Development and Field Testing of a Spatial Decision Support System to Control Populations of the European Cherry Fruit Fly, Rhagoletis cerasi, in Commercial Orchards

Ioannou, Charalampos S.; Papanastasiou, Stella A.; Zarpas, Kostas D.; Miranda, Miguel Ángel; Sciarretta, Andrea; Nestel, David; Papadopoulos, Nikos T.

doi:10.3390/agronomy9100568

Cited by 7 publications

(4 citation statements)

References 24 publications

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“…An SDSS, known as 'MedCila', was developed for medfly control in citrus orchards in Israel (Cohen, Cohen, Hetzroni, et al, 2008), resulted in reduction of 8% of spraying action . Additional decision support systems based on daily camera-trap data in different crop have been proved helpful in the management of fruit flies like the medfly (Sciarretta et al, 2018), the European Cherry Fruit Fly, Rhagoletis cerasi (Diptera: Tephritidae) (Ioannou et al, 2019), and the B. Oleae (Miranda et al, 2019). Developing of integrative approach that incorporate models of age-structured and flight activity within SDSS can not only contribute to the schedule of the optimal day for baited-spinosad treatment, but also to the schedule the optimal time of day.…”

Section: Discussionmentioning

confidence: 99%

Long‐term automatic trap data reveal factors affecting diurnal flight patterns of the Mediterranean Fruit fly

Goldshtein

Gazit²,

Hetzroni

et al. 2021

J Applied Entomology

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Mediterranean Fruit Fly (medfly), Ceratitis capitata (Wiedemann), is considered to be one of the most destructive fruit insect pests throughout the world. In recent years, the temporal dynamics of the medfly have been extensively studied by season, and, to a lesser extent, on a daily basis. We exploited, for the first time, a sequential automatic medfly male trapping system, in combination with climate data, to characterize diel flight patterns of male medflies trapped. The process was carried out in four commercial citrus fields over three growing seasons. Results showed that throughout the year, medfly flight activity began 4-6 hr after sunrise and peaked up to 2 to 3 hr before sunset. Generalized additive models (GAM) of the 934 days sampled revealed that in the fall, the diurnal flight activity was unimodal, that is, it began increasing at noon, peaking in the afternoon. By contrast, in the spring and summer, the diurnal flight activity exhibited a bimodal pattern, decreasing at midday. GAMs also revealed that hour after sunrise and temperature influenced medfly captures, with the former the more dominant factor. Thus, photophase significantly impacted the medfly's diurnal flight activity in each season. This study demonstrated that automatic traps that timestamp each capture are a primary research tool in insect flight activity studies that contributes to understanding diurnal insect activity within the growing season.

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Section: Discussionmentioning

confidence: 99%

Long‐term automatic trap data reveal factors affecting diurnal flight patterns of the Mediterranean Fruit fly

Goldshtein

Gazit²,

Hetzroni

et al. 2021

J Applied Entomology

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“…Ïëîäè, ùî ïîøêîäaeåí³ ëè÷èíêàìè ìóõè, âòðà÷àþòü áëèñê, ïëîäè ñòàþòü íå¿ñò³âíèìè, ì'ÿêîòü çàãíèâàº, ÷àñòèíà îïàäàº. Â äåÿê³ ðîêè öåé âèä ïîøêîäaeóº äî 80% ïëîä³â [3], ùî ï³äòâåðäaeóþòü ³ ìàòåð³àëè äîñë³äaeåíü çàðóá³aeíèõ â÷åíèõ [7][8].…”

Section: ìåòîäè ïîëüîâ³ â ïðîìèñëîâîìó ñàäó ÷åðåøí³ òà âèøí³ â óìîâàõ...unclassified

The efficacy of protection by modern insecticides in the industrial cherry plantations against cherry fruit fly pest

