scholarly journals Effects of landscape complexity on crop productivity: an assessment from space

2021 ◽  
Author(s):  
Lan Nguyen ◽  
Lan H Nguyen ◽  
Sam Robinson ◽  
Paul Galpern
2021 ◽  
Author(s):  
Lan Nguyen ◽  
Lan H Nguyen ◽  
Sam Robinson ◽  
Paul Galpern

Author(s):  
Saulius GUŽYS ◽  
Stefanija MISEVIČIENĖ

The use of nitrogen fertilizer is becoming a global problem; however continuous fertilization with nitrogen ensures large and constant harvests. An 8 year research (2006–2013) was conducted to evaluate the relationships between differently fertilized cultivated plant rotations. The research was conducted in Lipliunai (Lithuania) in the agroecosystem with nitrogen metabolism in fields with deeper carbonaceous soil, i.e. Endocalcari Endohypogleyic Cambisol (CMg-n-w-can). The research area covered three drained plots where crop rotation of differently fertilized cereals and perennial grasses was applied. Samples of soil, water and plants were investigated in the Chemical Analysis Laboratory of the Aleksandras Stulginskis University certified by the Environment Ministry of the Republic of Lithuania. The greatest productivity was found in a crop rotation with higher fertilization (N32-140). In crop rotation with lower fertilization (N24-90) productivity of cereals and perennial grasses (N0-80) was 11–35 % lower. The highest amount of mineral soil nitrogen was found in cereal crop rotation with higher fertilization. It was influenced by fertilization and crop productivity. The lowest Nmin and Ntotal concentrations in drainage water were found in grasses crop rotation. Crop rotations of differently fertilized cereals increased nitrogen concentration in drainage water. Nmin concentration in water depended on crop productivity, quantity of mineral soil nitrogen, fertilization, and nitrogen balance. The lowest nitrogen leaching was found in the crop rotation of grasses. Cereal crop rotation increased nitrogen leaching by 12–42 %. The usage of all crop rotations resulted in a negative nitrogen balance, which essentially depended on fertilization with nitrogen fertilizer.


2001 ◽  
Vol 2 (1) ◽  
pp. 109-119 ◽  
Author(s):  
D.J. Walker ◽  
N. C. Kenkel

Author(s):  
Sujata Mulik

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 


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