Effectiveness of insecticidal and fungicidal seed treatments in reducing hooded crow (Corvus cornix) predation on sunflower and maize seeds under field conditions

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The experiment was conducted at the Experimental Farm of Nubaria Agricultural Research Station, Behaira Governorate, Egypt, using a Randomized Complete Block Design (RCBD) with three replicates. Sunflower and maize seeds were treated before planting with eight treatments, including ethoprophos, oxamyl, tolclofos-methyl + thiram, and various mixtures of these compounds at full and half doses, in addition to an untreated control. The percentage of empty holes caused by crow feeding was recorded after planting until complete germination, and reduction percentages were calculated relative to the control treatment. Meritan ® (2 g/kg) and the Viva ® + Rizolex-T ® (2 ml+ 3 g/kg) combination provided the highest level of protection, reducing empty holes by up to 81.21% in sunflower and 78.89% in maize. Viva ® alone or in mixtures provided moderate deterrence, whereas Rizolex-T ® alone showed minimal effect in reducing hooded crow feeding activity. These results indicate that insecticidal seed treatments, particularly organophosphate and carbamate chemicals, can significantly reduce early-season seed loss caused by hooded crows, whereas fungicidal treatment alone is ineffective in reducing seed predation by the hooded crow. This effect may be associated with post-ingestive effects reported in previous studies. Thus, the study supports the beneficial effects of chemical seed treatments in protecting sunflower and maize throughout the susceptible seed-to-seedling period. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Plant sciences Biological sciences/Zoology Bird repellents Seed predation Crop damage Helianthus annuus L. Zea mays L 1. Introduction Crop losses caused by birds represent a serious and costly problem for farmers 1 . In Egypt, the hooded crow ( Corvus cornix ) caused yield losses between 3.01% and 3.16% 2 . The amount of loss varies significantly based on the crop, region, and year 3 . The hooded crow ( Corvus cornix ) is regarded as one of the most economically important vertebrate pests in agricultural lands, particularly in newly reclaimed ones, and it causes damage to various crops by feeding on seeds during the sowing stage 4, 5, 6 . Chemical repellents are classified as primary or secondary based on their mode of action and impact on target species. Primary repellents are produced from natural sources and function by irritating animals' sensory systems, causing rapid avoidance. Secondary repellents, on the other hand, cause gastrointestinal distress, leading in a learned aversion to certain illness-associated information 7, 8. Additionally, many secondary repellents are derivatives of synthetic agricultural pesticides 9, 10 . Despite previous studies on chemical repellents, limited field-based evidence is available regarding the comparative effectiveness of insecticidal and fungicidal seed treatments in reducing bird-induced seed predation under Egyptian conditions, particularly in newly reclaimed soils. Therefore, the current study was carried out to investigate the efficacy of certain insecticidal and fungicidal seed treatments, individually and in combination, in reducing early-season seed predation caused by the hooded crow ( Corvus cornix ) on sunflower and maize during the 2024 summer season. 2. Materials and methods 2.1. Location and Experimental Design The investigation was conducted during the 2024 summer growing season at the experimental farm of Nubaria Agricultural Research Station (30.95° N, 29.90° E), Beheira Governorate, Egypt. The objective was to study the efficacy of two insecticides, a fungicide, and their mixture in reducing the hooded crow ( Corvus cornix ) away from the two seed crops, Sunflower ( Helianthus annuus L.) and Maize ( Zea mays L.), which were planted separately on May 1 st and 3 rd , respectively, in a Randomized Complete Block Design (RCBD) with three replicates. The investigated area for each crop was separated into 24 plots, each size 42 m 2 (6 × 7 m). The experimental plot consisted of 10 rows, each 7 m long and 60 cm apart, with 30 cm spacing between plants. 2.1.1. Plant materials The maize ( Zea mays L.) and sunflower ( Helianthus annuus L.) cultivars used in this study were commercial cultivars widely grown under Egyptian field conditions. The maize variety was the single-cross hybrid Giza 168, while the sunflower variety was cv. 601. Both cultivars are well known for their wide adaptability and high productivity and are commonly cultivated across different agricultural regions in Egypt. Seeds were obtained from certified local suppliers to ensure genetic purity and quality. 2.2. Seed treatment s Before planting, the seeds of Sunflower ( Helianthus annuus L.) and Maize ( Zea mays L.) were treated with the following potential repellent treatments: The selected rates were based on recommended agricultural practices and preliminary trials. 1- Seeds treated with Ethoprophos (Meritan ® 10% GR) at a rate of 2 g/ Kg seeds. 2- Seeds treated with Oxamyl (Viva ® 24% SL) at a rate of 2 ml/ Kg seeds. 3- Seeds treated with tolclofos-methyl + thiram (Rizolex-T ® 50% WP) at a rate of 3g/ Kg seeds. 4- Seeds treated with a mixture of Ethoprophos (Meritan ® 10% GR) and tolclofos-methyl + thiram (Rizolex-T ® 50% WP) at the full recommended dose of each compound/ Kg seeds. 5- Seeds treated with a mixture of Oxamyl (Viva ® 24% SL) and tolclofos-methyl + thiram (Rizolex-T ® 50% WP) at the full recommended dose of each compound/ Kg seeds. 6- Seeds treated with a mixture of Ethoprophos (Meritan ® 10% GR) and tolclofos-methyl + thiram (Rizolex-T ® 50% WP) at half the recommended dose of each compound / Kg seeds. 7- Seeds treated with a mixture of Oxamyl (Viva ® 24% SL) and tolclofos-methyl + thiram (Rizolex-T ® 50% WP) at half the recommended dose of each compound/ Kg seeds. 8- Untreated control Seeds of sunflower ( Helianthus annuus L.) and maize ( Zea mays L.) were treated by thoroughly mixing the required amount of each tested compound with the seeds in polyethylene bags . The granular formulation was finely crushed before mixing with seeds to ensure uniform coating. A 3 ml solution of Arabic gum (1%) was added as a sticker to ensure proper adhesion of the compounds to the seed surface. The mixture was then shaken manually for 10 minutes to achieve uniform coating of the seeds. After treatment, the seeds were air-dried under shade before sowing. 2.3. Sampling technique and data collection 2.3.1. Percentage of empty holes due to the hooded crow feeding Thirty planting holes per plot were randomly selected and inspected in each experimental plot after seed treatment and continuing until complete germination. This sampling size was considered adequate to represent field variability. All empty holes resulting from hooded crow ( Corvus cornix ) feeding were recorded, and the percentage of empty holes was calculated using the following formula 6 . Empty holes (%) = (Number of empty holes/ Total number of inspected planting holes) × 100 2.3.2. Reduction percentage of empty holes due to the hooded crow feeding After the planting stage, the holes were examined, and the empty ones were determined in each plot from the moment of planting till the appearance of seedlings. The percentage reduction in empty holes due to repellent treatments was computed as follows 6, 11 : Reduction % = ((Total number of empty holes in the control ˗ Total number of empty holes in the treatment) / Total number of empty holes in the control) × 100. 