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Caffeic Acid and Biopesticides Interactions for the Control of Storage Beetles
Caffeic Acid and Biopesticides Interactions for the Control of Storage Beetles
Zarmakoupi, Chrysanthi;Mpistiolis, Konstantinos;Pantazis, George;Psatha, Panagiota;Dimitriadi, Despoina;Kitsiou, Foteini;Eliopoulos, Panagiotis;Patakioutas, George;Mantzoukas, Spiridon
Article Caffeic Acid and Biopesticides Interactions for the Control of Storage Beetles 1 1 1 1 2 Chrysanthi Zarmakoupi , Konstantinos Mpistiolis , George Pantazis , Panagiota Psatha , Despoina Dimitriadi , 1 3 , 1 , 1 , Foteini Kitsiou , Panagiotis Eliopoulos * , George Patakioutas * and Spiridon Mantzoukas * Department of Agriculture, University of Ioannina, 45100 Ioannina, Greece Karvelas AVEE, 80 km N.R. Athens-Lamia, 32200 Thiva, Greece Laboratory of Plant Health Management, Department of Agrotechnology, University of Thessaly, Geopolis, 45100 Larissa, Greece * Correspondence: firstname.lastname@example.org (P.E.); email@example.com (G.P.); firstname.lastname@example.org (S.M.) Abstract: Infestations of stored-product pests cause signiﬁcant losses of agricultural produce every year. Despite various environmental and health risks, chemical insecticides are now a ready-to-use solution for pest control. Against this background and in the context of Integrated Pest Management research, the present study focuses on the potential insecticidal effect of caffeic acid at ﬁve different concentrations (250, 500, 750, 1500 and 3000 ppm), and their combination with Cydia pomonella Granulovirus (CpGV), Bacillus thuringiensis subsp. tenebrionis and Beauveria bassiana strain GHA on three major insect stored-product beetle species, Tribolium confusum (Coleoptera: Tenebrionidae), Cryptolestes ferrugineus (Coleoptera: Laemophloeidae) and Trogoderma granarium Everts (Coleoptera: Dermestidae). Treatment efﬁcacy was expressed as mortality in relation to exposure time and adult species number. Compared to the control, the results showed a clear dose-dependent pesticidal activity, expressed as signiﬁcant adult mortality at a high-dose application, although some of the combinations of caffeic acid concentrations with the other substances acted positively (synergistically and additively) and some negatively. Based on our results, bioinsecticides can be combined with plant compounds such as caffeic acid and be integrated with other modern IPM tools in storage facilities. Citation: Zarmakoupi, C.; Mpistiolis, Keywords: caffeic acid; biopesticides; Cydia pomonella Granulovirus; Bacillus thuringiensis subsp. K.; Pantazis, G.; Psatha, P.; Dimitriadi, tenebrionis; Beauveria bassiana; interactions; stored pests D.; Kitsiou, F.; Eliopoulos, P.; Patakioutas, G.; Mantzoukas, S. Caffeic Acid and Biopesticides Interactions for the Control of 1. Introduction Storage Beetles. Appl. Biosci. 2023, 2, 211–221. https://doi.org/10.3390/ Storage pests can cause signiﬁcant economic losses by contaminating stored products, applbiosci2020015 resulting in both quantitative and qualitative deterioration. The deterioration of stored commodities is caused not only by the consumption of the product, but also by the con- Academic Editor: Robert Henry tamination of dead skin, excreta and dead insects, that can be dangerous for human health Received: 10 January 2023 because they cause allergic reactions [1,2]. Moreover, the presence of insect populations in Revised: 27 March 2023 stored products can considerably increase relative humidity, which promotes secondary Accepted: 4 May 2023 fungal infestations . Most agricultural products can be affected by such infestations, Published: 8 May 2023 resulting in annual losses of 9–20% . Practices such as sanitation, aeration cooling, drying and controlled atmospheres are implemented, but are not sufﬁcient to effectively control insect infestations in storage facilities . Until now, fumigation with synthetic insecticides such as phosphine was Copyright: © 2023 by the authors. primarily