MUHAMMAD AZEEM SABIR, MUHAMMAD FARRAKH NAWAZ, TANVEER HUSSAIN KHAN, USMAN ZULFIQAR, JUNAID NASEER, SADAM HUSSAIN, SADAF GUL, MUHAMMAD FAISAL MAQSOOD, RASHID IQBAL, BABER ALI, RANA ROY
{"title":"Impact of dust load and lead (Pb) stress on leaf functioning of urban vegetation","authors":"MUHAMMAD AZEEM SABIR, MUHAMMAD FARRAKH NAWAZ, TANVEER HUSSAIN KHAN, USMAN ZULFIQAR, JUNAID NASEER, SADAM HUSSAIN, SADAF GUL, MUHAMMAD FAISAL MAQSOOD, RASHID IQBAL, BABER ALI, RANA ROY","doi":"10.55730/1300-011x.3122","DOIUrl":"https://doi.org/10.55730/1300-011x.3122","url":null,"abstract":"","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MERVE URAN ŞENER, SONER KAZAZ, TUĞBA KILIÇ, EZGİ DOĞAN MERAL
{"title":"Crossing success of 'pot miniature rose x cut rose'","authors":"MERVE URAN ŞENER, SONER KAZAZ, TUĞBA KILIÇ, EZGİ DOĞAN MERAL","doi":"10.55730/1300-011x.3117","DOIUrl":"https://doi.org/10.55730/1300-011x.3117","url":null,"abstract":"","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimization of VAE-CGAN structure for missing time-series data complementation of UAV jujube garden aerial surveys","authors":"SHUNKANG LING, NIANYI WANG, JINGBIN LI, LONGPENG DING","doi":"10.55730/1300-011x.3124","DOIUrl":"https://doi.org/10.55730/1300-011x.3124","url":null,"abstract":"","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GIORGIANA BUZGAU, ROMİNA ALINA MARC, CRINA CARMEN MURESAN, ANCA FARCAS, SONIA ANCUTA SOCACI, ANDRUTA MURESAN, SEVASTITA MUSTE
{"title":"The study of the quality parameters of the tortilla chips products formulated from mixtures of corn flour and legumes","authors":"GIORGIANA BUZGAU, ROMİNA ALINA MARC, CRINA CARMEN MURESAN, ANCA FARCAS, SONIA ANCUTA SOCACI, ANDRUTA MURESAN, SEVASTITA MUSTE","doi":"10.55730/1300-011x.3126","DOIUrl":"https://doi.org/10.55730/1300-011x.3126","url":null,"abstract":"","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CAHİT KAYA, NACİYE SENA ÇAĞATAY, JOHN T. MARGARITOPOULOS, JOHN VONTAS, REMZİ ATLIHAN, NURPER GÜZ
: The cotton aphid, Aphis gossypii Glover (Hemiptera: Aphididae) is a polyphagous pest that could cause economic crop losses in various crops. Cotton production areas are under insecticide application pressure, and the possibility of insecticide resistance development is higher than in other crops. Chemical insecticides, especially neonicotinoids, are the most common instruments of Integrated Pest Management (IPM) strategies against A. gossypii . In this study, the resistance status of A. gossypii populations from the largest cotton plantation areas of Türkiye was analyzed. Nine field-collected aphid populations and a susceptible strain were examined in leaf-dip bioassays with three neonicotinoid insecticides. The resistance ratios of bioassays ranged from 22.6 to 82.6 for acetamiprid, 23.5 to 67.3 for imidacloprid, and 1.1 to 20.8 for thiamethoxam. Comparative sequence analysis between susceptible and resistant strains was analyzed to identify known mutations to confer resistance to neonicotinoids. The mean enzyme activity in some populations was significantly higher than in the susceptible strain. The enzyme activity ratios ranged from 1.9 to 3.9 for CarE and 1.5 to 3.1 for GST . The bioassay data revealed moderate to high resistance levels in acetamiprid and imidacloprid and low to medium levels in thiamethoxam. A partial sequence of the β 1 subunit of the nAChR in specimens of the populations examined did not reveal any of the V62I , L80S, and R81T and point mutations. The lack of any correlation between the carboxylesterase or glutathione-S-transferase activity and the LC 50 values of three insecticides suggested that these two detoxification enzymes were not involved in the resistance levels observed. However, the resistance levels observed in the present study could be attributed to metabolic resistance mechanisms. Another important point is the cross-resistance observed between the neonicotinoids in the present study. Their extensive use, especially in cotton, might select aphid genotypes resistant to more than one neonicotinoid.