2.4. Statistical analysis Data were analyzed using one-way ANOVA and the ''F'' test. To compare the means of the various treatments, a computer program used to calculate the least significant differences (LSD) at the 0.05 level 12 , and means were also compared using Duncan's Multiple Range Test 13 . 3. Results The results demonstrate significant differences in the efficacy of the tested repellent treatments (Meritan, Viva, and Rizolex-T) and their mixtures in protecting sunflower and maize seeds from seed predation caused by the hooded crow. 3.1. Efficacy of repellent treatments on sunflower seeds The results in Table (1) showed that Meritan ® alone, as well as the mixture Viva ® + Rizolex-T ® (2 ml + 3 g/kg) achieved the lowest number of empty holes (2.33 and 2.00 holes/30 seeds, respectively) and the highest percentages of intact seeds (92.22% and 93.33%, respectively), with no significant differences. A second group of treatments, including Viva ® alone, Meritan ® + Rizolex-T ® (2 + 3 g), Meritan ® + Rizolex-T ® (1 + 1.5 g), and Viva ® + Rizolex-T ® (1 ml + 1.5 g), exhibited moderate repellency, with 3.33, 3.33, 3.33, and 3.00 empty holes per 30 seeds, and 88.89%, 88.89%, 88.89%, and 90.00% intact seeds, respectively. These treatments showed no significant differences among themselves, confirming their similar level of protection. In contrast, Rizolex-T ® alone exhibited significantly lower repellency, reflected by a higher number of empty holes and a reduced proportion of intact seeds, indicating its limited effectiveness as a seed protectant compared with the other treatments. The untreated control showed the highest rate of seed predation (10.67 empty holes/30 seeds) and the lowest percentage of intact seeds (64.44%), indicating the severity of hooded crow damage in the absence of repellent. 3.2. Efficacy of repellent treatments on maize seeds A similar trend was observed in maize. The treatments Meritan ® (2 g/kg) gave the lowest numbers of empty holes (2.00 holes/30 seeds) and the highest percentage of intact seeds (93.33%) with significant difference compared to the untreated control. The mixtures Viva ® + Rizolex-T ® (2 ml + 3 g/kg), Meritan ® + Rizolex-T ® (2 + 3 g), Meritan ® + Rizolex-T ® (1 + 1.5 g), and Viva ® + Rizolex-T ® (1 ml + 1.5 g) also demonstrated moderate repellency, producing 3.33, 3.33, 3.33 and 3.67 empty holes per 30 seeds and intact seed percentages of 88.89%, 88.89%, 87.78%, and 90%, respectively with no significant differences. Furthermore, Rizolex-T ® alone provided much less protection, with 6.00 empty holes per 30 seeds and only 80.00% intact seeds, leaving it in the lowest efficacy category (b/c significance groups). The untreated control again recorded the highest level of damage (9.33 empty holes) and the lowest proportion of intact seeds (68.89%), demonstrating the impact of hooded crow feeding when no repellent is applied. These results suggest that Meritan ® and Viva ® + Rizolex-T ® treatments can be recommended as practical seed protection measures in fields prone to hooded crow predation. Table 1. Efficiency of Meritan, Viva, Rizolex-T, and their mixtures as repellents against the hooded crow ( Corvus cornix ) on sunflower and maize. 3.3. Reduction percentage in empty seed holes due to repellent treatments Results in Table (2) presented the percentage reduction in empty seed holes for sunflower and maize after planting, following the application of different chemical repellent treatments against the hooded crow ( Corvus cornix ). These reductions reflect the relative effectiveness of each treatment in minimizing seed predation compared with the untreated control. The results showed that Meritan ® 10% GR (2 g/kg) exhibited one of the highest repellency levels for both crops. It reduced seed predation by 78.18% in sunflower and 78.89% in maize, corresponding to the lowest mean number of empty holes (2.33 and 2.00 holes/30 sown seeds, respectively), confirming its strong deterrent effect on the birds. The mixture Viva ® + Rizolex-T ® at 2 ml+ 3 g/kg achieved the highest reduction in sunflower, reaching 81.21%, while maintaining a comparatively strong reduction of 68.15% in maize. The very low hole count in sunflower (2.00 holes/30 seeds) places this mixture alongside Meritan ® as one of the most efficient repellents for this crop. In contrast, Viva ® 24% SL alone (2 ml/kg) showed moderate efficacy, with 68.79% reduction in sunflower and 68.15% in maize, reflected by slightly higher numbers of empty holes compared with the top-performing treatments. All mixture treatments containing Meritan ® or Viva ® with Rizolex-T ® (1 ml+ 1.5 g/kg or 2 ml + 3 g/kg) also produced moderate reductions ranging between 64.81% and 71.82% in sunflower and 61.48% to 68.15% in maize, indicating no significant differences among them and confirming their comparable protective ability. On the other hand, Rizolex-T ® alone (3 g/kg) was the least effective repellent. It achieved only 28.18% reduction in sunflower and 35.93% in maize, with much higher numbers of empty holes (7.67 and 6.00 holes/30 seeds). These results clearly distinguish it from the more effective treatments and demonstrate its limited ability to deter crow feeding when used alone. As expected, the untreated control exhibited the highest number of empty holes (10.67 in sunflower and 9.33 in maize), corresponding to 0% reduction, highlighting the severity of seed predation by hooded crows in the absence of protective treatments. Overall, the data indicate that Meritan ® and the mixture Viva ® + Rizolex-T ® (2 ml + 3 g/kg) provide the strongest protection, while Viva ® alone and the mixture treatments offer moderate but consistent repellency. Rizolex-T ® alone remains significantly less effective for both sunflower and maize. Table 2 . Reduction percentage in empty holes of summer crops due to three repellent treatments (Meritan, Viva, and Rizolex-T) and their mixtures to the hooded crow ( Corvus cornix ). Treatment Rate/ Kg seeds Sunflower ( Helianthus annuus L.) Maize ( Zea mays L.) Mean No. of empty holes after planting stage Reduction % Mean number of empty holes/30 sown holes Reduction % Meritan ® 10% GR 2 g 2.33 d 78.18 a 2.00 d 78.89 a Viva ® 24% SL 2 ml 3.33 c 68.79 b 3.00 c 68.15 b Rizolex-T ® 50% WP 3 g 7.67 b 28.18 c 6.00 b 35.93 c Meritan ® 10% GR + Rizolex-T ® 50% WP 2 + 3 g 3.33 c 68.79 b 3.33 c 64.81 b Viva ® 24% SL + Rizolex-T ® 50% WP 2 ml + 3 g/kg 2.00 d 81.21 a 3.00 c 68.15 b Meritan ® 10% GR + Rizolex-T ® 50% WP 1 + 1.5 g 3.33 c 68.79 b 3.33 c 64.81 b Viva ® 24% SL + Rizolex-T ® 50% WP 1 ml + 1.5 g 3.00 c 71.82 b 3.67 c 61.48 b Untreated control - 10.67 a 0.00 d 9.33 a 0.00 d LSD0.05 0.60 4.75 0.86 10.54 * At the 0.05 level, there is no significant difference between the means in each column labeled by the same letter (s). 