Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabil...Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabilities has paved the way of using machine vision technologies for patch spraying. Machine vision system has to acquire and process digital images to make control decisions. Proper identification and classification of objects present in image holds the key to make control decisions and use of any spraying operation performed. Recognition of objects in digital image may be affected by background, intensity, image resolution, orientation of the object and geometrical characteristics. A set of 16, including 11 shape and 5 texture-based parameters coupled with predictive discriminating analysis has been used to identify the weed leaves. Geometrical features were indexed successfully to eliminate the effect of object orientation. Linear discriminating analysis was found to be more effective in correct classification of weed leaves. The classification accuracy of 69% to 80% was observed. These features can be utilized for development of image based variable rate sprayer.展开更多
Agricultural production is highly dependent on the climatic variability of the specific regions. Differential climatic and soil conditions bring about changes in yield, quality of crops thus affecting the economy. Thi...Agricultural production is highly dependent on the climatic variability of the specific regions. Differential climatic and soil conditions bring about changes in yield, quality of crops thus affecting the economy. This study evaluated the impact of variability in different climatic factors keeping the other factors constant on spring wheat production in North Dakota from 2007 to 2011. The spring wheat yield mainly depends on the climatic changes during growing periods April to September. Average maximum air temperature was significantly different from April to September except June from 2007 to 2011. High average minimum and maximum air temperatures during planting time increase yield and planting area for 2010. In 2011, low mean soil temperature, excess rainfall in April caused low yield of spring wheat. The unmitigated climate variability will result in declines in yields. So, adoption of sustainable agriculture practices helps the farmers to develop the different practices for their farms.展开更多
文摘Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabilities has paved the way of using machine vision technologies for patch spraying. Machine vision system has to acquire and process digital images to make control decisions. Proper identification and classification of objects present in image holds the key to make control decisions and use of any spraying operation performed. Recognition of objects in digital image may be affected by background, intensity, image resolution, orientation of the object and geometrical characteristics. A set of 16, including 11 shape and 5 texture-based parameters coupled with predictive discriminating analysis has been used to identify the weed leaves. Geometrical features were indexed successfully to eliminate the effect of object orientation. Linear discriminating analysis was found to be more effective in correct classification of weed leaves. The classification accuracy of 69% to 80% was observed. These features can be utilized for development of image based variable rate sprayer.
文摘Agricultural production is highly dependent on the climatic variability of the specific regions. Differential climatic and soil conditions bring about changes in yield, quality of crops thus affecting the economy. This study evaluated the impact of variability in different climatic factors keeping the other factors constant on spring wheat production in North Dakota from 2007 to 2011. The spring wheat yield mainly depends on the climatic changes during growing periods April to September. Average maximum air temperature was significantly different from April to September except June from 2007 to 2011. High average minimum and maximum air temperatures during planting time increase yield and planting area for 2010. In 2011, low mean soil temperature, excess rainfall in April caused low yield of spring wheat. The unmitigated climate variability will result in declines in yields. So, adoption of sustainable agriculture practices helps the farmers to develop the different practices for their farms.
