD) test (p < 0.05). Black bars represent the standard error of the mean. Different letters above the bars indicate a significant difference (p < 0.05). Larval choice frequency was fitted using a generalized linear model with a Poisson distribution. The analysis was performed using Infostat software (v. 2020p).
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Table 1. Kairomones (K) and compounds with antennal activity (EAG+) present in flowers and leaves of four cultivars of C. oblonga cultivars at the flowering stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Table 1. Kairomones (K) and compounds with antennal activity (EAG+) present in flowers and leaves of four cultivars of C. oblonga cultivars at the flowering stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Volatile CompoundsRetention Time (min)Retention
Index		Cultivars
ChampionINTA 37INTA 117INTA 147
FlowersLeavesFlowersLeavesFlowersLeavesFlowersLeaves
1(Z)-3-hexen-1-ol (EAG+)6.2845.90.0056.3000.4310.5380.9234.3330.1012.777
2benzaldehyde (EAG+)12.1943nd0.2700.873nd0.3710.036ndnd
3(Z)-3-hexenyl acetate (EAG+)15.8985.10.08364.3641.83695.9878.16866.2920.33696.396
4limonene (EAG+/K)17.71013nd0.8011.362ndnd0.038ndnd
5(E)-β-ocimene (EAG+)19.710300.0331.5194.1730.0481.6230.0150.7710.006
6(3Z)-hexenyl butanoate (EAG+)33.81190.9nd0.295ndndndndndnd
7decanal (EAG+)34.81202ndnd0.300ndndndndnd
8β-caryophyllene (EAG+/K)41.71418.4nd4.871nd0.3310.8610.113ndnd
9(Z,E)-α-farnesene (EAG+)42.11434nd0.077ndnd1.1840.074ndnd
10germacrene D (EAG+)43.31482.1nd0.582ndndndndndnd
11(E,E)-α-farnesene (EAG+/K)43.81504.494.0551.42938.4640.00271.2555.14152.4800.001
12(3Z)-hexenyl benzoate (EAG+)45.21565nd0.080ndndndndndnd
Other compounds 4.8713.3533.702.949.816.3744.050.77
ChampionINTA 37INTA 117INTA 147
FlowersLeavesFlowersLeavesFlowersLeavesFlowersLeaves
Kairomone frequencies (K) 13222311
Kairomone relative abundances 94.067.1039.830.3372.125.2952.480.001
Frecuency of EAG+ compounds 411757844
Relative abundance of EAG+ compounds 94.1880.5947.4496.9184.3976.0453.6999.18
EAG+ and K refer to compounds previously reported in the literature as electroantennography-active (EAG-active) or behaviorally active (kairomones) for female codling moths. Other compounds refer to the remaining identified components of the volatile profile. nd, not detected.
Table 2. Kairomones (K) and compounds with antennal activity (EAG+) present in fruits and leaves of four cultivars of C. oblonga cultivars at the fruit-setting stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Table 2. Kairomones (K) and compounds with antennal activity (EAG+) present in fruits and leaves of four cultivars of C. oblonga cultivars at the fruit-setting stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Volatile CompoundsRetention Time (min)Retention IndexCultivars
ChampionINTA 37INTA 117INTA 147
FruitsLeavesFruitsLeavesFruitsLeavesFruitsLeaves
1(Z)-3-hexenol (EAG+)6.284717.2310.59534.9300.79118.5822.73624.3901.304
2benzaldehyde (EAG+)12.19520.103nd0.106nd0.013nd0.029nd
3β-myrcene (EAG+)14.4969ndndndnd0.308ndndnd
4(Z)-3-hexenyl acetate (EAG+)15.89855.97695.87517.05191.39040.60697.12740.68097.244
5hexyl acetate (EAG+)16.59900.218nd0.744nd1.415nd1.438nd
6limonene (EAG+/K)17.710180.1020.0610.1170.0170.055nd0.2310.051
7(E)-β-ocimene (EAG+)19.6102948.582nd9.807nd11.281nd9.647nd
8nonanal (EAG+)25.911000.067nd0.077ndndndndnd
9(Z,E)-α-farnesene (EAG+)42.114320.047nd0.035ndndnd0.127nd
Other compounds 26.3322.75834.1407.72825.9150.10723.0410.706
ChampionINTA 37INTA 117INTA 147
FruitsLeavesFruitsLeavesFruitsLeavesFruitsLeaves
Kairomone frequencies (K) 11111011
Kairomone relative abundances 0.100.060.120.020.050.000.230.05
Frecuency of EAG+ compounds 83837273
Relative abundance of EAG+ compounds 72.3396.5362.8792.2072.2699.8676.5498.60
EAG+ and K refer to compounds previously reported in the literature as electroantennography-active (EAG-active) or behaviorally active (kairomones) for female codling moths. Other compounds refer to the remaining identified components of the volatile profile. nd, not detected.
Table 3. Kairomones (K) and compounds with antennal activity (EAG+) present in fruits and leaves of four cultivars of C. oblonga cultivars at the fruit growth stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Table 3. Kairomones (K) and compounds with antennal activity (EAG+) present in fruits and leaves of four cultivars of C. oblonga cultivars at the fruit growth stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Volatile CompoundsRetention Time (min)Retention IndexCultivars