4. Discussion The results of this study demonstrate that insecticidal seed treatments based on organophosphate (ethoprophos, Meritan®) and carbamate (oxamyl, Viva®) compounds, applied alone or in combination with a fungicidal treatment (tolclofos-methyl + thiram, Rizolex-T®), significantly reduced seed predation by the hooded crow ( Corvus cornix ) in both sunflower and maize under field conditions. These findings provide field-based evidence that certain insecticidal seed treatments can contribute not only to pest control but also to reducing vertebrate-induced crop losses during the early establishment stage 8 , 14 . The Meritan® treatment and the Viva® + Rizolex-T® mixture resulted in a significant reduction in empty seed holes, indicating that these treatments effectively deterred birds during the sensitive seed-to-seedling establishment period. This period is particularly vulnerable to bird damage, and even moderate reductions in seed loss can translate into improved crop establishment and potential yield stability under field conditions 2 , 6 . Similar findings have been reported by Linz 14 , who demonstrated that certain pesticide compounds may indirectly reduce bird feeding behavior in treated crops. Although organophosphates are not intended as repellents, their after-ingestion effects can cause secondary avoidance in birds, leading to conditioned aversion following sublethal exposure 14 , 15 . Carbamate insecticides, such as oxamyl, could lead to mild stomach pain, reducing consumption in repeated encounters 8 , 16 . Such secondary repellency mechanisms are particularly important in agricultural systems where immediate sensory deterrence is absent 8 , 17 . In contrast, fungicidal seed treatments alone (tolclofos-methyl + thiram) showed limited effectiveness in reducing seed predation. This suggests that fungicides lacking sensory or post-ingestive deterrent properties are insufficient to prevent bird damage under field conditions 2 , 6 , 18 . Similar observations have been reported in studies evaluating fungicide-based treatments against granivorous birds, where repellency was inconsistent or negligible 18 . The absence of significant sensory deterrent indicators that birds utilize to avoid feeding (taste/odor) may explain the relatively reduced efficacy of fungicidal seed treatments, as fungicides generally lack strong gustatory or olfactory deterrent cues that trigger avoidance in gran-eating birds 2 , 6 . Hooded crows are behaviorally adaptable and rapidly exploit newly planted fields, which intensifies seed predation pressure 2 , 6 . According to recent reviews, many chemical repellents that lack such sensory components are inconsistent or largely ineffective in preventing bird seed predation in crop systems, emphasizing the need for specific deterrent compounds or combinations that produce aversive signals to grain-eating birds 8 . Other fungicidal chemicals, such as Captan and Bayfidan, have exhibited varying repellency effects depending on bird species and crop, indicating that fungicides alone may not provide enough defenses against avian predation 18 . Furthermore, recent seed coating research emphasizes that combining sensory deterrents with seed protectants can significantly reduce bird seed predation, supporting the notion that fungicidal treatments lacking such features are insufficient on their own 17 . These findings provide one of the few field-based evaluations of insecticidal seed treatments against vertebrate pests under Egyptian agroecosystem conditions. However, the study was limited to a single season and location, and further multi-location and multi-season studies are recommended to validate these findings under diverse environmental conditions. In conclusion, the study supports the use of insecticide-based seed treatments, particularly those containing organophosphates or carbamates, to prevent early-season seed predation by hooded crows. Overall, the data point out the benefits of including insecticidal seed treatments into long-term bird management strategies, particularly in susceptible newly reclaimed agricultural areas. 5. Conclusion The results of this study clearly show that insecticidal seed treatments, especially ethoprophos and oxamyl, effectively reduce early-season seed predation by hooded crows (Corvus cornix) in sunflower and maize under field conditions. Meritan® and the Viva® + Rizolex-T® mixture consistently achieved the highest reduction in empty seed holes, demonstrating their strong protective efficacy during the critical seed-to-seedling establishment period. Tolclofos-methyl + thiram alone showed limited repellency under the tested conditions, likely due to the absence of strong sensory or post-ingestive deterrent effects reported for avian species. Overall, these findings highlight the potential integration of insecticidal seed treatments into bird management strategies, particularly in newly reclaimed agricultural areas and similar agro ecosystems. Declarations Author Contributions All authors contributed equally to this manuscript and thoroughly reviewed it prior to publication. Declaration of Competing Interest The authors certify that they have no known competing financial interests or personal relationships that could have appeared to influence the work described in this publication. Funding There is no outside funding. Ethics approval and consent to participate The authors don't conduct any human or animal experiments for this publication. References Issa, M.A. and El-Bakhshawngi, M.I.A. (2018).An estimation of bird damages on some fields, vegetable and fruit crops at Sharkia Governorate, Egypt. Zagazig J. Agric. Res., 45(4), 1273-1281. https://dx.doi.org/10.21608/zjar.2018.48571 Ahmed, E.A.A. (2013). Estimation of maize damage caused by Corvus cornix sardonius in Sheben Al - kom Menofiya governorate. Egypt. Acad. J. Biolog. Sci., 4(2), 11-17. https://doi.org/10.21608/eajbsh.2013.16998 Kandil, R.S., Mansour, M.R.K., Abdelrahem, F.M. and Dabour, N.A. (2023). Impact of fall armyworm Spodoptera frugiperda on maize yield and economic assessment of losses under different insecticidal sequences. Env. Biodiv. Soil Security, 7, 133-140. https://doi.org/10.21608/jenvbs.2023.208202.1217 Wilson, B.M. (1993). Integrated approaches for population management of harmful birds in agriculture areas of Egypt. 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Microplastic uptake by birds: from observation to development of a novel seed coating to prevent bird predation of corn seeds. Environ. Sci. Pollut. Res., 32, 6153–6160. https://doi.org/10.1007/s11356-025-36115-x Barakat, N.M., Hamdy, M.M. and El-Gendy, A.A. (2025). Repellent effect of Captan 50% WP and Bayfidan 25% EC fungicides against House Sparrow bird, passer Domesticus niloticus (L.) under laboratory and field conditions. Menoufia Journal of Plant Protection , 10(1), 13-19. https://doi.org/10.21608/mjapam.2025.352258.1045 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9247348","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":618133752,"identity":"e017c585-d6cd-4e4f-a549-7056a25746d3","order_by":0,"name":"Ragab Sebaita Kandil","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYDCCAxAqgb0BzLZhYJAgVgsPkHHgAEMaiVqAnMOEtfDdPsD24ccvuzwe6TOGhz/8OZ/YP7v54AOGGptoXFokzyUwz+ztSy7m4csxOHCw7XbijDvHkg0YjqXlNuDQYnCGgZmBt4c5cT8PD1BLw+3Ehhs5ZhKMDYfxamH821Of2APScuDPucT5xGhh5vlxGKqF7UDiBkJaJEFaZBuOF/PwsBUcONuWbLzxRlqyQQIev/CBHPbmT3UeDw/z5g8Vf+xk591IPvjgQ40NTi0MDPwfGBjbEFxHsMoEnMph4A+CaU9Q8SgYBaNgFIw4AACw2GOHQXYwiAAAAABJRU5ErkJggg==","orcid":"","institution":"Agricultural Research Center","correspondingAuthor":true,"prefix":"","firstName":"Ragab","middleName":"Sebaita","lastName":"Kandil","suffix":""},{"id":618133753,"identity":"22651b7b-00b3-4bd7-97ac-534a9d2ccd50","order_by":1,"name":"Gihan Hamza