Detection of Colletotrichum Gloeosporioides Fungus Isolates Development/Spread for Mango (Mangifera Indica L.) Cultivar from Electronic Nose Using Multivariate-Statistical Analysis

Abstract

Agriculture plays a very important role in Asia economic sectors. For Malaysia, it plays a big contribution towards the country’s development. Mangifera Indica L., commonly known as Mango, is one of the fruit that has high economic demand and potential in Malaysia export business. However, due to radical climate changes from hot to humid, Mango is exposed towards a number of disease and this will affect its production. Colletotrichum gloeosporioides is one of the major diseases that could occur on any types of Mango. This fungus can attack on fruit skin and leaf, therefore a method that able to detect and control it would be much appreciated. Hence, this paper shows that the presence of Colletotrichum gloeosporioides type of pathogen can be detected by using Electronic Nose (E-Nose). The E-Nose will detect the Volatile Organic Compound (VOC) that produced from this fungus. Further analysis and justification on its existence are completed by using one of Multivariate-Statistical Analysis method which is Principal Component Analysis (PCA).The analysis results effectively show that the PCA is able to classify the number of isolating days of this type of fungus after cultured. Furthermore the potential of pre-symptomatic detection of the plant diseases was demonstrated.