ChampionINTA 37INTA 117INTA 147
FruitsLeavesFruitsLeavesFruitsLeavesFruitsLeaves
1(Z)-3-hexenol (EAG+)6.184011.3567.2118.2150.1766.3820.15419.3960.172
2(E)-2-hexenal (EAG+)6.4851ndndnd4.197nd6.460nd6.449
3benzaldehyde (EAG+)12.2945nd0.093nd10.332nd10.477nd7.064
4β-pinene (EAG+)13.7961nd0.020nd3.156nd3.215nd2.633
56-methyl-5-hepten-2-one (EAG+)14.8973ndndnd0.439nd0.443nd0.354
6β-myrcene (EAG+)15.2976nd0.121nd5.487nd6.002nd7.408
7(Z)-3-hexenyl acetate (EAG+)15.69842.98436.8923.1420.3110.4100.2473.1790.041
8octanal (EAG+)16.1989ndndnd0.836nd0.720nd0.936
9hexyl acetate (EAG+)16.39910.808nd0.628nd0.119nd0.590nd
10limonene (EAG+/K)17.510170.3770.3030.15434.1630.47438.8560.26240.177
11(E)-β-ocimene (EAG+)19.510340.4150.1843.4140.5590.0670.4400.0880.905
12nonanal (EAG+) 26.71109ndndnd0.400nd0.364nd0.821
13methyl salicylate (EAG+)33.611740.326ndndndndndndnd
14decanal (EAG+)34.712000.218ndnd0.013nd0.039nd0.074
15(E,E)-α-farnesene (EAG+/K)43.715020.7900.3450.5950.0533.3520.0070.0240.007
Other compounds 74.08546.02378.35238.35884.95831.10573.30029.545
ChampionINTA 37INTA 117INTA 147
FruitsLeavesFruitsLeavesFruitsLeavesFruitsLeaves
Kairomone frequencies (K) 22222222
Kairomone relative abundances 1.170.650.7534.223.8338.860.2940.18
Frequency of EAG+ compounds 88612612612
Relative abundance of EAG+ compounds 17.2845.1716.1560.1210.8067.4223.5467.04
EAG+ and K refer to compounds previously reported in the literature as electroantennography-active (EAG-active) or behaviorally active (kairomones) for female codling moths. Other compounds refer to the remaining identified components of the volatile profile. nd, not detected.
Table 4. Kairomones (K) and compounds with antennal activity (EAG+) present in flowers and leaves of four cultivars of C. oblonga cultivars at the fruit-ripening stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Table 4. Kairomones (K) and compounds with antennal activity (EAG+) present in flowers and leaves of four cultivars of C. oblonga cultivars at the fruit-ripening stage. Determined by HS-SPME and GC/MS. The abundance of each compound is shown in relative proportion to the total.
Volatile CompoundsRetention Time (min)Retention IndexCultivars
ChampionINTA 37INTA 117INTA 147
FruitsLeavesFruitsLeavesFruitsLeavesFruitsLeaves
1(Z)-3-hexenol (EAG+)6.19846nd21.2382.73013.403nd7.181nd30.326
2benzaldehyde (EAG+)11.93942nd0.157nd0.271nd0.212nd0.786
36-methyl-5-hepten-2-one (EAG+)13.93963nd0.100nd0.149nd0.107nd0.112
4β-myrcene (EAG+)14.32969nd1.474nd1.909nd1.576nd1.471
5hexyl acetate (EAG+)16.519910.182nd0.168nd0.169nd0.176nd
6limonene (EAG+/K)17.5010058.88559.16927.84070.6287.88563.7103.80751.563
7(E)-β-ocimene (EAG+)19.4010340.0990.0470.0860.0310.0710.0440.0810.025
8decanal (EAG+)34.7612000.0670.0100.0600.0270.0540.0140.0630.021
9germacrene D (EAG+)43.241482ndndndndndnd0.249nd
10(E,E)-α-farnesene (EAG+/K)43.67150324.9700.01517.8910.0324.5720.0070.3250.005
Other compounds 51.91217.14646.08711.83582.59025.85191.43014.970
ChampionINTA 37INTA 117INTA 147
FruitsLeavesFruitsLeavesFruitsLeavesFruitsLeaves
Kairomone frequencies (K) 22222222
Kairomone relative abundances 33.8659.1845.7370.6612.4663.724.1351.57
Frequency of EAG+ compounds 58685868
Relative abundance of EAG+ compounds 34.2082.2148.7886.4512.7572.854.7084.31
EAG+ and K refer to compounds previously reported in the literature as electroantennography-active (EAG-active) or behaviorally active (kairomones) for female codling moths. Other compounds refer to the remaining identified components of the volatile profile. nd, not detected.
Table 5. Location and number of eggs laid by C. pomonella at the fruit-setting stage in four C. oblonga cultivars.
Table 5. Location and number of eggs laid by C. pomonella at the fruit-setting stage in four C. oblonga cultivars.
CultivarUbicationMeanE.E.
INTA 147Upper leaf surface12.431.07A
Lower leaf surface1.170.26C
INTA 117Upper leaf surface11.071.12A
Lower leaf surface0.470.19C
ChampionUpper leaf surface7.70.65B
Lower leaf surface0.110.07D
INTA 37Upper leaf surface6.450.63B
Lower leaf surface1.040.22C
Data were fitted using a generalized Poisson model. Means were separated using the DGC post hoc test (p < 0.05). N = 6 for all comparisons. Analyses were performed using Infostat software (version 2020p). Means sharing a common letter are not significantly different (p > 0.05).
Table 6. Location and number of eggs laid by C. pomonella at the fruit-growth stage in four C. oblonga cultivars.
Table 6. Location and number of eggs laid by C. pomonella at the fruit-growth stage in four C. oblonga cultivars.
CultivarUbicationMeanE.E.