Ismail","email":"","orcid":"","institution":"Agricultural Research Center","correspondingAuthor":false,"prefix":"","firstName":"Gihan","middleName":"Hamza","lastName":"Ismail","suffix":""}],"badges":[],"createdAt":"2026-03-27 17:39:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9247348/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9247348/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107358210,"identity":"b5b81408-3c98-4f8a-bda8-0d744601299b","added_by":"auto","created_at":"2026-04-20 17:25:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":828974,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9247348/v1/360a9730-3dd9-45eb-aa15-bf414e24515b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effectiveness of insecticidal and fungicidal seed treatments in reducing hooded crow (Corvus cornix) predation on sunflower and maize seeds under field conditions","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCrop losses caused by birds represent a serious and costly problem\u0026nbsp;for farmers \u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e. In Egypt, the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e) caused yield losses between 3.01% and 3.16% \u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e. The amount of loss varies significantly based on the crop, region, and year \u003cstrong\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e. The hooded crow (\u003cem\u003eCorvus\u003c/em\u003e \u003cem\u003ecornix\u003c/em\u003e) is regarded as one of the most economically important vertebrate pests in agricultural lands, particularly in newly reclaimed ones, and it causes damage to various crops by feeding on seeds during the sowing stage \u003cstrong\u003e\u003csup\u003e4, 5, 6\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eChemical repellents are classified as primary or secondary based on their mode of action and impact on target species. Primary repellents are produced from natural sources and function by irritating animals' sensory systems, causing rapid avoidance. Secondary repellents, on the other hand, cause gastrointestinal distress, leading in a learned aversion to certain illness-associated information \u003cstrong\u003e\u003csup\u003e7, 8.\u003c/sup\u003e\u003c/strong\u003e Additionally, many secondary repellents are derivatives of synthetic agricultural pesticides \u003cstrong\u003e\u003csup\u003e9, 10\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite previous studies on chemical repellents, limited field-based evidence is available regarding the comparative effectiveness of insecticidal and fungicidal seed treatments in reducing bird-induced seed predation under Egyptian conditions, particularly in newly reclaimed soils.\u0026nbsp;Therefore, the current study was carried out to investigate the efficacy of certain insecticidal and fungicidal seed treatments, individually and in combination, in reducing early-season seed predation caused by the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e) on sunflower and maize during the 2024 summer season.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e2.1. Location and Experimental Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe investigation was conducted during the 2024 summer growing season at the experimental farm of Nubaria Agricultural Research Station (30.95\u0026deg; N, 29.90\u0026deg; E), Beheira Governorate, Egypt. The objective was to study the efficacy of two insecticides, a fungicide, and their mixture in reducing the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e) away from the two seed crops, Sunflower (\u003cem\u003eHelianthus annuus\u003c/em\u003e L.) and Maize (\u003cem\u003eZea mays\u003c/em\u003e L.), which were planted separately on May 1\u003csup\u003est\u0026nbsp;\u003c/sup\u003eand 3\u003csup\u003erd\u003c/sup\u003e, respectively, in a Randomized Complete Block Design (RCBD) with three replicates. The investigated area for each crop was separated into 24 plots, each size 42 m\u003csup\u003e2\u003c/sup\u003e (6 \u0026times; 7 m). The experimental plot consisted of 10 rows, each 7 m long and 60 cm apart, with 30 cm spacing between plants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.1. Plant materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe maize (\u003cem\u003eZea mays\u003c/em\u003e L.) and sunflower (\u003cem\u003eHelianthus annuus\u003c/em\u003e L.) cultivars used in this study were commercial cultivars widely grown under Egyptian field conditions. The maize variety was the single-cross hybrid Giza 168, while the sunflower variety was cv. 601. Both cultivars are well known for their wide adaptability and high productivity and are commonly cultivated across different agricultural regions in Egypt. Seeds were obtained from certified local suppliers to ensure genetic purity and quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Seed treatment\u003c/strong\u003es\u003c/p\u003e\n\u003cp\u003eBefore planting, the seeds of Sunflower (\u003cem\u003eHelianthus annuus\u003c/em\u003e L.) and Maize (\u003cem\u003eZea mays\u003c/em\u003e L.) were treated with the following potential\u003cu\u003e\u0026nbsp;\u003c/u\u003erepellent treatments:\u003cu\u003e\u0026nbsp;\u003c/u\u003eThe selected rates were based on recommended agricultural practices and preliminary trials.\u003c/p\u003e\n\u003cp\u003e1-\u0026nbsp; \u0026nbsp;Seeds treated with Ethoprophos (Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e 10% GR) at a rate of \u003cspan dir=\"RTL\"\u003e2\u003c/span\u003e g/ Kg seeds.\u003c/p\u003e\n\u003cp\u003e2-\u0026nbsp; \u0026nbsp;Seeds treated with Oxamyl (Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e 24% SL) at a rate of \u003cspan dir=\"RTL\"\u003e2\u003c/span\u003e ml/ Kg seeds.\u003c/p\u003e\n\u003cp\u003e3-\u0026nbsp; \u0026nbsp;Seeds treated with tolclofos-methyl + thiram (Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP) at a rate of 3g/ Kg seeds.\u003c/p\u003e\n\u003cp\u003e4-\u0026nbsp; \u0026nbsp;Seeds treated with a mixture of Ethoprophos (Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e 10% GR) and tolclofos-methyl + thiram (Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP) at the full recommended dose of each compound/ Kg seeds.\u003c/p\u003e\n\u003cp\u003e5-\u0026nbsp; \u0026nbsp;Seeds treated with a mixture of Oxamyl (Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e 24% SL) and tolclofos-methyl + thiram (Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP) at the full recommended dose of each compound/ Kg seeds.\u003c/p\u003e\n\u003cp\u003e6-\u0026nbsp; \u0026nbsp;Seeds treated with a mixture of Ethoprophos (Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e 10% GR) and tolclofos-methyl + thiram (Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP) at half the recommended dose of each compound / Kg seeds.\u003c/p\u003e\n\u003cp\u003e7- Seeds treated with a mixture of Oxamyl (Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e 24% SL) and tolclofos-methyl +\u0026nbsp;thiram\u0026nbsp;(Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP) at half the recommended dose of each compound/ Kg seeds.