BibTex RIS Kaynak Göster
Yıl 2018, Cilt: 19 Sayı: 3, 732 - 747, 01.09.2018

Öz

Kaynakça

  • [1] De Geronimo E, Aparicio VC, Barbaro S, Portocarrero R., Jaime S, & Costa JL. Presence of pesticides in surface water from four sub-basins in Argentina. Chemosphere 2014; 107: 423-431. [2] Laurance WF, Sayer J, Cassman K. Agricultural expansion and its impacts on tropical nature. Trends in Ecology & Evolution 2014; 29: 107-116. [3] Masters WA, Djurfeldt AA, De Haan C, Hazell P, Jayne T, Jirström M, Reardon T. Urbanization and farm size in Asia and Africa: implications for food security and agricultural research. Global Food Security 2013; 2: 156-165. [4] Donaldson D, Kiely T, Grube A. Pesticide's industry sales and usage 1998-1999 market estimates. US Environmental Protection Agency, Washington (DC) 2002: Report No. EPA-733-R-02-OOI. [5] Fayyad U, Piatesky–Shapiro G, Smyth P. Data mining to knowledge discovery in databases. AI Magazine, 1996. pp. 50-67.[6] Aktar MW, Sengupa D, Chowdhury A. Impact of pesticides use in agriculture: theirbenefits and hazard. Interdiscip Toxicol 2009; 2: 1-12. [7] Abdullah A, Brobst, S, Pervaiz I, Umer M, Nisar A. Learning dynamics of pesticide abuse through data mining. Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalization 2003; 32: 151-156.[8] Abdullah A, Brobst S. Clustering by recursive noise removal. In Proc. Atlantic Symposium on Com Biology and Genome Informatics; 2003; USA, pp. 973-977.[9] Oakley E, Zhang M, Miller R. Mining pesticide use data to identify best management practices. Renewable Agriculture and Food Systems 2006; 22: 260–270. [10] Aktar W, Sengupta D, Chowdhury A. Impact of pesticides use in agriculture: their benefits and hazrds. Interdiscip Toxicol 2009; 2: 1–12.[11] Raghuveer K, Yogesh M J, Shwetha S. Data mining in agriculture: a review AEIJMR 2014; 2: 2348 – 6724.[12] Küçükönder H, Vursavuş K, Üçkardeş F. Determining The Effect of Some Mechanical Properties on Color Maturity of Tomato With K-Star, Random Forest and Decision Tree (C4.5) Classification Algorithms. “(article in Turkish with an abstract in English)”. Türk Tarım- Gıda Bilim ve Teknoloji Dergisi 2015; 3: 300-306.[13] Ramesh D, Vardhan B V. Analysis of Crop Yield Prediction Using Data Mining Techniques. International Journal of Research in Engineering and Technology 2015; 4: 470-473.[14] Isin S, Yildirim I. Fruit-growers’ perceptions on the harmful effects of pesticides and their reflection on practices: The case of Kemalpasa, Turkey. Crop protection 2007; 26: 917-922. [15] SPSS Inc. Clementine® 7.0 User’s Guide, 2002.

entrAN ANALYSIS OF PESTICIDE USE FOR COTTON PRODUCTION THROUGH DATA MINING: THE CASE OF NAZILLIAN ANALYSIS OF PESTICIDE USE FOR COTTON PRODUCTION THROUGH DATA MINING: THE CASE OF NAZILLI

Yıl 2018, Cilt: 19 Sayı: 3, 732 - 747, 01.09.2018

Öz

Data mining involves certain methods of obtaining or inferring meaningful and otherwise-unknown information from the data. With the increasing significance of precision agricultural practices, farmers have become inclined to be engaged in a more conscious strategy of agriculture. Farmers use pesticides to destroy a disease or other hazard on their plants. Nevertheless, it has been learned over time that pesticides have harmful effects on human health and the environment. Although many farmers are aware of the risks of excessive use of agricultural pesticides, they still use them to get a faster yield and to maximize financial gain or minimize financial loss. Data received from Aydın Nazilli District Directorate of Agriculture was carefully organized and evaluated with the classification algorithms in the SPSS Clementine software. C5.0 and CR&T algorithms were employed in this study. It was thereby observed that, contrary to the conventional wisdom of most farmers, the excessive use of pesticides actually leads to a decrease in the yield obtained from the product, proportional to the measured dose.

