Anti-nutrient components of guinea grass (Panicum maximum) under different nitrogen fertilizer application rates and cutting management

2012 ◽  
Vol 11 (9) ◽  
Author(s):  
Onyeonagu, C. C
Keyword(s):  
Nitrogen Fertilizer ◽  
Fertilizer Application ◽  
Panicum Maximum ◽  
Application Rates ◽  
Guinea Grass ◽  
Cutting Management

Effect of Plant Density and Nitrogen Fertilizer Application Rates on Nutrient Content of Clonal Tea Leaf

2016 ◽  
Vol 11 (2) ◽  
pp. 1-8
Author(s):  
Kibet Sitienei ◽  
Kiplangat Kirui ◽  
David Kamau ◽  
John Wanyoko ◽  
Kimutai Langat
Keyword(s):  
Nitrogen Fertilizer ◽  
Plant Density ◽  
Nutrient Content ◽  
Fertilizer Application ◽  
Application Rates ◽  
Tea Leaf

scholarly journals Extrapolation of point measurements and fertilizer-only emission factors cannot capture statewide soil NOxemissions

2018 ◽  
Vol 4 (9) ◽  
pp. eaau7373 ◽  
Author(s):  
Maya Almaraz ◽  
Edith Bai ◽  
Chao Wang ◽  
Justin Trousdell ◽  
Stephen Conley ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Nitrogen Fertilizer ◽  
Fertilizer Application ◽  
Emission Factors ◽  
Sales Data ◽  
The Core ◽  
Working Hypothesis ◽  
Application Rates ◽  
Core Issues

Maazet al. argue that inconsistencies across scales of observation undermine our working hypothesis that soil NOxemissions have been substantially overlooked in California; however, the core issues they raise are already discussed in our manuscript. We agree that point measurements cannot be reliably used to estimate statewide soil NOxemissions—the principal motivation behind our new modeling/airplane approach. Maazet al.’s presentation of fertilizer-based emission factors (a nonmechanistic scaling of point measures to regions based solely on estimated nitrogen fertilizer application rates) includes no data from California or other semiarid sites, and does not explicitly account for widely known controls of climate, soil, and moisture on soil NOxfluxes. In contrast, our model includes all of these factors. Finally, the fertilizer sales data that Maazet al. highlight are known to suffer from serious errors and do not offer a logically more robust pathway for spatial analysis of NOxemissions from soil.

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