\u003c/p\u003e\n\u003cp\u003e8- \u0026nbsp; Untreated control\u003c/p\u003e\n\u003cp\u003eSeeds of sunflower (\u003cem\u003eHelianthus annuus\u003c/em\u003e L.) and maize (\u003cem\u003eZea mays\u003c/em\u003e L.) were treated by thoroughly mixing the required amount of each tested compound with the seeds in polyethylene bags\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThe granular formulation was finely crushed before mixing with seeds to ensure uniform coating. A 3 ml solution of Arabic gum (1%) was added as a sticker to ensure proper adhesion of the compounds to the seed surface. The mixture was then shaken manually for 10 minutes to achieve uniform coating of the seeds. After treatment, the seeds were air-dried under shade before sowing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Sampling technique and data\u003c/strong\u003e \u003cstrong\u003ecollection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.1. Percentage of empty holes due to the hooded crow feeding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThirty planting holes per plot were randomly selected and inspected in each experimental plot after seed treatment and continuing until complete germination. This sampling size was considered adequate to represent field variability.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eAll empty holes resulting from hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e) feeding were recorded, and the percentage of empty holes was calculated using the following formula \u003cstrong\u003e\u003csup\u003e6\u003c/sup\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmpty holes (%) = (Number of empty holes/ Total number of inspected\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eplanting holes) \u0026times; 100\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.2. Reduction percentage of empty holes due to the hooded crow feeding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the planting stage, the holes were examined, and the empty ones were determined in each plot from the moment of planting till the appearance of seedlings. The percentage reduction in empty holes due to repellent treatments was computed as follows \u003cstrong\u003e\u003csup\u003e6, 11\u003c/sup\u003e\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eReduction % = ((Total number of empty holes in the control ˗ Total number of empty holes in the treatment) / Total number of empty holes in the control) \u0026times; 100.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using one-way ANOVA and the \u0026apos;\u0026apos;F\u0026apos;\u0026apos; test. To compare the means of the various treatments, a computer program used to calculate the least significant differences (LSD) at the 0.05 level \u003cstrong\u003e\u003csup\u003e12\u003c/sup\u003e\u003c/strong\u003e, and means were also compared using Duncan\u0026apos;s Multiple Range Test \u003cstrong\u003e\u003csup\u003e13\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe results demonstrate significant differences in the efficacy of the tested repellent treatments (Meritan, Viva, and Rizolex-T) and their mixtures in protecting sunflower and maize seeds from seed predation caused by the hooded crow.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1. Efficacy of repellent treatments on sunflower seeds\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results in \u003cstrong\u003eTable (1)\u003c/strong\u003e showed that Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e alone, as well as\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003ethe mixture Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u0026nbsp;\u003c/sup\u003e(2 ml + 3 g/kg) achieved the lowest number of empty holes (2.33 and 2.00 holes/30 seeds, respectively) and the highest percentages of intact seeds (92.22% and 93.33%, respectively), with no significant differences. A second group of treatments, including Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e alone, Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (2 + 3 g), Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (1 + 1.5 g), and Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (1 ml + 1.5 g), exhibited moderate repellency, with 3.33, 3.33, 3.33, and 3.00 empty holes per 30 seeds, and 88.89%, 88.89%, 88.89%, and 90.00% intact seeds, respectively. These treatments showed no significant differences among themselves, confirming their similar level of protection. In contrast, Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e alone exhibited significantly lower repellency, reflected by a higher number of empty holes and a reduced proportion of intact seeds, indicating its limited effectiveness as a seed protectant compared with the other treatments. The untreated control showed the highest rate of seed predation (10.67 empty holes/30 seeds) and the lowest percentage of intact seeds (64.44%), indicating the severity of hooded crow damage in the absence of repellent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Efficacy of repellent treatments on maize seeds\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA similar trend was observed in maize. The treatments Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e (2 g/kg) gave the lowest numbers of empty holes (2.00 holes/30 seeds) and the highest percentage of intact seeds (93.33%) with significant difference compared to the untreated control. The mixtures Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (2 ml + 3 g/kg), Meritan\u003csup\u003e\u0026reg;\u0026nbsp;\u003c/sup\u003e+ Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (2 + 3 g), Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (1 + 1.5 g), and Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (1 ml + 1.5 g) also demonstrated moderate repellency, producing 3.33, 3.33, 3.33 and 3.67 empty holes per 30 seeds and intact seed percentages of 88.89%, 88.89%, 87.78%, and 90%, respectively with no significant differences. Furthermore, Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e alone provided much less protection, with 6.00 empty holes per 30 seeds and only 80.00% intact seeds, leaving it in the lowest efficacy category (b/c significance groups). The untreated control again recorded the highest level of damage (9.33 empty holes) and the lowest proportion of intact seeds (68.89%), demonstrating the impact of hooded crow feeding when no repellent is applied. These results suggest that Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e and Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e treatments can be recommended as practical seed protection measures in fields prone to hooded crow predation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Efficiency of Meritan, Viva, Rizolex-T, and their mixtures as repellents against the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e) on sunflower and maize.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Reduction percentage\u003c/strong\u003e \u003cstrong\u003ein empty seed holes due to repellent treatments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults in \u003cstrong\u003eTable (2)\u0026nbsp;\u003c/strong\u003epresented the percentage reduction in empty seed holes for sunflower and maize after planting, following the application of different chemical repellent treatments against the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e). These reductions reflect the relative effectiveness of each treatment in minimizing seed predation compared with the untreated control. The results showed that Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e 10% GR (2 g/kg) exhibited one of the highest repellency levels for both crops. It reduced seed predation by 78.18% in sunflower and 78.89% in maize, corresponding to the lowest mean number of empty holes (2.33 and 2.00 holes/30 sown seeds, respectively), confirming its strong deterrent effect on the birds. The mixture Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e at 2 ml+ 3 g/kg achieved the highest reduction in sunflower, reaching 81.21%, while maintaining a comparatively strong reduction of 68.15% in maize. The very low hole count in sunflower (2.00 holes/30 seeds) places this mixture alongside Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e as one of the most efficient repellents for this crop.