{"title":"Neonicotinoid resistance in populations of the cotton aphid, Aphis gossypii Glover (Hemiptera: Aphididae) in Cotton Plantation Areas of Turkey","authors":"CAHİT KAYA, NACİYE SENA ÇAĞATAY, JOHN T. MARGARITOPOULOS, JOHN VONTAS, REMZİ ATLIHAN, NURPER GÜZ","doi":"10.55730/1300-011x.3114","DOIUrl":"https://doi.org/10.55730/1300-011x.3114","url":null,"abstract":": The cotton aphid, Aphis gossypii Glover (Hemiptera: Aphididae) is a polyphagous pest that could cause economic crop losses in various crops. Cotton production areas are under insecticide application pressure, and the possibility of insecticide resistance development is higher than in other crops. Chemical insecticides, especially neonicotinoids, are the most common instruments of Integrated Pest Management (IPM) strategies against A. gossypii . In this study, the resistance status of A. gossypii populations from the largest cotton plantation areas of Türkiye was analyzed. Nine field-collected aphid populations and a susceptible strain were examined in leaf-dip bioassays with three neonicotinoid insecticides. The resistance ratios of bioassays ranged from 22.6 to 82.6 for acetamiprid, 23.5 to 67.3 for imidacloprid, and 1.1 to 20.8 for thiamethoxam. Comparative sequence analysis between susceptible and resistant strains was analyzed to identify known mutations to confer resistance to neonicotinoids. The mean enzyme activity in some populations was significantly higher than in the susceptible strain. The enzyme activity ratios ranged from 1.9 to 3.9 for CarE and 1.5 to 3.1 for GST . The bioassay data revealed moderate to high resistance levels in acetamiprid and imidacloprid and low to medium levels in thiamethoxam. A partial sequence of the β 1 subunit of the nAChR in specimens of the populations examined did not reveal any of the V62I , L80S, and R81T and point mutations. The lack of any correlation between the carboxylesterase or glutathione-S-transferase activity and the LC 50 values of three insecticides suggested that these two detoxification enzymes were not involved in the resistance levels observed. However, the resistance levels observed in the present study could be attributed to metabolic resistance mechanisms. Another important point is the cross-resistance observed between the neonicotinoids in the present study. Their extensive use, especially in cotton, might select aphid genotypes resistant to more than one neonicotinoid.","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
KIRILL MAKSIMOVICH, OLGA ALSOVA, VLADIMIR KALICHKIN, DMITRY FEDOROV
{"title":"Crop weed infestation forecasting using data mining methods","authors":"KIRILL MAKSIMOVICH, OLGA ALSOVA, VLADIMIR KALICHKIN, DMITRY FEDOROV","doi":"10.55730/1300-011x.3118","DOIUrl":"https://doi.org/10.55730/1300-011x.3118","url":null,"abstract":"","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Potential roles of plant growth-promoting microbes in wheat adaptation and tolerance to herbicide and drought stress combination","authors":"OKSANA LASTOCHKINA, MASSIMO BOSACCHI","doi":"10.55730/1300-011x.3121","DOIUrl":"https://doi.org/10.55730/1300-011x.3121","url":null,"abstract":"","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"QTL-seq for the identification of candidate genes responsible for double seeds in almond","authors":"HARUN KARCI","doi":"10.55730/1300-011x.3115","DOIUrl":"https://doi.org/10.55730/1300-011x.3115","url":null,"abstract":"","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Tomato plant leaf diseases are the main risk factor for plant growth. Detection of diseases at the initial stage is the main and most complex task for farmers due to common morphological properties like colour, shape, texture, and edges. The quality and quantity of agricultural products might be significantly reduced because of plant diseases. One hundred and seventy-seven pathogens, including 167 fungi and others like bacteria, algae, and nematodes, attack the well-known tomato plant. Postharvest illnesses may also result in significant productivity losses. An expert opinion is needed for illness analysis due to the modest variations in the symptoms of different tomato diseases. Farmers who misuse pesticides may suffer financial losses as a result of erroneous diagnoses. Plant leaf diseases are difficult to categorize since there are many similarities among different groups and intricate design changes. In this paper, the authors present a deep ensemble learning model (DELM) for autonomous plant disease identification. The pretrained models are refined using transfer learning. Different augmentation techniques, including picture enhancement, rotation, and scaling, combat overfitting. This research gives a thorough taxonomy of the performance of a single model and various ensemble learning models to classify superresolution tomato plant leaf disease images. With the publicly available dataset, including ten different biotic disease classes of tomato plants, the efficiency of the projected prototype is evaluated. The efficiency of a single pretrained model, VGG16, shows 98% accuracy with an F1-score of 93.25%. In addition, an ensemble of three models (VGG16, InceptionV3, and GoogleNet) shows more accurate results than other ensemble models.
{"title":"DELM: Deep Ensemble Learning Model for Multiclass Classification of Super-Resolution Leaf Disease Images","authors":"PRABHJOT KAUR, MUKUND PRATAP SINGH, ANAND MUNI MISHRA, ACHYUT SHANKAR, PRABHISHEK SINGH, MANOJ DIWAKAR, SOUMYA RANJAN NAYAK","doi":"10.55730/1300-011x.3123","DOIUrl":"https://doi.org/10.55730/1300-011x.3123","url":null,"abstract":": Tomato plant leaf diseases are the main risk factor for plant growth. Detection of diseases at the initial stage is the main and most complex task for farmers due to common morphological properties like colour, shape, texture, and edges. The quality and quantity of agricultural products might be significantly reduced because of plant diseases. One hundred and seventy-seven pathogens, including 167 fungi and others like bacteria, algae, and nematodes, attack the well-known tomato plant. Postharvest illnesses may also result in significant productivity losses. An expert opinion is needed for illness analysis due to the modest variations in the symptoms of different tomato diseases. Farmers who misuse pesticides may suffer financial losses as a result of erroneous diagnoses. Plant leaf diseases are difficult to categorize since there are many similarities among different groups and intricate design changes. In this paper, the authors present a deep ensemble learning model (DELM) for autonomous plant disease identification. The pretrained models are refined using transfer learning. Different augmentation techniques, including picture enhancement, rotation, and scaling, combat overfitting. This research gives a thorough taxonomy of the performance of a single model and various ensemble learning models to classify superresolution tomato plant leaf disease images. With the publicly available dataset, including ten different biotic disease classes of tomato plants, the efficiency of the projected prototype is evaluated. The efficiency of a single pretrained model, VGG16, shows 98% accuracy with an F1-score of 93.25%. In addition, an ensemble of three models (VGG16, InceptionV3, and GoogleNet) shows more accurate results than other ensemble models.","PeriodicalId":23365,"journal":{"name":"TURKISH JOURNAL OF AGRICULTURE AND FORESTRY","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136182664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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