Classification of Soil and Prediction of Total Nitrogen Content Present in Soil by Using Hyperspectral Imaging

Author(s):  
Manoj Kumar Behera ◽  
Kanti Mahanti Sai Kishore ◽  
S. Chakravarty
2014 ◽  
Vol 931-932 ◽  
pp. 1582-1586 ◽  
Author(s):  
Nitikarn Nimsuk

Fish sauce is one of the signature condiments in various cuisines in many countries. In this paper, fish sauces are successfully classified into groups depending on their quality indicated by the level of total nitrogen content. We introduce an electronic nose technology together with a neural network algorithm to the classification of fish sauces. The transient responses are used as features for the creation of pattern vectors for odor samples. The result of principal component analysis shows well-separated patterns of fish sauce. Furthermore, we also apply the learning vector quantization method for the classification. As a result, we obtain high accuracy of more than 90% in the classification of fish sauce based on the level of total nitrogen content.


1992 ◽  
Vol 25 (4-5) ◽  
pp. 203-209 ◽  
Author(s):  
R. Kayser ◽  
G. Stobbe ◽  
M. Werner

At Wolfsburg for a load of 100,000 p.e., the step-feed activated sludge process for nitrogen removal is successfully in operation. Due to the high denitrification potential (BOD:TKN = 5:1) the effluent total nitrogen content can be kept below 10 mg l−1 N; furthermore by some enhanced biological phosphate removal about 80% phosphorus may be removed without any chemicals.


2020 ◽  
Vol 63 (5) ◽  
pp. 407-417
Author(s):  
Lim Wai Yin ◽  
Lim Phaik Eem ◽  
Affendi Yang Amri ◽  
Song Sze Looi ◽  
Acga Cheng

AbstractWith the potential adverse effects of climate change, it is essential to enhance the understanding of marine ecosystem dynamics, which can be driven by the co-evolutionary interaction between autotrophs and herbivores. This study looked into the autotroph-herbivore interactions in Malaysian waters, mainly to determine if autotroph nutritional quality significantly influences herbivore consumption rates. We documented the relative consumption rate of a generalist herbivore (Chanos chanos Forsskål) obtained from the Straits of Malacca through multiple feeding trials using 12 macroalgal species collected from different coastal areas of the Straits of Malacca, the Straits of Johor, and the South China Sea. The herbivore fed selectively on the tested macroalgal species, with the most and least consumed species having the lowest and highest total nitrogen content, respectively. Besides total nitrogen content, the least consumed species also had the highest total phenolic content. Interestingly, we observed that the herbivore generally preferred to consume filamentous macroalgae, especially those collected from the South China Sea. Overall, our findings demonstrated that the feeding behaviour of a generalist herbivore could be influenced by the nutritional quality of the autotrophs, which may depend directly or indirectly on other factors such as autotroph morphology and geography.


2014 ◽  
Vol 602-605 ◽  
pp. 2445-2448
Author(s):  
Fu Quan Jia ◽  
Zhu Jun Tian

NIPGA technology is used in order to detect the total nitrogen content in sewage quickly. D-D neutron generator is used as the neutron source and BGO detector is used to detect gamma rays of nitrogen. The simulated result of MCNP shows the nitrogen’s limit of detection is 0.2 mg/L and the total nitrogen in V-type water can be detected. So this method can be used to detect the total nitrogen content in sewage quickly.


Eksergi ◽  
2015 ◽  
Vol 12 (2) ◽  
pp. 23
Author(s):  
Iqbal Syaichurrozi

The purpose of this study was to increase biogas production using co-digestion concept. Vinasse Waste (VW) containing high COD and low total Nitrogen content was mixtured with Tofu Liquid Waste (TLW) containing low COD and high total Nitrogen. Substrates were varied with volume ratio of VW:TLW of 100:0, 20:80, 0:100. Total volume of substrates was 250 mL. Anaerobic digesters were operated at room temperatur. After fermentation, biogas total volume of variables of 100:0, 20:80, 0:100 was 88.5; 125.5; 41.5 mL. Initial pH for all variables was 7.0. At the end of fermentation, pH substrates became 3.9; 5.1; 6.8 for variables of 100:0, 20:80, 0:100 respectively.


Sign in / Sign up

Export Citation Format

Share Document