Volatiles as an indicator of fungal activity and differentiation between species, and the potential use of electronic nose technology for early detection of grain spoilage

Rail foot flaws have the potential to cause broken rails that can lead to derailment. This is not only an extremely costly issue for a rail operator in terms of damage to rolling stock, but has significant flow-on effects for network downtime and a safe working environment. In Australia, heavy haul operators run up to 42.5 t axle loads with trains in excess of 200 wagons and these long trains produce very large cyclic rail stresses. The early detection of foot flaws before a broken rail occurs is of high importance and there are currently no proven techniques for detecting rail foot flaws on trains at normal running speeds. This paper shall focus on the potential use of thermography as a detection technique and begin investigating the components of heat transfer in the rail to determine the viability of thermography for detecting rail foot flaws. The paper commences with an introduction to the sources of heat generation in the rail and modelling approaches for the effects of bending, natural environmental factors and transverse defects. It concludes with two theoretical case studies on heat generated due to these sources and discusses how they may inform the development of a practical thermography detection methodology.

Download Full-text

Deteksi Formalin Pada Buah Tomat (Lycopersicum esculentum Mill) Dengan Teknologi Hidung Elektronik (Electronic Nose)

Jurnal Ilmiah Mahasiswa Pertanian ◽

10.17969/jimfp.v4i2.10935 ◽

2019 ◽

Vol 4 (2) ◽

pp. 359-366

Author(s):

Irfan Maibriadi ◽

Ratna Ratna ◽

Agus Arip Munawar

Keyword(s):

Principal Component Analysis ◽

Electronic Nose ◽

Principal Component ◽

Component Analysis ◽

Lycopersicum Esculentum ◽

Olfactory Ability ◽

Pca Method ◽

The Difference ◽

Electronic Nose Technology

Abstrak, Tujuan dari penelitian ini adalah mendeteksi kandungan dan kadar formalin pada buah tomat dengan menggunakan instrument berbasis teknologi Electronic nose. Penelitian ini menggunakan buah tomat yang telah direndam dengan formalin dengan kadar 0.5%, 1%, 2%, 3%, 4%, dan buah tomat tanpa perendaman dengan formalin (0%). Jumlah sampel yang digunakan pada penelitian ini adalah sebanyak 18 sampel. Pengukuran spektrum beras menggunakan sensor Piezoelectric Tranducer. Klasifikasi data spektrum buah tomat menggunakan metode Principal Component Analysis (PCA) dengan pretreatment nya adalah Gap Reduction. Hasil penelitian ini diperoleh yaitu: Hidung elektronik mulai merespon aroma formalin pada buah tomat pada detik ke-8.14, dan dapat mengklasifikasikan kandungan dan kadar formalin pada buah tomat pada detik ke 25.77. Hidung elektronik yang dikombinasikan dengan metode principal component analysis (PCA) telah berhasil mendeteksikandungan dan kadar formalin pada buah tomat dengan tingkat keberhasilan sebesar 99% (PC-1 sebesar 93% dan PC-2 sebesar 6%). Perbedaan kadar formalin menjadi faktor utama yang menyebabkan Elektronik nose mampu membedakan sampel buah tomat yang diuji, karena semakin tinggi kadar formalin pada buah tomat maka aroma khas dari buah tomat pun semakin menghilang, sehingga Electronic nose yang berbasis kemampuan penciuman dapat membedakannya.Detect Formaldehyde on Tomato (Lycopersicum esculentum Mill) With Electronic Nose TechnologyAbstract, The purpose of this study is to detect the contents and levels of formalin in tomatoes by using instruments based on Electronic nose technology. This study used tomatoes that have been soaked in formalin with a concentration of 0.5%, 1%, 2%, 3%, 4%, 5% and tomatoes without soaking with formalin (0%). The samples in this study were 18 samples. The measurements of the intensity on tomatoes aroma were using Piezoelectric Transducer sensors. The classification of tomato spectrum data was using the Principal Component Analysis (PCA) method with Gap Reduction pretreatment. The results of this study were obtained: the Electronic nose began to respond the smell of formalin on tomatoes at 8.14 seconds, and it could classify the content and formalin levels in tomatoes at 25.77 seconds. Electronic nose combined with the principal component analysis (PCA) method have successfully detected the content and levels of formalin in tomatoes with a success rate at 99% (PC-1 of 93% and PC-2 of 6%). The difference of grade formalin levels is the main factor that causes Electronic nose to be able to distinguish the tomato samples tested, because the higher of formalin content in tomatoes, the distinctive of tomatoes aroma is increasingly disappearing. Thereby, the Electronic nose based on the olfactory ability can distinguish them.

Download Full-text