applied in storage facilities for disinfestation, but the increasing hazards to human Licensee MDPI, Basel, Switzerland. health and the environment restricted their use [5,6]. Needless to say, the overreliance on This article is an open access article these substances all these years has led to resistance development,  and the neglect of distributed under the terms and research into alternative control methods . conditions of the Creative Commons Due to the above facts, new investigations have recently emerged aimed at ﬁnding Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ more ecological methods for the management of storage pests, by utilizing natural plant 4.0/). compounds or more speciﬁc products of plants’ secondary metabolism such as essential Appl. Biosci. 2023, 2, 211–221. https://doi.org/10.3390/applbiosci2020015 https://www.mdpi.com/journal/applbiosci Appl. Biosci. 2023, 2 212 oils. Apart from the fact that they do not pollute the environment, they are very effective against insects due to their volatility . Substances derived from metabolic reactions of plants can be bioactive towards insects, as they are part of their natural defense mechanisms and include compounds such as terpenes, ﬂavonoids, alkaloids, polyphenols, quinones, and others . Plant extracts and essential oils can exert a wide range of actions against insects, such as toxicity, repellency, inhibition of respiration, oviposition, growth or feeding and a reduction in adult emergence and abnormalities in larvicidal transitions [10–12]. Phenolic acids such as salicylic, coumaric, caffeic and chlorogenic acids are ubiqui- tously present in plants and mostly participate in plant defense mechanisms . Some of these substances have already been investigated to utilize the natural immunity of plants in the concept of biological control in agriculture. Caffeic acid (CA) is an early interme- diate of phenylpropanoid metabolism, and a precursor for structural polyphenols and many biologically active secondary compounds that are important in the plant defense mechanisms [14,15]. This speciﬁc phenolic compound has been attributed to antifungal, antibacterial and insecticidal properties . Another promising aspect of insect biological control is the use of entomopathogens. This approach has been thoroughly investigated lately as they offer a great alternative in the context of integrated pest management (IPM). Viruses, bacteria and fungi have been described as effective against various insect species [16–18]. These insect pathogens are not hazardous as they already exist in nature and so have a very low environmental impact and low mammalian toxicity [19,20]. There have been some studies that investigated the synergistic effect of insect pathogens with biopesticides, and the results have varied between a lesser, zero or enhanced efﬁcacy against arthropods. In this context, the present study aimed to investigate the efﬁcacy of CA, in combina- tion with commercially available biopesticides (fungal, viral and bacterial) on three major insect stored-product beetle species. All tested species are globally distributed stored- product pests and cause serious quantitative and qualitative losses in a vast range of com- modities. Our results are discussed in the context of enhancing the use of insect pathogens as a key component of integrated pest management against stored-product pests. 2. Materials and Methods 2.1. Insect Rearing Three important stored-product beetle species were selected for experimentation. The insect species tested were T. confusum, C. ferrugineus and T. granarium. Insects were reared in incubators (PHC Europe/Sanyo/Panasonic Biomedical MLR-352-PE) at 27.5 C and 75% relative humidity (r.h.). T. granarium was kept on whole wheat, C. ferrugineus on rolled oats with 5% brewer ’s yeast, and T. confusum on whole wheat ﬂour with 10% brewer ’s yeast. Adults of uniform age (<2 weeks old) and mixed sex were used for experimentation. 