Ammonia and ethanol detection via an electronic nose utilizing a bionic chamber and a sparrow search algorithm–optimized backpropagation neural network DOI Creative Commons

Yeping Shi,

Yunbo Shi,

Haodong Niu

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(12), P. e0309228 - e0309228

Published: Dec. 3, 2024

Ammonia is widely acknowledged to be a stressor and one of the most detrimental gases in animal enclosures. In livestock- poultry-breeding facilities, precise, rapid, affordable method for detecting ammonia concentrations essential. We design develop an electronic nose system containing bionic chamber that imitates nasal-cavity structure humans canines. The sensors are positioned based on fluid simulation results. Response data ethanol response/ recovery times sensor under three collected using system. classified regressed sparrow search algorithm (SSA)-optimized backpropagation neural network (BPNN). results show has relative mean deviation 1.45%. sensor’s output voltage 1.3–2.05 V when concentration ranges from 15 300 ppm. gas 1.89–3.15 8 200 average response time 13 s slower than directly exposed being measured, while 19 faster. tests comparing performance SSA-BPNN, support vector machine (SVM), random forest (RF) models, SSA-BPNN achieves 99.1% classification accuracy, better SVM RF models. It also outperforms other models at regression prediction, with smaller absolute, root square errors. Its coefficient determination (R 2 ) greater 0.99, surpassing those theoretical experimental both indicate proposed chamber, used offers promising approach facilities.

Language: Английский

The sensitivity of chitosan/TiO2 film on ammonia detection DOI Creative Commons
Irwana Nainggolan,

Widya Tri Wadana,

Tulus Ikhsan Nasution

et al.

Materials Today Proceedings, Journal Year: 2024, Volume and Issue: unknown

Published: March 1, 2024

Ammonia (NH3) is a toxic gas from various sources, including industrial waste, agriculture, and other human activities. The high concentration can cause negative impacts on air, water, soil quality harm health ecosystems. objective of this research was to detect ammonia based chitosan-CS/titanium dioxide-TiO2 film. CS solution supplemented with TiO2 in quantities ranging 0.01 g 0.05 g, increments g. formed films were characterized using FTIR SEM, the sensing characteristic CS/TiO2 film-based sensor tested by varying concentrations (1.5, 3, 4.5, 6, 7.5) mg/L. SEM analytical results indicated that loading process proceeded only through physical interaction. test demonstrate CS-TiO2 has higher maximum output voltage (0.223 V) than (0.078 when exposed 7.5 mg/L ammonia. From testing results, it found adding 0.02 have good sensitivity, selectivity, reproducibility, fast response, compared sensors. However, inversely proportional lifetime test. Finally, be concluded Cs/TiO2 used for detection.

Language: Английский

Citations

0
Complementary assessment of nano‐packaged garlic properties by electronic nose DOI Creative Commons
Alireza Makarichian, Ebrahim Ahmadi, Reza Amiri Chayjan

et al.

Food Science & Nutrition, Journal Year: 2024, Volume and Issue: 12(7), P. 5087 - 5099

Published: April 9, 2024

It is crucial to initiate appropriate storage conditions for garlic depending on its properties. Fungal contamination can reduce the quality of through changes in properties which result aroma alteration. This study aimed evaluate effects treatments such as fungal infection (FI), material packaging (MP), and duration (SD) various characteristics garlic. An electronic nose was used complementarily trace a non-destructive indicator. The

Language: Английский

Citations

0
Potential of eNose Technology for Monitoring Biological CO2 Conversion Processes DOI
Muhammad Awais, Syed Muhammad Zaigham Abbas Naqvi, Sami Ullah Khan

et al.

Transactions of Tianjin University, Journal Year: 2024, Volume and Issue: 30(5), P. 381 - 394

Published: Aug. 30, 2024

Language: Английский

Citations

0
Ammonia and ethanol detection via an electronic nose utilizing a bionic chamber and a sparrow search algorithm–optimized backpropagation neural network DOI Creative Commons

Yeping Shi,

Yunbo Shi,

Haodong Niu

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(12), P. e0309228 - e0309228

Published: Dec. 3, 2024

Ammonia is widely acknowledged to be a stressor and one of the most detrimental gases in animal enclosures. In livestock- poultry-breeding facilities, precise, rapid, affordable method for detecting ammonia concentrations essential. We design develop an electronic nose system containing bionic chamber that imitates nasal-cavity structure humans canines. The sensors are positioned based on fluid simulation results. Response data ethanol response/ recovery times sensor under three collected using system. classified regressed sparrow search algorithm (SSA)-optimized backpropagation neural network (BPNN). results show has relative mean deviation 1.45%. sensor’s output voltage 1.3–2.05 V when concentration ranges from 15 300 ppm. gas 1.89–3.15 8 200 average response time 13 s slower than directly exposed being measured, while 19 faster. tests comparing performance SSA-BPNN, support vector machine (SVM), random forest (RF) models, SSA-BPNN achieves 99.1% classification accuracy, better SVM RF models. It also outperforms other models at regression prediction, with smaller absolute, root square errors. Its coefficient determination (R 2 ) greater 0.99, surpassing those theoretical experimental both indicate proposed chamber, used offers promising approach facilities.

Language: Английский

Citations

0