Roasting process needs to be monitored and carefully controlled because it plays as the most important stage for determining flavor quality on the final product in the secondary coffee processing. Common quality monitoring method by applying parameters namely roasting time, roasting temperature and grain color may have disadvantages especially for nonuniform quality of green beans and stirring mechanism of regular roasters; therefore, an alternative quality monitoring model is necessary. Because emitted vapor during roasting may represent the occurred reaction stage, it is possible to indicate the roast degree of the coffee grain. This study evaluated the application of an electronic nose based on semiconductor sensor array for quality monitoring of coffee roasting. The electronic nose designed with gas sensor array was integrated to a mini batch coffee roaster. Data including sensor array response, vapor humidity and temperature were recorded in line to the roasting process and compared to the coffee grain color measured with a universal colorimeter. The experiment showed that the gas sensors respond to the emitted coffee flavors, from which a logarithmic profile as a function of grain color was obtained with the highest slope of [Formula: see text]1.6[Formula: see text]V/color difference of roasted coffee. Aroma patterns obtained from sensor responses were then analyzed with principle component analysis (PCA), by which a distinctive profile between initial and final phases of roasting is obtained. Although the corresponding analysis is still unable to distinguish the levels of light, medium and dark (LMD); high sensor responses indicate a further benefit of this system for developing an analogous quality monitoring system.

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The exhaled breath analysis is a procedure of measuring several types of gases that aim to identify various diseases in the human body. The purpose of this study is to analyze the gases contained in the exhaled breath in order to recognize healthy and asthma subjects with varying severity. An electronic nose consisting of seven gas sensors equipped with the Support Vector Machine classification method is used to analyze the gases to determine the patient's condition. Non-linear binary classification is used to identify healthy and asthma subjects, whereas the multiclass classification is applied to recognize the subjects of asthma with different severity. The result of this study showed that the system provided a low accuracy to distinguish the subjects of asthma with varying severity. This system can only differentiate between partially controlled and uncontrolled asthma subjects with good accuracy. However, this system can provide high sensitivity, specificity, and accuracy to distinguish between healthy and asthma subjects. The use of five gas sensors in the electronic nose system has the best accuracy in the classification results of 89.5%. The gases of carbon monoxide, nitric oxide, volatile organic compounds, hydrogen, and carbon dioxide contained in the exhaled breath are the dominant indications as biomarkers of asthma.The performance of electronic nose was highly dependent on the ability of sensor array to analyze gas type in the sample. Therefore, in further study we will employ the sensors having higher sensitivity to detect lower concentration of the marker gases.

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Salah satu masalah utama yang dihadapi Indonesia di bidang pertanian adalah berkurangnya lahan pertanian akibat beralih fungsi menjadi pemukiman. Dibutuhkan sebuah metode tanam di lahan sempit, salah satunya adalah hidroponik yang menggunakan media air untuk mengalirkan nutrisi yang dibutuhkan ke akar tanaman. Namun, metode ini masih memiliki beberapa kekurangan khususnya pada penggunaan air yang kurang efisien dan tingkat aerasi pada akar yang kurang maksimal. Aeroponik sebagai modifikasi dari hidroponik mulai banyak digunakan, yaitu bertanam dengan cara membiarkan akar tanaman tergantung bebas di udara. Pemberian nutrisi dilakukan dengan cara mengubah larutan nutrisi dari wujud cair menjadi kabut yang kemudian disemprotkan ke akar tanaman. Pada penelitian telah dirancang sebuah ruang tumbuh GrowBox yang dilengkapi dengan sebuah sistem kontrol yang mengatur penyemprotan larutan nutrisi ke akar tanaman, dan dilengkapi juga dengan pemantau temperatur dan kelembapan relatif dari ruang tumbuh melalui internet. Mikrokontroler yang digunakan adalah NodeMCU ESP8266 dengan modul sensor DHT22 sebagai sensor temperatur dan kelembapan relatif, sensor HC-SR04 untuk mendeteksi ketinggian air, ultrasonic atomizer sebagai pengubah wujud larutan nutrisi menjadi kabut, kipas DC sebagai pendistribusi kabut dan pompa DC untuk memompa larutan nutrisi. Hasil percobaan menunjukkan bahwa sensor DHT22 dapat mengukur kelembaban relatif dan temperatur GrowBox dengan error 1,54% dan menjadi sinyal perintah bagi aktuator untuk bekerja. Sensor HC-SR04 dapat mendeteksi level nutrisi dengan error 0,09 cm, dan ultrasonic atomizer dapat mengubah larutan nutrisi menjadi kabut yang dapat meningkatkan nilai kelembaban GrowBox yang dirancang sesuai nilai yang ditentukan yaitu 85%.