2.2. Caffeic Acid Solution and Biopesticides The solution was obtained for Karvelas AVEE with lot number 15038821. The composi- tion of the tested solution was natural caffeic acid at 1120 mg/kg, conductivity 97.9 mS/cm, pH 4.62 and density 1.215 g/cm . Biopesticides tested during the present study were commercial formulations obtained from the market. Speciﬁcally, we used Madex (Cydia pomonella granulovirus (CpGV) (Hellafarm, Athens, Greece), Novodor FC (Bacillus thuringiensis subsp. Tenebrionis 3%) (BIOFA Germany, Bad Boll, Germany) and Botanigard 10.7SC (Beauveria bassiana strain GHA 10.735%) (K&N Efthymiadis Single Member S.A., Thessaloniki, Greece). 2.3. Experimental Procedure 500 g of wheat (var. Mexa) were divided into separate lots and ﬁlled into 0.45 L cylinder jars. Since it is difﬁcult for these species to reproduce on intact grains, the wheat used had 5% broken kernels. The wheat was stored for 28 days under ambient conditions to adjust the moisture content (m.c.) to 12%. Appl. Biosci. 2023, 2 213 Experimentation included ﬁve concentrations of CA solution (Karvellas AVEE, Thiva, Greece) (250 ppm, 500 ppm, 750, ppm, 1500 ppm and 3000 ppm) and one (3000 ppm) for commercial biopesticides. The solvent used to prepare all solutions was distilled water. Twenty 10 g wheat samples were taken from the jars and placed in 9 cm Petri dishes. Following this, ten adult beetles of each species, of uniform age (<2 weeks old) and mixed sex, were transferred to each Petri dish. The inner “neck” of the Petri dish was covered with ﬂuon to prevent insect escape (Northern Products, Woonsocket, RI, USA). A Potter spray tower (Burkard Manufacturing Co., Ltd., Rickmansworth, Hertfordshire, UK) was used to apply the solutions to the products at a rate of 1 kgf cm . For separate doses testing, the experimental adults were sprayed once with 2 mL of the CA or biopesticide. Conversely, for the combined treatments, spraying was performed twice, once with 2 mL of the CA solution and once with 2 mL of the biopesticide solution, each 2 s apart. The Petri dishes were then transferred to Toshiba incubators (PHC Europe/Sanyo/Panasonic Biomedical MLR-352-PE) and set at 27.5 C and 75% relative humidity. The beetles were observed daily, and mortality was recorded 7, 14, 21, and 28 days after treatment. The entire procedure was repeated twenty times by preparing new batches of treated and untreated grains at each replicate (separate treatments: 9 3 20 = 540 Petri dishes for each dose insect species replicate, combined treatments: 15 3 20 = 900 Petri dishes for each dose insect species replicate). 2.4. Mathematical Estimation and Statistical Analysis The interaction between the CA and the biopesticides was estimated using the formula of Robertson and Preisler: P = P + (1 P ) (P ) + (1 P ) (1 P ) (P ), E 0 0 1 0 1 2 where: P is the expected mortality induced by the combined treatment; P is the mor- E 0 tality of the control; P is the mortality caused by the CA; P is the mortality caused by 1 2 the biopesticide. 2 2 2 Distribution was determined by the chi-square formula: x = (L L ) /L + (D D ) / 0 E E 0 E D where L is the number of living adults, D is the number of dead larvae, L is the E 0 0 E expected number of live larvae, and D is the expected number of dead larvae. The formula was used to test the hypothesis independent–simultaneous relationship (1 df, p = 0.05). 2 2 If x < 3.84, the ratio is deﬁned as additive (A); if x > 3.84 and the observed mortality is higher than expected, the relationship is deﬁned as synergistic (S). On the contrary, if x > 3.84 and the observed mortality is less than expected, the relationship is deﬁned as competitive (C). The general linear model of SPSS (version 23.0, IBM Corp., Armonk, NY, USA) was then used to evaluate the data using a three-way ANOVA (IBM 2014). The Bonferroni test was used to compare means in cases where there were substantial F values. 