Browsing by Author "ERDOĞAN, HİLAL"

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Detection of cucurbit powdery mildew, sphaerotheca fuliginea (schlech.) thermal imaging in field conditions
(Univ Agronomic Sciences & Veterinary Medicine Bucharest - Usamv, 2023-01-01) Erdoğan, Hilal; ERDOĞAN, HİLAL; Bütüner, Alperen Kaan; BÜTÜNER, ALPEREN KAAN; Şahin, Yavuz Selim; ŞAHİN, YAVUZ SELİM; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü.; 0000-0002-0387-2600; AAP-5834-2020; AAH-2823-2021
Plant diseases are one of the leading causes of yield losses in agricultural areas. In the fight against these diseases, chemical control methods are frequently used. However, this method of combat usually begins after the disease has spread throughout the entire field. The most essential thing here is to control the disease before it spreads throughout the entire country. Thermal imaging methods can now be used to accomplish this. Plant diseases stress the plant as a result of infection. The plant's stress causes activities that cause a temperature increase or reduction in the area where the infection has occurred or has begun. Thermal imaging technologies can be used to identify this condition. This work focuses on the potential early detection of Cucurbit powdery mildew (Sphaerotheca fuliginea (Schlech.) Polacci), which causes considerable yield loss in Cucurbitaceae, utilizing thermal imaging technologies. According to the findings, the lowest temperature in infected leaf tissues was 8.2 degrees C, whereas the maximum temperature in plant tissues without infection was 10.2 degrees C. The findings suggest that thermal imaging technology could be used to identify powdery mildew in cucurbits. In this case, early detection will potentially enable the detection of the disease that has started to spread in a certain region and will allow the disease to be potentially controlled with less labor and chemical use.
Entomopathogenic nematode dispensing robot: Nemabot
(Elsevier, 2021-02-14) Erdoğan, Hilal; Ünal, Halil; Lewis, Edwin E.; ERDOĞAN, HİLAL; ÜNAL, HALİL; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü; 0000-0002-0387-2600; AAP-5834-2020; IHS-3745-2023
Entomopathogenic nematodes (EPN) are obligate endoparasites of many insect species and they are important biocontrol agents. Application strategies that improve precision and reduce labor would increase their potential in many cropping systems. We developed a unique robotic system to apply EPNs to a surface area precisely. The robotic system picks up EPNs from a suspension in a reservoir with a peristaltic pump and transfers them to an exact point with an exact amount. Four suspensions were prepared with four concentrations of EPNs; 0.1, 0.2, 0.4 and 0.8 g of commercial EPN product per 2 L of water. All suspensions were applied in three different amounts of water (25, 50 and 100 mL per application). In total, 12 different applications were conducted with the robot. Conical falcon centrifuge tubes were used to collect applied EPNs. Five samples (10 ?l) were taken from collected 25, 50 and 100 mL EPN suspensions and the average nematode number in the samples were scaled to the whole suspension. Results of the experiments showed that all robot applications, except 25 mL?0.1 g dose, were not significantly different from those of the control treatment, application with a pipette.. Thus, the robotic system has been found to make consistent applications.
Field application of encapsulated entomopathogenic nematodes using a precision planter
(Academic Press Inc Elsevier Science, 2023-04-28) Ulu, Tufan Can; ERDOĞAN, HİLAL; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü.; 0000-0003-3640-1474; 0000-0002-0387-2600; AAP-5834-2020
The use of entomopathogenic nematodes (EPNs) as a biological control agent in agriculture has shown efficacy against various soil-dwelling pests. Despite its potential, high production costs and inconsistent field efficiency remain significant challenges. Although EPNs can be applied using irrigation systems and spraying equipment, optimized applications are required. This study aimed to evaluate the feasibility of applying EPNs in gelatin capsules and planting with a precision planter. It was hypothesized that this method would lead to more controlled and uniform EPN application. The effects of EPN encapsulation on dispersal and field persistence in the soil were also investigated. Larval mortality for capsule applications was between 53 and 67% under field conditions, with no statistical difference compared to the drip irrigation applications. Dispersal trials were carried out using custom steel olfactometers, and capsule application did not have any adverse effects on the dispersal of infective juveniles for 24, 48 and 72 h. Persistence trials revealed no significant differences between the capsule and control groups, with a maximum persistence of 50 days. The results suggest that the capsule technique could be a promising option for large-scale EPN applications, and further optimization may lead to improved results.
