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Study on Comparison of Biochemistry Between Trogoderma Granarium Everts and Trogoderma Variabile Ballion

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Study on Comparison of Biochemistry Between Trogoderma Granarium Everts and Trogoderma Variabile Ballion Study on Comparison of Biochemistry between Trogoderma granarium Everts and Trogoderma variabile Ballion This thesis is presented for the degree of Doctor of Philosophy at Murdoch University by THAMER ALSHUWAILI College of Science, Health, Engineering and Education Murdoch Murdoch University Perth, Western Australia December 2020 Declaration I declare that this thesis is my own account of my research and contains as its main content work, which has not previously been submitted for a degree at any tertiary education institution. Signature: T. ALSHUWAILI Date: 09/12/2020 ii Acknowledgments In the name of God Firstly, I would like to thank the Iraqi government and Kerbala university for providing me with the International Postgraduate Scholarship to pursue this exciting research and Murdoch University for providing the research materials and technical support. Then, I would like to acknowledgment my supervisors Dr. Manjree Agarwal and Professor Yonglin Ren for their support, guidance and their profound inspiration. I am thankful to them for their valuable suggestions and timely corrections of my thesis chapters. Thanks, are also due to Dr. Panghao wang (Supervisory Committee Chair) for his time and advice during all my study. Many thanks are passed to Mr. Bob Du Postharvest, Biosecurity and Food Safety Laboratory Murdoch University for his help with technical support with laboratory instruments and his patience and time, and many thanks for his help with GC-MS and GC-FID, equipment. I would like also to thank Dr. Dave Berryman from Western Australia state agricultural biotechnology center (SABC) for all the help on hyperspectral working. I would also like to thank my colleague, my friend and my teacher Ihab Alnajim, you were my best supporter during my stay in Australia. Thanks to all the staff and colleagues in Post-harvest Biosecurity and Food Safety Laboratory (PHBFSL), Farhan Elbehadili, Ahmed Auda, Nadia Hanoon, Amy Xiao, Junxi Li and Shuting Pan. I am also thankful to my relatives in Australia Mr. Muthana Alkhairallah and his family for their support and help through my study. I also gratefully pass my thanks to Mr. Mushtaq Talib from department of plant protection, college of agriculture, Kerbala University for his support and encouragement during my study. My deepest gratitude to my family, My Dad, My Mom, my brothers and My sisters for being a strong pillar of support during my study. I would also to thank my lovely wife Alaa and my lovely kids Dora and Abbas. They were always very patience and support me. I would not be typing this thesis without their support and their encouragement. iii Dedication This thesis is dedicated to My Dad and Mom My wife and kids Alaa, Dora and Abbas My brothers and sisters Without them none of my success would be possible Thamer Alshuwaili iv Abstract Stored grains are paramount commodities to be preserved and stocked for future supply to the market according to the requirement. However, one of the major problems during storage is insect pests, of which insects from Trogoderma sp. especially khapra beetle (Trogoderma granarium) is considered the world most dangerous stored grain insect pests. Therefore, it has been listed as quarantine insect pests in many counties. For timely management of quarantine pest, effective and rapid diagnostic methods are required. Until now, diagnostic technology is mainly based on morphology of insects which require trained taxonomists. Recently, diagnostics based on metabolites and hyperspectral imaging coupled with machine learning is gaining importance. However, very little is known about the metabolites in Trogoderma sp. and how the host grain, gender, and geographical distribution affect the metabolomic profiling in these species is still unknown. In this thesis, volatile organic compounds (VOCs) emitted by Trogoderma variabile at different life stages were analysed as biomarkers which can help us to understand the biochemistry and metabolomic. Some compounds were identified from T. variabile different stages, which could be used as diagnostic tool for this insect. Gas chromatography coupled to mass spectrometry (GC–MS) was used as a technique to study the metabolite profile of T. variabile in different host grains. However, there are several factors that affect the volatile organic compounds including extraction time and number of insects. The results indicated that the optimal number of insects required for volatile organic compounds (VOC) extraction at each life stage was 25 and 20 for larvae and adults respectively. Sixteen hours were selected as the optimal extraction time for larvae and adults. Some of the VOCs compounds identified from this insect can be used as biomarkers such as pentanoic acid; diethoxymethyl acetate; 1-decyne; naphthalene, 2- methyl-; n-decanoic acid; dodecane, 1-iodo- and m-camphorene from larvae. While butanoic acid, 2-methyl-; pentanoic acid; heptane, 1,1'-oxybis- 2(3H)-Furanone, 5-ethyldihydro-; pentadecane, 2,6,10-trimethyl-; and 1,14-tetradecanediol VOCs, were found in male, whereas pentadecane; nonanic acid; pentadecane, 2,6,10-trimethyl-; undecanal and hexadecanal were identified from female. Additionaly, direct immersion-solid phase microextraction (DI-SPME) was employed, followed by gas chromatography mass spectrometry analysis (GC-MS) for the collection, v separation, and identification of the chemical compounds from T. variabile adults fed on four different host grains. Results showed that insect host grains have a significant difference on the chemical compounds that were identified from female and male. There were 23 compounds identified from adults reared on canola and wheat. However, there were 26 and 28 compounds detected from adults reared on oats and barley respectively. Results showed that 11- methylpentacosane; 13-methylheptacosane; heptacosane; docosane, 1-iodo- and nonacosane were the most significant compounds that identified form T. variabile male reared on different host grains. However, the main compounds identified from female cultured on different host grains include docosane, 1-iodo-; 1-butanamine, N-butyl-; oleic acid; heptacosane; 13- methylheptacosane; hexacosane; nonacosane; 2-methyloctacosane; n-hexadecanoic acid and docosane. A novel diagnostic tool to identify between T. granarium and T. variabile were developed using visible near infrared hyperspectral imaging and deep learning models including Convolutional Neural Networks (CNN) and Capsule Network. Ventral orientation showed a better accuracy over dorsal orientation of the insects for both larvae and adult stages. This technology offers a new approach and possibility of an effective identification of T. granarium and T. variabile. from its body fragments and larvae skins. The results showed high accuracy to identify between T. granarium and T. variabile. The accuracy was 93.4 and 96.2% for adults and larvae respectively, and the accuracies of 91.6, 91.7 and 90.3% were achieved for larvae skin, adult fragments, larvae fragment respectively. vi Table of contents Declaration ............................................................................................................................................... ii Acknowledgments ................................................................................................................................... iii Dedication ................................................................................................................................................ iv Abstract ..................................................................................................................................................... v Table of contents .................................................................................................................................... vii List of tables .............................................................................................................................................. x List of figures .......................................................................................................................................... xi Publications ........................................................................................................................................... xiii List of Abbreviations ............................................................................................................................ xiv Chapter One .......................................................................................................................................... 1 General Introduction and Literature Review .................................................................................... 1 1.1. General Introduction ................................................................................................................... 2 1.1.1. Grains .............................................................................................................................................. 4 1.1.2. Stored grain insects......................................................................................................................... 5 1.1.3. Management control of stored grain insects ................................................................................ 6 1.1.3.1. Chemical control .......................................................................................................................... 7 1.1.3.2. Biological control ........................................................................................................................
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