3. Results The results of the laboratory bioassays on adults of T. granarium, C. ferrugineus, and T. confusum showed that separate treatments with CA and all pathogens caused varying degrees of time-, treatment- and dose-dependent mortality. Adult mortality of T. granarium was 57–73%, of C. ferrugineus was 43–67%, and of T. confusum was 27–67% twenty-eight days after treatment with CA solution at the highest dose (3000 ppm). After twenty-eight days, the application of B. thuringiensis caused 67% mortality in T. granarium adults, 73% in C. ferrugineus, and 69% in T. confusum. After twenty-eight days of CpGV treatment, the observed mortality of adults of T. granarium, C. ferrugineus, and T. confusum was 70%, 43%, and 47%, respectively. The mortality of T. confusum, C. ferrugineus, and T. granarium after twenty-eight days of treatment with B. bassiana was 93%, 77%, and 93%, respectively. In all of the tested insects, the control mortality was less than 3%. According to results of the combined bioassays, all combinations tested induced vari- ous levels of time- and dose-dependent mortality (Table 1). The results of the combined Appl. Biosci. 2023, 2 214 treatments showed a distinct interaction between treatments, as follows: for T. granarium adults, the interaction between the pathogens was additive in nine combinations the ﬁrst seven days, synergistic in two and antagonistic in ﬁve. The following fourteen days, the interactions proved to be additive in seven combinations, synergistic in one and antago- nistic in six. After twenty-one days, the interaction was additive in eight combinations and competitive in seven (Table 1). Finally, twenty-eight days later, the interaction was characterized as additive in seven combinations and competitive in eight (Table 1). Adult T. granarium mortality was between 37 and 100% (F: 19.764; df: 654.2360; p: <0.001) (overall 15 treatments). Interactions between treatments on T. confusum for seven days were additive in ten combinations, synergistic in four combinations and competitive in one combination. For fourteen days, the interactions between treatments were all additive. At twenty-one days, the interaction between treatments was additive in fourteen combinations and synergistic in one combination (Table 2). As for the twenty-eighth day, the interaction between treatments was additive in fourteen combinations and synergistic in one combination (Table 2). Adult T. confusum mortality ranged from 27 to 100% (F: 20.764; df: 654.2360; p: <0.001) (overall 15 treatments). Appl. Biosci. 2023, 2 215 Table 1. Percentage of observed and expected mortality of T. granarium adults at seven, fourteen, twenty-one and twenty-eight days of the experiment, treated with treatments in several combinations, and their interactions (n = 100). Mortality Mortality Mortality Mortality 2 3 2 2 2 Treatment Interaction Interaction Interaction x Interaction x x x 1 2 Observed% Expected% Observed% Expected% Observed% Expected% Observed% Expected% Entomopathogen caffeic acid 7 days 14 days 21 days 28 days (ppm) (3000 ppm) 250 37 55 7.0100 C 37 75 18.7841 C 43 84 46.0425 C 47 89 30.6352 C 500 37 63 7.0169 C 37 75 18.5344 C 47 86 40.2042 C 47 89 30.0133 C Bacillus 750 37 61 7.0094 C 40 75 17.4215 C 47 84 34.6456 C 53 89 29.2205 C thuringiensis 1500 40 61 7.0292 C 47 74 15.5904 C 47 85 29.3120 C 57 89 23.8527 C 3000 43 63 7.0450 C 57 79 4.3251 C 60 85 11.9527 C 67 93 18.5516 C 250 40 42 0.0435 A 57 67 0.7815 A 62 78 3.2709 A 69 90 7.6806 C Cydia pomonella 500 57 53 0.3601 A 62 67 0.0967 A 70 80 1.9105 A 77 90 2.7879 A Granulovirus 750 60 50 1.6065 A 65 67 0.1029 A 70 78 0.8179 A 77 90 2.7879 A (CpGV) 1500 67 50 9.3082 S 77 72 0.5404 A 71 79 0.8291 A 81 90 3.2932 A 3000 67 53 2.7871 A 79 65 3.1823 A 83 79 0.6247 A 89 94 0.5655 A 250 47 53 0.5122 A 57 87 15.8274 C 69 97 66.4130 C 84 98 16.5679 C 500 50 62 1.4289 A 83 87 0.0438 A 87 97 9.3253 C 90 98 4.1772 C Beauveria 750 52 59 0.3538 A 97 87 3.5782 A 93 97 1.0476 A 93 98 1.0648 A bassiana strain 1500 57 59 0.0292 A 100 89 4.4242 S 100 97 1.0261 A 100 98 1.0154 A GHA 3000 60 62 0.0162 A 100 86 5.6963 S 100 97 1.0261 A 100 98 1.0070 A 1 2 3 4 ® : Percentage of dead adults recorded during