Encapsulated biochar-based sustained release fertilizer for precision agriculture: A review

Development of a carbon-based slow release fertilizer treated by bio-oil coating and study on its feedback effect on farmland application

Slow-release fertilizers based on starch acetate/glycerol/polyvinyl alcohol biocomposites for sustained nutrient release

Starch is one of the most common biodegradable polymers found in nature, and it is widely utilized in the food and beverage, bioplastic industry, paper industry, textile, and biofuel industries. Starch has received significant attention due to its environmental benignity, easy fabrication, relative abundance, non-toxicity, and biodegradability. However, native starch cannot be directly used due to its poor thermo-mechanical properties and higher water absorptivity. Therefore, native starch needs to be modified before its use. Major starch modification techniques include genetic, enzymatic, physical, and chemical. Among those, chemical modification techniques are widely employed in industries. This review presents comprehensive coverage of chemical starch modification techniques and genetic, enzymatic, and physical methods developed over the past few years. In addition, the current applications of chemically modified starch in the fields of packaging, adhesives, pharmaceuticals, agriculture, superabsorbent and wastewater treatment have also been discussed.

Development of Starch-Based Materials Using Current Modification Techniques and Their Applications: A Review.

Environmentally friendly hydrogel: A review of classification, preparation and application in agriculture.

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Cassava starch‐graft‐poly(acrylonitrile)‐coated urea fertilizer with sustained release and water retention properties

The Convolutional Neural Network CNN works by obtaining a picture and designating it with some weightage supported by the various objects of the image, to distinguish them from one another. CNN needs little or no pre-processing information as compared to different deep learning algorithms. Early diagnosis and correct identification of mango plant disease prediction will manage the unfolding of the diseases Mango leaf diseases damage mango quality and yield.This research uses deep learning to automatically identify leaf diseases in different mango plant kinds. The planned work is Associated with the Nursing correct identification approach for the mango plant disease prediction exploitation of the Convolutional Neural Network. It includes generating comfortable method pathological pictures Associate in nursing coming up with a model and a design of the Convolutional Neural Network to discover mango leaf diseases. The image augmentation method is employed to extend the number of images. completely different information augmentation techniques square measure applied to stop overfitting and improve generalization.

Mancharyamkunnath Aravind

Papers

Cassava starch‐graft‐poly(acrylonitrile)‐coated urea fertilizer with sustained release and water retention properties

Prediction of Mango Leaf Diseases using Convolutional Neural Network