Proceedings
Authors
| Filter results5 paper(s) found. |
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1. A Non-Destructive Method of Estimating Red Tip Disease in PineappleRed Tip disease typically reduces pineapple yields by up to 50%. At present, the causal agent of Red Tip disease is still unconfirmed. B... F. Abu kassim, G. Vadamalai, A. Mohd hanif, S.K. Balasundram |
2. Artificial Neural Network Techniques To Predict Orange Spotting Disease In Oil PalmLarge-Scale oil palm plantations require timely detection of disease symptoms to enable effective intervention. Orange spotting is an emerging disease that significantly reduces oil palm productivity. Remote sensing technology offers the means to detect crop biophysical properties, including crop stress, in a cost effective and non destructive manner. In this study, different portable sensors were used to measure spectral reflectance and chlorophyll... S. Liaghat, S.K. Balasundram |
3. Application of Radio Frequency Identification Technology in Agriculture: a Case with Dragon FruitGlobal and local concerns about food safety are turning food traceability into a trade requirement. Typically, a Food Traceability Scheme (FTS) discloses information about food production and its distribution process. A reliable FTS will increase consumer trust in the quality and safety of farm produce. In Malaysia, dragon fruit is a profitable commodity that is growing in export value. Hence, dragon fruit is an excellent candidate for FTS solution development. ... S.K. Balasundram, M.H. Husni |
4. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural CropsAerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. G, D.P. Biradar, B.L. Desai, V.C. Patil, P. Patil, V.B. Nargund, V. Desai, W. John, S.M. Channangi, V. Tulasigeri |
5. Estimation of Crop Coefficient in Malaysian Durian Using Satellite Data and Machine LearningDurian (Durio zibethinus) is a popular fruit and key crop in Southeast Asia, known as the “King of Fruits” for its thorny exterior and distinctive aroma. The crop coefficient (Kc), based on crop evapotranspiration (ETc) and reference evapotranspiration (ETo), is crucial for water efficiency. Currently, there is no Kc value for Malaysian durian. This study introduces a machine learning method utilizing remote sensing data from Sentinel-1, Sentinel-3, and MODIS ET, combined with... S.K. Balasundram |