experiments. : Mortality calculated according to Robertson and Preisler. : A = Additive, C = Competitive, S = Synergistic. : Novodor 5 ® 6 ® FC (BIOFA Germany). : Madex (Hellafarm, Athens. Greece). : Botanigard 10.7SC (K&N Efthymiadis Single Member S.A., Thessaloniki, Greece). Table 2. Percentage of observed and expected mortality of T. confusum adults at seven, fourteen, twenty-one and twenty-eight days of the experiment, treated with treatments in several combinations, and their interactions (A = Additive, C = Competitive, S = Synergistic) (n = 100). Expected mortality calculated according to Robertson and Preisler . Mortality Mortality Mortality Mortality 2 3 2 2 2 Treatment Interaction Interaction Interaction x Interaction x x x 1 2 Observed% Expected% Observed% Expected% Observed% Expected% Observed% Expected% Entomopathogen caffeic acid 7 days 14 days 21 days 28 days (ppm) (3000 ppm) 250 20 19 0.0558 A 37 50 1.4805 A 43 61 3.7692 A 63 78 3.2719 A 500 30 22 1.3274 A 37 51 2.2317 A 50 64 2.4033 A 80 83 0.0296 A Bacillus 750 35 25 1.6483 A 50 56 0.2562 A 63 68 0.2309 A 90 85 0.8895 A thuringiensis 1500 47 19 15.6913 S 50 58 0.6202 A 77 70 1.1977 A 93 88 0.9887 A 3000 47 25 7.7754 S 57 60 0.1210 A 83 70 3.1762 A 97 90 1.6296 A 250 23 28 0.3229 A 40 48 0.6507 A 50 53 0.0373 A 63 62 0.0688 A Cydia pomonella 500 33 30 0.1053 A 57 50 0.8984 A 60 56 0.3524 A 80 71 1.3673 A Granulovirus 750 33 34 0.0037 A 57 55 0.1206 A 60 61 0.0050 A 87 74 2.7530 A (CpGV) 1500 47 28 5.5592 S 60 56 0.3524 A 67 63 0.4454 A 90 79 2.7072 A 3000 47 34 2.4437 S 63 59 0.3567 A 77 63 3.1074 A 97 83 5.0396 S Appl. Biosci. 2023, 2 216 Table 2. Cont. Mortality Mortality Mortality Mortality 2 3 2 2 2 Treatment Interaction Interaction Interaction x Interaction x x x 1 2 Observed% Expected% Observed% Expected% Observed% Expected% Observed% Expected% 250 10 31 5.9015 C 43 51 0.6802 A 77 85 0.9549 A 87 95 2.0092 A 500 23 33 1.1206 A 50 53 0.0492 A 87 86 0.2435 A 90 96 0.6173 A Beauveria 750 23 36 1.9048 A 67 57 1.2404 A 87 88 0.0046 A 90 97 0.6355 A bassiana strain 1500 37 31 0.5979 A 67 59 1.0598 A 97 88 2.6542 A 93 97 1.2666 A GHA 3000 40 36 0.3271 A 70 62 1.1024 A 100 88 4.4576 S 100 98 1.0154 A 1 2 3 4 ® : Percentage of dead adults recorded during experiments. : Mortality calculated according to Robertson and Preisler. : A = Additive, C = Competitive, S = Synergistic. : Novodor 5 ® 6 ® FC (BIOFA Germany). : Madex (Hellafarm, Athens, Greece). : Botanigard 10.7SC (K&N Efthymiadis Single Member S.A., Thessaloniki, Greece). The interaction between treatments for C. ferrugineus was additive in ten combinations and competitive in ﬁve combinations over the ﬁrst seven days. After fourteen and twenty-one days, the interactions between the treatments were all additive. At last, for twenty-eight days, the interaction between the treatments was additive in fourteen combinations and synergistic in one combination (Table 3). Adult C. ferrugineus mortality was 10–100% (F: 15.164; df: 654.2360; p: <0.001) (overall 15 treatments). Table 3. Percentage of observed and expected mortality of C. ferrugineus adults at seven, fourteen, twenty-one and twenty eight days of the experiment, treated with treatments in several combinations, and their interactions (A = Additive, C = Competitive, S = Synergistic) (n = 100). Expected mortality calculated according to Robertson and Preisler . Mortality Mortality Mortality Mortality 2 3 2 2 2 Treatment Interaction Interaction Interaction x Interaction x x x 1 2 Observed% Expected% Observed% Expected% Observed% Expected% Observed% Expected% Entomopathogen caffeic acid 7 days 14 days 21 days 28 days (ppm) (3000 ppm) 250 10 46 14.4489 C 57 60 0.1155 A 70 79 0.8927 A 90 86 0.8651 A 500 20 48 9.0018 C 67 64 0.1496 A 73 79 0.3189 A 93 86 1.8692 A Bacillus 750 27 51 6.5817 C 70 64 0.5271 A 81 81 0.0151 A 93 86 1.8692 A thuringiensis 1500 33 55 5.3190 C 70 68 0.1276 A 83 84 0.0029 A 97 88 2.6660 A 3000 33 55 5.3190 C 77 72 0.6169 A 91 84 1.2601 A 100 92 3.2246 A 250 27 20 0.9188 A 53 60 0.6191 