INTA 147Upper leaf surface34.151.57A
Lower leaf surface3.840.44F
Branches0.290.12G
INTA 117Upper leaf surface31.351.64A
Lower leaf surface8.750.77D
Branches0.660.2G
ChampionUpper leaf surface22.751.31B
Lower leaf surface5.760.6E
Branches0.470.17G
INTA 37Upper leaf surface17.171.01C
Lower leaf surface3.750.44F
Branches0.250.11G
Data were fitted using a generalized Poisson model. Means were separated using the DGC post hoc test (p < 0.05). N = 6 for all comparisons. Analyses were performed using Infostat software (version 2020p). Means sharing a common letter are not significantly different (p > 0.05).
Table 7. Location and number of eggs laid by C. pomonella at the fruit-ripening stage in four C. oblonga cultivars.
Table 7. Location and number of eggs laid by C. pomonella at the fruit-ripening stage in four C. oblonga cultivars.
CultivarUbicationMeanE.E.
INTA 147Upper leaf surface7.790.88A
Lower leaf surface1.290.31C
Fruit6.640.8A
ChampionUpper leaf surface6.120.66A
Lower leaf surface0.780.2C
Fruit2.430.37B
INTA 117Upper leaf surface3.040.43B
Lower leaf surface0.670.19C
Fruit2.320.37B
INTA 37Upper leaf surface2.20.34B
Lower leaf surface0.240.11D
Fruit1.170.25C
Data were fitted using a generalized Poisson model. Means were separated using the DGC post hoc test (p < 0.05). N = 6 for all comparisons. Analyses were performed using Infostat software (version 2020p). Means sharing a common letter are not significantly different (p > 0.05).
Table 8. Number of C. pomonella neonate larvae exhibiting different behaviors for each combination of C. oblonga cultivars at the fruit setting stage.
Table 8. Number of C. pomonella neonate larvae exhibiting different behaviors for each combination of C. oblonga cultivars at the fruit setting stage.
Cultivar-Dominant AreaCultivar-Distant Area
CombinationChoiceArrest CvArrest CenterWanderingG2glp
Champion-INTA37278222312.1730.0068
Champion-INTA1172411153011.330.0102
Champion-INTA147271413268.6630.0341
INTA37-INTA1172610162811.4830.0094
INTA37-INTA147269192610.9630.0119
INTA117-INTA1472413133010.6830.0136
Total1546598163
Different larval behaviors by treatment combination. N = 80 larvae. Chi-square test (MV-G2). Choice refers to larvae that selected a cultivar. Arrest Cv refers to larvae that remained arrested near a cultivar. Arrest Center refers to larvae that remained arrested in the center of the arena. Wandering refers to larvae that moved throughout the arena without making a clear choice.
Table 9. Number of C. pomonella neonate larvae exhibiting different behaviors for each combination of C. oblonga cultivars at the fruit-growth stage.
Table 9. Number of C. pomonella neonate larvae exhibiting different behaviors for each combination of C. oblonga cultivars at the fruit-growth stage.
Cultivar-Distant AreaCultivar-Distant Area
CombinationChoiceArrest CvArrest
Center		WanderingG2glp
Champion-INTA3754821676.263<0.0001
Champion-INTA11748662055.153<0.0001
Champion-INTA147471022159.293<0.0001
INTA37-INTA11747562256.23<0.0001
INTA37-INTA14742552853.443<0.0001
INTA117-INTA14743862343.153<0.0001
Total2814227130
Different larval behaviors by treatment combination. N = 80 larvae. Chi-square test (MV-G2). Choice refers to larvae that selected a cultivar. Arrest Cv refers to larvae that remained arrested near a cultivar. Arrest Center refers to larvae that remained arrested in the center of the arena. Wandering refers to larvae that moved throughout the arena without making a clear choice.
Table 10. Number of C. pomonella neonate larvae exhibiting different behaviors for each combination of C. oblonga cultivars at the fruit ripening stage.
Table 10. Number of C. pomonella neonate larvae exhibiting different behaviors for each combination of C. oblonga cultivars at the fruit ripening stage.
Cultivar-Distant AreaCultivar-Distant Area
CombinationChoiceArrest CvArrest
Center		WanderingG2glp
Champion-INTA3740633156.793<0.0001
Champion-INTA1172711152710.6330.0139
Champion-INTA14729883531.43<0.0001
INTA37-INTA1171211114638.063<0.0001
INTA37-INTA147107125154.663<0.0001
INTA117-INTA147201364133.213<0.0001
Total1385655231
Different larval behaviors by treatment combination. N = 80 larvae. Chi-square test (MV-G2). Choice refers to larvae that selected a cultivar. Arrest Cv refers to larvae that remained arrested near a cultivar. Arrest Center refers to larvae that remained arrested in the center of the arena. Wandering refers to larvae that moved throughout the arena without making a clear choice.
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MDPI and ACS Style

