Cover cropIn agriculture, cover crops are plants that are planted to cover the soil rather than for the purpose of being harvested. Cover crops manage soil erosion, soil fertility, soil quality, water, weeds, pests, diseases, biodiversity and wildlife in an agroecosysteman ecological system managed and shaped by humans. Cover crops can increase microbial activity in the soil, which has a positive effect on nitrogen availability, nitrogen uptake in target crops, and crop yields. Cover crops may be an off-season crop planted after harvesting the cash crop.
Energy cropEnergy crops are low-cost and low-maintenance crops grown solely for renewable bioenergy production (not for food). The crops are processed into solid, liquid or gaseous fuels, such as pellets, bioethanol or biogas. The fuels are burned to generate electrical power or heat. The plants are generally categorized as woody or herbaceous. Woody plants include willow and poplar, herbaceous plants include Miscanthus x giganteus and Pennisetum purpureum (both known as elephant grass).
CropA crop is a plant that can be grown and harvested extensively for profit or subsistence. When the plants of the same kind are cultivated at one place on a large scale, it is called a crop. Most crops are cultivated in agriculture or hydroponics. Crops may include macroscopic fungus (e.g. mushrooms) and marine macroalga (e.g. seaweed), some of which are grown in aquaculture. Most crops are harvested as food for humans or fodder for livestock. Some crops are gathered from the wild often in a form of intensive gathering (e.
Foundation modelsA foundation model (also called base model) is a large machine learning (ML) model trained on a vast quantity of data at scale (often by self-supervised learning or semi-supervised learning) such that it can be adapted to a wide range of downstream tasks. Foundation models have helped bring about a major transformation in how artificial intelligence (AI) systems are built, such as by powering prominent chatbots and other user-facing AI.
Machine visionMachine vision (MV) is the technology and methods used to provide -based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science.