A 67 64 0.1496 A 73 70 0.4055 A Cydia pomonella 500 27 23 0.3924 A 60 64 0.1692 A 73 64 1.1362 A 80 70 2.0486 A Granulovirus 750 30 27 0.1455 A 60 64 0.1692 A 77 68 1.3612 A 87 70 4.9951 S (CpGV) 1500 37 33 0.3555 A 63 68 0.2114 A 83 72 2.2449 A 87 75 2.6684 A 3000 40 33 0.8740 A 67 72 0.1750 A 83 72 2.2449 A 90 83 1.7042 A 250 20 20 0.0000 A 53 67 2.5699 A 73 75 0.0142 A 83 88 0.3815 A 500 23 23 0.0337 A 56 70 2.8425 A 73 75 0.0142 A 93 88 0.9946 A Beauveria 750 30 27 0.1455 A 67 70 0.1390 A 80 77 0.1733 A 93 88 0.9946 A bassiana strain 1500 37 33 0.3555 A 73 73 0.0902 A 87 80 0.9188 A 97 90 2.5684 A GHA 3000 37 33 0.3555 A 77 77 0.1522 A 87 80 0.9188 A 97 93 1.5232 A 1 2 3 4 ® : Percentage of dead adults recorded during experiments. : Mortality calculated according to Robertson and Preisler. : A = Additive, C = Competitive, S = Synergistic. : Novodor 5 ® 6 ® FC (BIOFA Germany). : Madex (Hellafarm, Athens. Greece). : Botanigard 10.7SC (K&N Efthymiadis Single Member S.A., Thessaloniki, Greece). Appl. Biosci. 2023, 2 217 Overall, all the main effects of examined factors (insect species, exposure time, treat- ment) and their interactions proved to be signiﬁcant as was demonstrated by a 3-way analysis of variance (Table 4). Table 4. An analysis of variance (3-way ANOVA) for the main effects and interactions for the mortality of T. granarium, T. confusum and C. ferrugineus adults exposed to separate and combined treatments with CA and biopesticides. Separate Treatments Combined Treatments Source df F Sig. df F Sig. Exposure time 3 11.838 <0.001 3 8.142 <0.001 Insect species 2 10.099 <0.001 2 6.499 <0.001 Treatment 3 16.476 <0.001 4 3.702 <0.001 Exposure time * Insect species 6 11.109 <0.001 6 7.288 <0.001 Exposure time * Treatment 9 11.540 <0.001 12 11.534 <0.001 Insect Species * Treatment 6 13.829 <0.001 8 5.420 <0.001 Exposure time * Insect species * Treatment 16 14.950 <0.001 24 9.946 <0.001 Error 210 380 Total 280 400 Corrected total 279 399 4. Discussion As chemical insecticides are being more and more neglected, many studies now focus on alternatives, investigating compounds derived from nature. Plant chemicals can act as insecticides by preventing insects from feeding or by demonstrating repellent and growth inhibition effects [21,22]. The insecticidal potential of phenolic plant compounds such as CA has been well documented [23–28]. In our bioassays, adult beetles treated only with CA showed noteworthy mortality (up to 70%). The lethal effect of CA on insects has been also veriﬁed for the tobacco cutworm, Spodoptera litura (Fabricius)  and the cotton bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) . Apart from mortality effects, various studies have demonstrated that CA and other plant phenolic compounds may have negative effects on insect feeding, larval growth rate and reproduction [31–35]. Paciﬁco et al.  investigated the effect of CA on the larvae of Phthorimaea operculella and recorded sublethal effects and anti-nutrient action as it inhibited larval growth. A possible explanation for these results may lie in the interaction of the phenolic compounds with digestive proteins of the insects leading to a decrease in nutritional quality. The way phenolic compounds affect the interaction of plants with bacteria and fungi has already been investigated even though little is known about the toxicity of phenolics against insects . As expected, separate treatments with biopesticides caused high mortality in all tested species. There are several main factors that can inﬂuence the efﬁcacy of biopesticides, such as the type of biopathogen, the dose applied, temperature, relative humidity and the type of product [20,37–43]. Moreover, the insecticidal efﬁcacy of biopesticides can be highly inﬂuenced by a host’s physiology, morphology and behavior, the population density, age, nutrition, and genetic information . Our original hypothesis was that the interaction between CA and biopesticides either leads to additional efﬁcacy or plays only a supporting role. Based on our results, the interac- tion was additive in T. confusum in most combinations. On the other hand, it was negative in four treatments in some combinations for T. granarium and C. ferrugineus adults, especially in the ﬁrst 7 days of the experiment when the bacterial insecticide was applied. A negative Appl. Biosci. 