Gomez, M.P.; Jofré Barud, F.; Jaled, S.; Garrido, S.; Cichón, L.; López, M.L. Exploring the Possible Role of Semiochemicals in Quince (Cydonia oblonga Mill.): Implications for the Biological Behavior of Cydia pomonella. Agronomy 2026, 16, 331. https://doi.org/10.3390/agronomy16030331

AMA Style

Gomez MP, Jofré Barud F, Jaled S, Garrido S, Cichón L, López ML. Exploring the Possible Role of Semiochemicals in Quince (Cydonia oblonga Mill.): Implications for the Biological Behavior of Cydia pomonella. Agronomy. 2026; 16(3):331. https://doi.org/10.3390/agronomy16030331

Chicago/Turabian Style

Gomez, María Pía, Flavia Jofré Barud, Sayra Jaled, Silvina Garrido, Liliana Cichón, and María Liza López. 2026. "Exploring the Possible Role of Semiochemicals in Quince (Cydonia oblonga Mill.): Implications for the Biological Behavior of Cydia pomonella" Agronomy 16, no. 3: 331. https://doi.org/10.3390/agronomy16030331

APA Style

Gomez, M. P., Jofré Barud, F., Jaled, S., Garrido, S., Cichón, L., & López, M. L. (2026). Exploring the Possible Role of Semiochemicals in Quince (Cydonia oblonga Mill.): Implications for the Biological Behavior of Cydia pomonella. Agronomy, 16(3), 331. https://doi.org/10.3390/agronomy16030331

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