\u003c/p\u003e\n\u003cp\u003eIn contrast, Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e 24% SL alone (2 ml/kg) showed moderate efficacy, with 68.79% reduction in sunflower and 68.15% in maize, reflected by slightly higher numbers of empty holes compared with the top-performing treatments. All mixture treatments containing Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e or Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e with Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (1 ml+ 1.5 g/kg or 2 ml + 3 g/kg) also produced moderate reductions ranging between 64.81% and 71.82% in sunflower and 61.48% to 68.15% in maize, indicating no significant differences among them and confirming their comparable protective ability. On the other hand, Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e alone (3 g/kg) was the least effective repellent. It achieved only 28.18% reduction in sunflower and 35.93% in maize, with much higher numbers of empty holes (7.67 and 6.00 holes/30 seeds). These results clearly distinguish it from the more effective treatments and demonstrate its limited ability to deter crow feeding when used alone. As expected, the untreated control exhibited the highest number of empty holes (10.67 in sunflower and 9.33 in maize), corresponding to 0% reduction, highlighting the severity of seed predation by hooded crows in the absence of protective treatments. Overall, the data indicate that Meritan\u003csup\u003e\u0026reg;\u003c/sup\u003e and the mixture Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e (2 ml + 3 g/kg) provide the strongest protection, while Viva\u003csup\u003e\u0026reg;\u003c/sup\u003e alone and the mixture treatments offer moderate but consistent repellency. Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e alone remains significantly less effective for both sunflower and maize.\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"755\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 755px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable \u003cspan dir=\"RTL\"\u003e2\u003c/span\u003e. Reduction percentage in empty holes of summer crops due to three repellent treatments (Meritan, Viva, and Rizolex-T) and their mixtures to the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e).\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRate/\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eKg seeds\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 257px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSunflower (\u003cem\u003eHelianthus annuus\u003c/em\u003e L.)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaize (\u003cem\u003eZea mays\u003c/em\u003e L.)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean No. of empty holes after planting stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReduction %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean number of empty holes/30 sown holes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReduction %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeritan\u003csup\u003e\u0026reg;\u003c/sup\u003e 10% GR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.33\u003csup\u003ed\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e78.18\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.00\u003csup\u003ed\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e78.89\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViva\u003csup\u003e\u0026reg;\u003c/sup\u003e 24% SL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 ml\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.33\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.79\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.00\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.15\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3 g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.67\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.18\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.00\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35.93\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeritan\u003csup\u003e\u0026reg;\u003c/sup\u003e 10% GR + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 + 3 g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.33\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.79\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.33\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e64.81\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViva\u003csup\u003e\u0026reg;\u003c/sup\u003e 24% SL + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 ml + 3 g/kg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.00\u003csup\u003ed\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e81.21\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.00\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.15\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeritan\u003csup\u003e\u0026reg;\u003c/sup\u003e 10% GR + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 + 1.5 g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.33\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.79\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.33\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e64.81\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViva\u003csup\u003e\u0026reg;\u003c/sup\u003e 24% SL + Rizolex-T\u003csup\u003e\u0026reg;\u003c/sup\u003e 50% WP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 ml + 1.5 g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.00\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e71.82\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.67\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e61.48\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUntreated control\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.67\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00\u003csup\u003ed\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.33\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00\u003csup\u003ed\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 256px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLSD0.05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 19.4159%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 16.0622%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e* At the 0.05 level, there is no significant difference between the means in each column labeled by the same letter (s).