2023, 2 218 interaction refers to the competitive relationship between CA and the pathogen. The nature of this competition is not precisely known. Entomopathogenic microorganisms have also shown increased efﬁcacy when applied in combination treatments not only with other entomopathogens but also with synthetic insecticides . Regarding their coexistence with plant extracts, entomopathogenic microorganisms have shown both an inhibitory effect  and a positive interaction as Neem seed cake improved the pathogenicity of the fungus Metarhizium anisopliae against the Black Vine Weevil . The entomopathogenic fungus M. anisopliae has been successfully combined with plant extracts for the control of ticks , whereas other plant extracts showed compatible capacity with entomopathogenic bacteria against aphids . To the best of our knowledge, there are no data available concerning the interaction of CA or other plant phenolic metabolites with entomopathogens. In general, combinations of feeding stimulants and deterrents affect the feeding re- sponse of phytophagous insects [49,50]. It has been suggested that the Colorado potato beetle selects its hosts among solanaceous plants based on the presence of deterrents such as alkaloid glycosides rather than on the presence of feeding stimulants [51,52]. Various types of sesquiterpene lactones are present in Asteraceae and deter numerous phytophagous insects from feeding on the plants . Caffeic acid derivatives play an important role in plant defense . Chlorogenic acid has been reported to inhibit larval development of some Lepidoptera, such as H. armigera, the corn earworm Heliothis zea (Boddie), and the fall armyworm Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) [55–58] and deters feeding in leaf beetles Lochmaea caprea (L.) , and Agelastica alni (L.) (Coleoptera: Chrysomelidae) [60,61]. To conclude, the interactions between tested insecticidal agents could be positive or negative, acting synergistically (increasing host mortality compared to single pathogen infections) [20,62,63] or antagonistically (reducing the observed host mortality compared to single pathogen infections) . Needless to say, pest mortality can be affected by genotype, dose and sequence of infection [65,66]. 5. Conclusions Based on our results, the combined application of plant extracts and entomopathogenic microorganisms may become an effective strategy for eco-friendly pest management in storage facilities. However, special attention should be paid to the selection of the combined agents as the additive or synergistic effect is not always valid. Our study has shown the signiﬁcant insecticidal action of CA alone or in combination with biopesticides. Further research is needed to clarify the effects of various factors, such as pest species, storage environment, application dose, time interval, stored product type, etc., and to enhance the use of plant compounds in stored-product IPM. Author Contributions: Conceptualization, S.M. and D.D.; methodology, S.M.; software, S.M.; vali- dation, S.M., G.P. (Georgios Parakioutas) and P.E.; formal analysis, S.M.; investigation, C.Z., K.M., G.P. (Georgios Pantazis ), P.P. and F.K.; resources, S.M.; data curation, S.M.; writing—original draft preparation, S.M., G.P. (Georgios Parakioutas) and P.E.; writing—review and editing, S.M., G.P. (Georgios Parakioutas), P.E. and F.K.; visualization, S.M.; supervision, S.M.; project administration, S.M. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. 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Caffeic Acid and Biopesticides Interactions for the Control of Storage Beetles
, Volume 2 (2) –
May 8, 2023
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