Kaynakça

  • [1] De Geronimo E, Aparicio VC, Barbaro S, Portocarrero R., Jaime S, & Costa JL. Presence of pesticides in surface water from four sub-basins in Argentina. Chemosphere 2014; 107: 423-431. [2] Laurance WF, Sayer J, Cassman K. Agricultural expansion and its impacts on tropical nature. Trends in Ecology & Evolution 2014; 29: 107-116. [3] Masters WA, Djurfeldt AA, De Haan C, Hazell P, Jayne T, Jirström M, Reardon T. Urbanization and farm size in Asia and Africa: implications for food security and agricultural research. Global Food Security 2013; 2: 156-165. [4] Donaldson D, Kiely T, Grube A. Pesticide's industry sales and usage 1998-1999 market estimates. US Environmental Protection Agency, Washington (DC) 2002: Report No. EPA-733-R-02-OOI. [5] Fayyad U, Piatesky–Shapiro G, Smyth P. Data mining to knowledge discovery in databases. AI Magazine, 1996. pp. 50-67.[6] Aktar MW, Sengupa D, Chowdhury A. Impact of pesticides use in agriculture: theirbenefits and hazard. Interdiscip Toxicol 2009; 2: 1-12. [7] Abdullah A, Brobst, S, Pervaiz I, Umer M, Nisar A. Learning dynamics of pesticide abuse through data mining. Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalization 2003; 32: 151-156.[8] Abdullah A, Brobst S. Clustering by recursive noise removal. In Proc. Atlantic Symposium on Com Biology and Genome Informatics; 2003; USA, pp. 973-977.[9] Oakley E, Zhang M, Miller R. Mining pesticide use data to identify best management practices. Renewable Agriculture and Food Systems 2006; 22: 260–270. [10] Aktar W, Sengupta D, Chowdhury A. Impact of pesticides use in agriculture: their benefits and hazrds. Interdiscip Toxicol 2009; 2: 1–12.[11] Raghuveer K, Yogesh M J, Shwetha S. Data mining in agriculture: a review AEIJMR 2014; 2: 2348 – 6724.[12] Küçükönder H, Vursavuş K, Üçkardeş F. Determining The Effect of Some Mechanical Properties on Color Maturity of Tomato With K-Star, Random Forest and Decision Tree (C4.5) Classification Algorithms. “(article in Turkish with an abstract in English)”. Türk Tarım- Gıda Bilim ve Teknoloji Dergisi 2015; 3: 300-306.[13] Ramesh D, Vardhan B V. Analysis of Crop Yield Prediction Using Data Mining Techniques. International Journal of Research in Engineering and Technology 2015; 4: 470-473.[14] Isin S, Yildirim I. Fruit-growers’ perceptions on the harmful effects of pesticides and their reflection on practices: The case of Kemalpasa, Turkey. Crop protection 2007; 26: 917-922. [15] SPSS Inc. Clementine® 7.0 User’s Guide, 2002.
Toplam 1 adet kaynakça vardır.

Ayrıntılar

Bölüm Makaleler
Yazarlar

Zehra Burdur Bu kişi benim

Canan Eren Atay Bu kişi benim

Yayımlanma Tarihi 1 Eylül 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 19 Sayı: 3

Kaynak Göster

AMA Burdur Z, Atay CE. entrAN ANALYSIS OF PESTICIDE USE FOR COTTON PRODUCTION THROUGH DATA MINING: THE CASE OF NAZILLIAN ANALYSIS OF PESTICIDE USE FOR COTTON PRODUCTION THROUGH DATA MINING: THE CASE OF NAZILLI. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering. Eylül 2018;19(3):732-747.