Data set for non-infused aroma-based quality identification of Gambung green tea using electronic nose
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This experiment focuses on the analysis of green tea aroma using a set of gas sensors. Specifically, the gas sensors selected for this research are the TGS822, TGS2602, TGS2620, MQ138, MQ5, and MQ3. The experiment involved testing a total of 78 different tea samples (chops), with each sample being observed three times. To conduct the experiment, a tea chamber was utilized, capable of accommodating 125 grams of dry green tea. The tea chamber was connected to a sensor chamber through a hose and intake micro air pump. During data acquisition, air from the tea chamber flowed into the sensor chamber for a duration of 60 seconds. Once the airflow from the tea sample was complete, the gas sensors recorded the aroma data for 60 seconds, resulting in 60 data records. These records were then saved into a CSV file for further processing and labeli' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Non-infused, aroma, Gambung green tea, e-nose, machine learning, hyperparameter optimization"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This experiment focuses on the analysis of green tea aroma using a set of gas sensors. Specifically, the gas sensors selected for this research are the TGS822, TGS2602, TGS2620, MQ138, MQ5, and MQ3. The experiment involved testing a total of 78 different tea samples (chops), with each sample being observed three times. To conduct the experiment, a tea chamber was utilized, capable of accommodating 125 grams of dry green tea. The tea chamber was connected to a sensor chamber through a hose and intake micro air pump. During data acquisition, air from the tea chamber flowed into the sensor chamber for a duration of 60 seconds. Once the airflow from the tea sample was complete, the gas sensors recorded the aroma data for 60 seconds, resulting in 60 data records. These records were then saved into a CSV file for further processing and labeli' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This experiment focuses on the analysis of green tea aroma using a set of gas sensors. Specifically, the gas sensors selected for this research are the TGS822, TGS2602, TGS2620, MQ138, MQ5, and MQ3. The experiment involved testing a total of 78 different tea samples (chops), with each sample being observed three times. To conduct the experiment, a tea chamber was utilized, capable of accommodating 125 grams of dry green tea. The tea chamber was connected to a sensor chamber through a hose and intake micro air pump. During data acquisition, air from the tea chamber flowed into the sensor chamber for a duration of 60 seconds. Once the airflow from the tea sample was complete, the gas sensors recorded the aroma data for 60 seconds, resulting in 60 data records. These records were then saved into a CSV file for further processing and labeli
Non-infused, aroma, Gambung green tea, e-nose, machine learning, hyperparameter optimization