\u003c/strong\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe results of this study demonstrate that insecticidal seed treatments based on organophosphate (ethoprophos, Meritan\u0026reg;) and carbamate (oxamyl, Viva\u0026reg;) compounds, applied alone or in combination with a fungicidal treatment (tolclofos-methyl\u0026thinsp;+\u0026thinsp;thiram, Rizolex-T\u0026reg;), significantly reduced seed predation by the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e) in both sunflower and maize under field conditions. These findings provide field-based evidence that certain insecticidal seed treatments can contribute not only to pest control but also to reducing vertebrate-induced crop losses during the early establishment stage \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The Meritan\u0026reg; treatment and the Viva\u0026reg; + Rizolex-T\u0026reg; mixture resulted in a significant reduction in empty seed holes, indicating that these treatments effectively deterred birds during the sensitive seed-to-seedling establishment period. This period is particularly vulnerable to bird damage, and even moderate reductions in seed loss can translate into improved crop establishment and potential yield stability under field conditions \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Similar findings have been reported by Linz \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e, who demonstrated that certain pesticide compounds may indirectly reduce bird feeding behavior in treated crops.\u003c/p\u003e \u003cp\u003eAlthough organophosphates are not intended as repellents, their after-ingestion effects can cause secondary avoidance in birds, leading to conditioned aversion following sublethal exposure \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Carbamate insecticides, such as oxamyl, could lead to mild stomach pain, reducing consumption in repeated encounters \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Such secondary repellency mechanisms are particularly important in agricultural systems where immediate sensory deterrence is absent \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast, fungicidal seed treatments alone (tolclofos-methyl\u0026thinsp;+\u0026thinsp;thiram) showed limited effectiveness in reducing seed predation. This suggests that fungicides lacking sensory or post-ingestive deterrent properties are insufficient to prevent bird damage under field conditions \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Similar observations have been reported in studies evaluating fungicide-based treatments against granivorous birds, where repellency was inconsistent or negligible \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe absence of significant sensory deterrent indicators that birds utilize to avoid feeding (taste/odor) may explain the relatively reduced efficacy of fungicidal seed treatments, as fungicides generally lack strong gustatory or olfactory deterrent cues that trigger avoidance in gran-eating birds \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Hooded crows are behaviorally adaptable and rapidly exploit newly planted fields, which intensifies seed predation pressure \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAccording to recent reviews, many chemical repellents that lack such sensory components are inconsistent or largely ineffective in preventing bird seed predation in crop systems, emphasizing the need for specific deterrent compounds or combinations that produce aversive signals to grain-eating birds \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Other fungicidal chemicals, such as Captan and Bayfidan, have exhibited varying repellency effects depending on bird species and crop, indicating that fungicides alone may not provide enough defenses against avian predation \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Furthermore, recent seed coating research emphasizes that combining sensory deterrents with seed protectants can significantly reduce bird seed predation, supporting the notion that fungicidal treatments lacking such features are insufficient on their own \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. These findings provide one of the few field-based evaluations of insecticidal seed treatments against vertebrate pests under Egyptian agroecosystem conditions. However, the study was limited to a single season and location, and further multi-location and multi-season studies are recommended to validate these findings under diverse environmental conditions. In conclusion, the study supports the use of insecticide-based seed treatments, particularly those containing organophosphates or carbamates, to prevent early-season seed predation by hooded crows. Overall, the data point out the benefits of including insecticidal seed treatments into long-term bird management strategies, particularly in susceptible newly reclaimed agricultural areas.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe results of this study clearly show that insecticidal seed treatments, especially ethoprophos and oxamyl, effectively reduce early-season seed predation by hooded crows (Corvus cornix) in sunflower and maize under field conditions. Meritan\u0026reg; and the Viva\u0026reg; + Rizolex-T\u0026reg; mixture consistently achieved the highest reduction in empty seed holes, demonstrating their strong protective efficacy during the critical seed-to-seedling establishment period. Tolclofos-methyl\u0026thinsp;+\u0026thinsp;thiram alone showed limited repellency under the tested conditions, likely due to the absence of strong sensory or post-ingestive deterrent effects reported for avian species. Overall, these findings highlight the potential integration of insecticidal seed treatments into bird management strategies, particularly in newly reclaimed agricultural areas and similar agro ecosystems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed equally to this manuscript and thoroughly reviewed it prior to publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors certify that they have no known competing financial interests or personal relationships that could have appeared to influence the work described in this publication.\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no outside funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors don't conduct any human or animal experiments for this publication.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eIssa, M.A. and El-Bakhshawngi, M.I.A. (2018).An estimation of bird damages on some fields, vegetable and fruit crops at Sharkia Governorate, Egypt. Zagazig J. Agric. Res., 45(4), 1273-1281. https://dx.doi.org/10.21608/zjar.2018.48571\u003c/li\u003e\n \u003cli\u003eAhmed, E.A.A. (2013). Estimation of maize damage caused by \u003cem\u003eCorvus cornix\u003c/em\u003e sardonius in Sheben Al\u003cspan dir=\"RTL\"\u003e-\u003c/span\u003ekom Menofiya governorate. Egypt. Acad. J. Biolog. Sci., 4(2), 11-17. https://doi.org/10.21608/eajbsh.2013.16998\u003c/li\u003e\n \u003cli\u003eKandil, R.S., Mansour, M.R.K., Abdelrahem, F.M. and Dabour, N.A. (2023). Impact of fall armyworm \u003cem\u003eSpodoptera frugiperda\u003c/em\u003e on maize yield and economic assessment of losses under different insecticidal sequences. Env. Biodiv. Soil Security, 7, 133-140. https://doi.org/10.21608/jenvbs.2023.208202.1217\u003c/li\u003e\n \u003cli\u003eWilson, B.M. (1993). Integrated approaches for population management of harmful birds in agriculture areas of Egypt. Ph.D. Thesis. Institute of Environmental Studies and Research, Ain Shams University, Egypt.