Experimental Demonstration of Nitrogen Fixation

1975 ◽  
Vol 37 (1) ◽  
pp. 49-50
Author(s):  
John Cunningham ◽  
Theodore Lemeshka ◽  
Frederick J. Pearson
Keyword(s):  
Nitrogen Fixation ◽  
Experimental Demonstration

Factors controlling nitrogen fixation in temperate seagrass beds

2015 ◽  
Vol 525 ◽  
pp. 41-51 ◽  
Author(s):  
PLM Cook ◽  
V Evrard ◽  
RJ Woodland
Keyword(s):  
Nitrogen Fixation ◽  
Seagrass Beds

NEW CLOVER CULTIVARS FOR WAIKATO DAIRY PASTURE: ESTABLISHMENT, PRODUCTION AND NITROGEN FIXATION DURING THE FIRST YEAR

1988 ◽  
pp. 207-211
Author(s):  
S.F. Ledgard ◽  
G.J. Brier ◽  
R.N. Watson
Keyword(s):  
Nitrogen Fixation ◽  
White Clover ◽  
Dairy Cow ◽  
Red Clover ◽  
First Year ◽  
Buried Seed

Clover cultivars grown with ryegrass were compared in an establishment year under dairy cow grazing. There was no difference in total annual productton but summer production was greater with Pawera red clover and with Kopu or Pitau white clovers. Clovers differed little in the proportion of nitrogen fixed, except during summer when values were highest for Pawera. Pawera was less prone to nematode attack than white clover cultivars but was more susceptible to clover rot. Resident clovers and high buried seed levels (e.g., 11-91 kg/ha) made introduction of new clover cultivars difficult. Sown clovers established best (50-70% of total clover plants) when drilled into soil treated with dicamba and glyphosate. Keywords: white clover, red clover, nematodes. nitrogen fixation, pasture renovation

Experimental Demonstration of 1200V IGBT Module for a Magnetic Energy Recovery Switch Application

2008 ◽  
Vol 128 (4) ◽  
pp. 677-682 ◽  
Author(s):  
Taku Takaku ◽  
Noriyuki Iwamuro ◽  
Yoshiyuki Uchida ◽  
Ryuichi Shimada
Keyword(s):  
Energy Recovery ◽  
Magnetic Energy ◽  
Experimental Demonstration ◽  
Igbt Module

Recognition of Birds in Blurred and Illumination Images by Local Features

2017 ◽  
Vol 7 (7) ◽  
pp. 243
Author(s):  
Suresha .M ◽  
. Sandeep
Keyword(s):  
Computer Vision ◽  
Time Complexity ◽  
Feature Detection ◽  
Feature Matching ◽  
Fast Algorithms ◽  
Local Features ◽  
Experimental Demonstration ◽  
Harris Corner ◽  
Blurred Image ◽  
Blurred Images

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.

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