• BH.SUJITH VARMA

Seeds, as living products, require proper cultivation, harvesting, and processing to optimize their viability and crop productivity. Chemical and physical techniques have proven to be effective and reliable, with high accuracy rates. However, these techniques are often accompanied by certain drawbacks such as high costs, extended processing times, and a requirement for skilled operators. To overcome these limitations, alternative approaches are being explored, including the use of machine learning algorithms and image analysis techniques. These innovative methods have the potential to significantly improve the efficiency, speed, and accuracy of seed quality assessment while reducing the need for manual intervention.. Non-destructive technologies are rapid, accurate, reliable, and simple methods for assessing the quality of the seeds. Some research based on image processing and analysis has been explored in terms of the assessing external and internal quality of a variety of seeds. Another important aspect of agricultural productivity is detection and elimination of diseases during growth period. Generally, leaves are the most effected part during a disease since they are food factories to plants/crops. This can cause a significant decline in production if the disease is not identified and eliminated. Research supports that detection of these diseases can be done easily by employing machine vision where there is less scope for error. Hence, we aim to develop a model using the above-mentioned techniques which can be used to assess the quality of seeds, and a model for prediction of leaf disease.

"SEED QUALITY ASSESMENT AND LEAF DISEASE DETECTION THROUGH NON DESTRUCTIVE TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.j799-j803, June-2023, Available :http://www.jetir.org/papers/JETIR2306995.pdf

"SEED QUALITY ASSESMENT AND LEAF DISEASE DETECTION THROUGH NON DESTRUCTIVE TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. ppj799-j803, June-2023, Available at : http://www.jetir.org/papers/JETIR2306995.pdf