\u003c/li\u003e\n \u003cli\u003eMetwally, A.M., Ahmed, M.A., Mahmoud, N.A. and Abdel El\u0026ndash;Aal, M.M. (2009). Field trails to evaluate damage caused by wild birds to contain field crops under different habitats at Assuit Governorate. Journal of Plant Protection and Pathology, 34(2), 1291-1300. \u003cu\u003ehttps://dx.doi.org/10.21608/jppp.2019.121980\u003c/u\u003e\u003c/li\u003e\n \u003cli\u003eKandil, R.S. and Ismail, G.H. (2024). Protecting agricultural crops from attacking of crested lark, \u003cem\u003eGalerida cristata\u003c/em\u003e (L.) using insecticide and fungicide repellents. International Journal of Entomology Res., 9(12), 59-63. https://www.entomologyjournals.com/assets/archives/2024/vol9issue12/9344.pdf\u003c/li\u003e\n \u003cli\u003eSayre, R.W. and Clark, L. (2001). Effect of primary and secondary repellents on European starlings: an initial assessment. Journal of Wildlife Management, 65(3), 461\u0026ndash;469. https://doi.org/10.2307/3803098\u003c/li\u003e\n \u003cli\u003eDeLiberto, S.T. and Werner, S.J. (2024). Applications of chemical bird repellents for crop and resource protection: a review and synthesis\u003cem\u003e.\u003c/em\u003e Wildlife Research, 51(2), WR23062. https://doi.org/10.1071/WR23062\u003c/li\u003e\n \u003cli\u003eIsmail, G.H. and Kandil, R.S. (2024). Joint effect of insecticide and fungicide poison baits against land snail, \u003cem\u003eEobania vermiculata\u003c/em\u003e under laboratory and field conditions. International Journal of Agriculture and Plant Science, 6(4), 41-45. https://www.agriculturejournal.in/assets/archives/2024/vol6issue4/6065.pdf\u003c/li\u003e\n \u003cli\u003eIbrahim, S.A.M., El-Nasharty, M.E.A. and kandil, R.S. (2024). Efficacy of some insecticides against white grub, \u003cem\u003ePentodon algerinum\u003c/em\u003e on sugar beet. J. of Plant Protection and Pathology, Mansoura Univ., 15(10), 305-309. https://jppp.journals.ekb.eg/article_384020_3545ba304d70b2590bed57e8a8426b1a.pdf\u003c/li\u003e\n \u003cli\u003eGuo, W., Yan, X., Zhao, G. and Han, R. (2013). Efficacy of \u003cem\u003eEntomopathogenic steinernema\u0026nbsp;\u003c/em\u003eand \u003cem\u003eheterorhabditis\u0026nbsp;\u003c/em\u003enematodes against white grubs (Coleoptera: Scarabaeidae) in peanut fields. Journal of Economic Entomol., 106(3), 1112-1117. \u003cu\u003ehttps://doi.org/10.1603/EC12477\u003c/u\u003e\u003c/li\u003e\n \u003cli\u003eCostat Software, 1988. Microcomputer Program Analysis. Co-Hort Software, Berkely, CA, USA.\u003c/li\u003e\n \u003cli\u003eDuncan, D.B., 1955. Multiple range and multiple, F-tests. International Biometric Society, 11(1), 1-42. \u003cu\u003ehttp://dx.doi.org/10.2307/3001478\u003c/u\u003e\u003c/li\u003e\n \u003cli\u003eLinz, G.M., Homan, H.J., Slowik, A.A. and Penry, L.B. (2006). Evaluation of registered pesticides as repellents for reducing blackbird (Icteridae) damage to sunflower. Crop Protection, 25(8), 842-847. https://doi.org/10.1016/j.cropro.2005.11.006\u003c/li\u003e\n \u003cli\u003eWalker, C. (2003). Neurotoxic pesticides and behavioural effects upon birds. Ecotoxicology, 12, 307\u0026ndash;316. https://doi.org/10.1023/A:1022523331343\u003c/li\u003e\n \u003cli\u003eFagerstone, K.A. and Schafer, E.W. (1998). Status of APHIS vertebrate pesticides and drugs. Proceedings of the Eighteenth Vertebrate Pest Conference, 18, 319-324. https://digitalcommons.unl.edu/vpc18/11\u003c/li\u003e\n \u003cli\u003eAccinelli, C., Bruno, V., Abbas, H.K., Morena C., Khambhati, V.H. and\u0026middot; Shier, W.T. (2025). Microplastic uptake by birds: from observation to development of a novel seed coating to prevent bird predation of corn seeds. Environ. Sci. Pollut. Res.,\u003cem\u003e\u0026nbsp;\u003c/em\u003e32, 6153\u0026ndash;6160. https://doi.org/10.1007/s11356-025-36115-x\u003c/li\u003e\n \u003cli\u003eBarakat, N.M., Hamdy, M.M. and El-Gendy, A.A. (2025). Repellent effect of Captan 50% WP and Bayfidan 25% EC fungicides against House Sparrow bird, passer \u003cem\u003eDomesticus niloticus\u003c/em\u003e (L.) under laboratory and field conditions.\u003cem\u003e\u0026nbsp;\u003c/em\u003eMenoufia Journal of Plant Protection\u003cem\u003e,\u0026nbsp;\u003c/em\u003e10(1), 13-19. https://doi.org/10.21608/mjapam.2025.352258.1045\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bird repellents, Seed predation, Crop damage, Helianthus annuus L., Zea mays L","lastPublishedDoi":"10.21203/rs.3.rs-9247348/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9247348/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe present study evaluated the effectiveness of two insecticidal seed treatments—ethoprophos (Meritan\u003csup\u003e®\u003c/sup\u003e 10% GR) and oxamyl (Viva\u003csup\u003e® \u003c/sup\u003e24% SL)—and a fungicide, tolclofos-methyl + thiram (Rizolex-T\u003csup\u003e®\u003c/sup\u003e 50% WP), as seed treatments, alone or in combination, in reducing seed predation caused by the hooded crow (\u003cem\u003eCorvus cornix\u003c/em\u003e) on sunflower (\u003cem\u003eHelianthus annuus \u003c/em\u003eL.) and maize (\u003cem\u003eZea mays \u003c/em\u003eL.) during the summer season of 2024. The experiment was conducted at the Experimental Farm of Nubaria Agricultural Research Station, Behaira Governorate, Egypt, using a Randomized Complete Block Design (RCBD) with three replicates.\u003c/p\u003e\n\u003cp\u003eSunflower and maize seeds were treated before planting with eight treatments, including ethoprophos, oxamyl, tolclofos-methyl + thiram, and various mixtures of these compounds at full and half doses, in addition to an untreated control. The percentage of empty holes caused by crow feeding was recorded after planting until complete germination, and reduction percentages were calculated relative to the control treatment.\u003c/p\u003e\n\u003cp\u003eMeritan\u003csup\u003e®\u003c/sup\u003e (2 g/kg) and the Viva\u003csup\u003e®\u003c/sup\u003e + Rizolex-T\u003csup\u003e®\u003c/sup\u003e (2 ml+ 3 g/kg) combination provided the highest level of\u0026nbsp; protection, reducing empty holes by up to 81.21% in sunflower and 78.89% in maize. Viva\u003csup\u003e® \u003c/sup\u003ealone or in mixtures provided moderate deterrence, whereas Rizolex-T\u003csup\u003e®\u003c/sup\u003e alone showed minimal effect in reducing hooded crow feeding activity. These results indicate that insecticidal seed treatments, particularly organophosphate and carbamate chemicals, can significantly reduce early-season seed loss caused by hooded crows, whereas fungicidal treatment alone is ineffective in reducing seed predation by the hooded crow. This effect may be associated with post-ingestive effects reported in previous studies. Thus, the study supports the beneficial effects of chemical seed treatments in protecting sunflower and maize throughout the susceptible seed-to-seedling period.\u003c/p\u003e","manuscriptTitle":"Effectiveness of insecticidal and fungicidal seed treatments in reducing hooded crow (Corvus cornix) predation on sunflower and maize seeds under field conditions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 06:13:41","doi":"10.21203/rs.3.rs-9247348/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"42d77874-c815-45b2-a251-9055f48a0763","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":65774246,"name":"Biological sciences/Ecology"},{"id":65774247,"name":"Earth and environmental sciences/Ecology"},{"id":65774248,"name":"Biological sciences/Plant sciences"},{"id":65774249,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2026-04-20T17:24:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 06:13:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9247348","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9247348","identity":"rs-9247348","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}