A PROTOTYPE FOR SPRAYING PESTICIDE USING VISION TECHNIQUE

Document Type : Original Article

Authors

1 Prof. Emeritus of Ag. Power & Machinery., Fac. of Ag. Eng., Al-Azhar U., Egypt.

2 Prof and Deputy Dean of Fac. of Ag. Eng., Al-Azhar U., Egypt.

3 Assoc. Prof. Emeritus. of Ag. Machinery., Fac. of Ag. Eng., Al-Azhar U., Egypt.

4 Assist. Lect., Ag. Mach. & Power Eng. Dept., Fac. of Ag. Eng., Al-Azhar U., Egypt.

Abstract

The spraying of horticultural crops is done by spray all unit area, including the inter-tree distance, which leads to large losses of applied pesticide, pollution of soil and groundwater. To overcome these problems a prototype of a spray machine was manufactured using principle of vision technique. The first stage of experiments was carried out in the laboratory of the faculty of Agric. Eng., Al-Azhar Univ., Nasr city, Cairo to study the analysis of images and response time of electronic components and discharge of different nozzles. The images analysis was carried out to find the color values (RGB) of the trees (orange) used in the experiments and adapted them in the history of program. The tree images were taken each an hour at distances of 1, 3, and 5 m at a daytime from 5.00 to10.00 am and from 3.00 to 6.00 pm. The second stage of experiments was carried out to calculate the percentage of savings and economical. Four forward speeds (0.27, 0.55, 0.85 and 1.12 m/s), four types of nozzles and four spray pressures (250, 300, 350 and 400 kPa) were studied. The camera was installed at distances of 0.74, 1.5, 2.33 and 3.07 m to overcome the response time of electronic components at forward speeds of 0.27, 0.55, 0.85 and 1.12 m/s, respect. The maximum percentage amount of saving spray liquid was 57.57 % at nozzle type N4, spray pressure of 400 kPa and spray forward speed of 0.27 m/s by using vision technique than without.

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Brosnan, T., & Sun, D. W. (2004). Improving quality inspection of food products by computer vision - a review. Journal of food engineering, 61(1), 3-16.‏
Brown, D. L., Giles, D. K., Oliver, M. N., & Klassen, P. (2008). Targeted spray technology to reduce pesticide in runoff from dormant orchards. Crop Protection, 27(3-5), 545-552.
FAO (Food and Agricultural Organization) (2016). Pesticides Use http://www.fao.org/faostat/en/#data/RP.
Ismail A. M., H. Rashad, Z. Imara and A. E. Rezk. (2015) development of an autonomous navigation agricultural robotic platform based on machine vision. Misr J. Ag. Eng., 32 (4): 1421 – 1450.
Merritt, S. J., G. E. Meyer, K. Von Bargen, and D. A. Mortensen.  (1994). Reflectance sensor and control system for spot spraying.  ASAE Paper No. 941057. St. Joseph, Mich.: ASAE.
Oerke, E. C. (2006). Crop losses to pests. The Journal of Agricultural Science, 144(1): 31-43.
https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=2ahUKEwjng7Si1sHeAhUJDOwKHS0xCmwQFjABegQIAxAC&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.657.5813%26rep%3Drep1%26type%3Dpdf&usg=AOvVaw38tFZ9wAcNUlF7jdvdEOcO
Padmavathi, K., and K. Thangadurai (2016). Implementation of RGB and grayscale images in plant leaves disease detection–comparative study. Indian Journal of Science and Technology, 9(6).