Yanovskyi

Suchanov

Krykunov

et al. 2023

qpp

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Goal. To investigate an efficacy of the insecticides Aktelik 500 ЕС, (pyrymyphos-methyl 500 g/l), Calipso 480 SС (thiacloprid, 480 g/l), Proclaim 50 SG (emamectyn benzoat, 50 g/ kg), Movento 100 SC (spirotetramate, 100 g/l), Exirel, СЕ (cyantraniliprole, 100 g/l) and bio products Actofit, EC (aversektyn С, 0.2%), bitoxybacilyn — BTU, (insecticide), (Bacillus thuringiensis. endospores, endotoxyn, exotoxyn) and Lepidocyd-BTU, (insecticide), (Bacillus thuringiensis var. Kurstaki, endospores, endotoxyn) on a reduction of a number and a harmfulness of cherry fruit fly (Rhagoletis cerasi L.) it impact on yields in industrial cherry orchards. Methods. A field method, in the industrial orchards in educational production department of university. A type of cherry trees — Regina and Alfa. Planting scheme — 4.0 × 5.0 m. Year of planting — 1996. Crown shape — sparsely (improved) — tiered. Rootstock — antipka. Phases of plant development at application timing — «fruit development, (fruits about 90% of the final size)» (BBCH 81) and («fruits ripening phase») (BBCH 85). Soil — shallow, low — humus dusty — loamy podzolic leached black soils: humus content — 1.3—2.5%; pH 4.8—5.2; mobile compounds Р2О5 — 130—180 mg/kg and К2О — 8.9—9.2 mg/kg (by Chirikov method). The measures for care of the experimental site — loosening a soil in the stem strips during the growing period, an application of organic and mineral fertilizers, a pruning, a splaying of grass between the rows (row spacing), a protection from pests and diseases. The technical effectiveness of applications was determined in different rates against blood-red aphids and their impact on yields in commercial apple orchards. Calculations were made according to generally accepted methods in in horticulture, plant protection and entomology. Results. The use of insecticides Aktelik 500 ЕС, Calypso 480 SС), Proclaim 50 SG, Movento 100 SC Exirel, СЕ against cherry fruit fly helped to decrease number of pests on 91.4—98.9% — 93.7—97.6% accordingly. It allowed to obtain a high — grade cherries product with a yield of 1.7—1.9 times and 1.4—2.1 times higher comparing to control. The outcome of non-standard products did not exceed 0.4—0.6% compared to 34.9—44.3% in the control (water treatment). The efficacy of bio products was 32.9—40.4%. It confirms their low efficacy against this pest. Conclusions. The use of insecticides Aktelik 500 ЕС, Calypso 480 SС, Proclaim 50 SG, Movento 100 SC, Exirel, СЕ allows to achieve high efficacy of cherry fruit fly control in industrial plantations, to manage it number and population during whole month (the period of larva development). A limitation of pest number in cherry orchard by using the studied treatments provided a yield increase and a marketable quality of the obtained fruit products.

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“…SBN-Watch was used to analyse the effect of crop rotation and sugar beet varieties on the Heterodera schachtii Schmidt population [36]. The spatial decision support system was employed to estimate the Rhagoletis cerasi severity and reduce the chemical footprint on cherry fruit and its surroundings [37]. This method used two algorithms: one based on day degree mode and the other relying on parameters such as harvest dates, pre-harvest date, and percentage of the trap.…”

Section: Related Workmentioning

confidence: 99%

A Deep Learning-Based Decision Support Tool for Plant-Parasitic Nematode Management

Pun,

Neupane,

Koech

2023

J. Imaging

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Plant-parasitic nematodes (PPN), especially sedentary endoparasitic nematodes like root-knot nematodes (RKN), pose a significant threat to major crops and vegetables. They are responsible for causing substantial yield losses, leading to economic consequences, and impacting the global food supply. The identification of PPNs and the assessment of their population is a tedious and time-consuming task. This study developed a state-of-the-art deep learning model-based decision support tool to detect and estimate the nematode population. The decision support tool is integrated with the fast inferencing YOLOv5 model and used pretrained nematode weight to detect plant-parasitic nematodes (juveniles) and eggs. The performance of the YOLOv5-640 model at detecting RKN eggs was as follows: precision = 0.992; recall = 0.959; F1-score = 0.975; and mAP = 0.979. YOLOv5-640 was able to detect RKN eggs with an inference time of 3.9 milliseconds, which is faster compared to other detection methods. The deep learning framework was integrated into a user-friendly web application system to build a fast and reliable prototype nematode decision support tool (NemDST). The NemDST facilitates farmers/growers to input image data, assess the nematode population, track the population growths, and recommend immediate actions necessary to control nematode infestation. This tool has the potential for rapid assessment of the nematode population to minimise crop yield losses and enhance financial outcomes.

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Development and Field Testing of a Spatial Decision Support System to Control Populations of the European Cherry Fruit Fly, Rhagoletis cerasi, in Commercial Orchards

Cited by 7 publications

References 24 publications

Long‐term automatic trap data reveal factors affecting diurnal flight patterns of the Mediterranean Fruit fly

Long‐term automatic trap data reveal factors affecting diurnal flight patterns of the Mediterranean Fruit fly

The efficacy of protection by modern insecticides in the industrial cherry plantations against cherry fruit fly pest

A Deep Learning-Based Decision Support Tool for Plant-Parasitic Nematode Management

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