Group joining behaviours in the entomopathogenic nematode steinernema glaseri
(Elsevier, 2023-03-28) Stevens, Glen; Erdoğan, Hilal; Pimentel, Eleanor; Dotson, Jenna; Stevens, Asa; Shapiro-Ilan, David; Kaplan, Fatma; Schliekelman, Paul; Lewis, Edwin; ERDOĞAN, HİLAL; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü; AAP-5834-2020
Aggregations of foraging animals are key aspects of their ecology, driving spatial patterns, resource access, and successful resource exploitation. Entomopathogenic/insect parasitic nematodes demonstrate aggregated population structures. However, there are gaps in our understanding of how different behaviours affect aggregation. To understand joining behaviour as a mechanism of aggregation, we examined the group movement and joining behaviour of the EPN species, Steinernema glaseri, in conspecific (S. glaseri) and heterospecific (S. carpocapsae and S. feltiae) assemblages. We assessed group movement of S. glaseri using a glass olfactometer where nematodes were added to the central hub and allowed to disperse into six arms towards cues at the ends. We measured movement in the absence of external cues, when host cues were present but uniform, and in response to both con- and heterospecific entomopathogenic nematodes. S. glaseri dispersed in a highly aggregated fashion both in the presence and absence of host cues. When conspecific nematodes were present in the olfactometer ends, S. glaseri readily moved towards and joined conspecific groups, particularly if those conspecifics had experienced host contact 48 h previously. When heterospecific nematodes were present in the ends, S. glaseri only appeared to preferentially join groups of S. feltiae with prior host contact. S. glaseri exhibited no propensity to join groups of S. carpocapsae regardless of prior host contact. Findings demonstrate context-dependent joining behaviours that may underlie aggregation in EPNs. These behaviours may lead to more effective mass attack and regulate interspecific competition among these insect parasites.
Machine learning-based detection and severity assessment of sunflower powdery mildew: A precision agriculture approach
(Bursa Uludağ Üniversitesi, 2023-09-18) Erdinç, Atilla; BÜTÜNER, ALPEREN KAAN; ŞAHİN, YAVUZ SELİM; ERDOĞAN, HİLAL
Sunflower powdery mildew (Golovinomyces cichoracearum (DC.) V.P. Heluta) is a substantial threat to sunflower crops, causing significant yield loss. Traditional identification methods, based on human observation, fall short in providing early disease detection and quick control. This study presents a novel approach to this problem, utilizing machine learning for the early detection of powdery mildew in sunflowers. The disease severity levels were determined by training a Decision Trees model using matrix of soil, powdery mildew, stems, and leaf images obtained from original field images. It was detected disease severity levels of 18.14% and 5.56% in test images labeled as A and C, respectively. The model's demonstrated accuracy of 85% suggests high proficiency, indicating that machine learning, specifically the DTs model, holds promising prospects for revolutionizing disease control and diseases prevention in agriculture.
Nematodes follow a leader
(Frontiers Media Sa, 2021-11-04) Erdoğan, Hilal; Cruzado-Gutierrez, Karin; Stevens, Glen; Shapiro-Ilan, David; Kaplan, Fatma; Alborn, Hans; Lewis, Edwin; ERDOĞAN, HİLAL; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü.; AAP-5834-2020
Aggregated movement and population structure are known in entomopathogenic nematodes, which are obligate insect parasites. Aggregation behavior in the absence of external stimuli suggests communication among individuals, often in the form of trail-following, which has not been shown by nematodes of any kind. Interactions among individuals are an essential basis of following behaviors and can have significant fitness consequences. We explored intraspecific and interspecific interactions among three Steinernema species (S. glaseri, S. carpocapsae, and S. feltiae) in terms of trail following, and fitness outcomes of following heterospecific individuals. We found that the following behavior is context dependent. Following behavior among conspecifics was significantly increased when the lead nematode had prior contact with host cuticle. However, we did not find a clear association between the following response to heterospecific IJs and their reproductive success in a co-infected host.
Potential for early detection of powdery mildew in okra under field conditions using thermal imaging
(Univ Agronomic Sciences & Veterinary Medicine Bucharest - Usamv, 2023-01-01) ŞAHİN, YAVUZ SELİM; BÜTÜNER, ALPEREN KAAN; Bütüner, Alperen Kaan; Erdoğan, Hilal; ERDOĞAN, HİLAL; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Bitki Koruma Bölümü.; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü.; 0000-0002-0387-2600; AAP-5834-2020; AAH-2823-2021
In recent years, apprehensions surrounding the pervasive employment of chemical control methods in global agricultural production have intensified, primarily due to their detrimental effects on non-target organisms. This situation accentuates the importance of technology-driven alternatives for managing plant diseases in agriculture. One such technological innovation, thermal imaging technology, has emerged as a promising tool for the early detection of plant diseases. Infections often induce stress in plants, leading to either elevated or reduced temperatures at the point of infection. It is postulated that thermal imaging may effectively identify such temperature deviations in plant tissues afflicted by disease during the initial stages. The study investigated temperature differences in leaves infected by Erysiphe cichoracearum, with disparities up to 1.6 degrees C. Over three weeks, the surface temperatures of numerous leaves were analysed at 30-minute intervals. In three weeks period, it was shown that infected leaf surfaces had significantly lower average daily temperatures than ambient and healthy leaf temperatures. Furthermore, healthy leaf temperatures remained consistently lower than ambient temperatures throughout the study.