Patent classifications
A01G22/00
Method for cultivation of hybrid mint plant designated 13-S12-2 for production of essential oil composition
A hybrid mint plant characterized by an essential oil composition profile, methods of cultivating the hybrid mint plant, and methods of producing an essential oil composition with the essential oil composition profile using the hybrid mint plant are disclosed.
Modular Precision Agriculture System
A modular system includes a hub and a set of modules removably coupled to the hub. The modules are physically coupled to the frame relative to each other so that each module can operate with respect to a different row of a field. An individual module includes a sensor for capturing field measurement data of individual plants along a row as the modular system moves through the geographic region. An individual module further includes a treatment mechanism for applying a treatment to the individual plants of the row based on the field measurement data before the modular system passes by the individual plants. An individual module further includes a computing device that determines the treatment based on the field measurement data and communicates data to the hub. The hub is communicatively coupled to the modules, so that it may exchange data between the modules and with a remote computing system.
Modular Precision Agriculture System
A modular system includes a hub and a set of modules removably coupled to the hub. The modules are physically coupled to the frame relative to each other so that each module can operate with respect to a different row of a field. An individual module includes a sensor for capturing field measurement data of individual plants along a row as the modular system moves through the geographic region. An individual module further includes a treatment mechanism for applying a treatment to the individual plants of the row based on the field measurement data before the modular system passes by the individual plants. An individual module further includes a computing device that determines the treatment based on the field measurement data and communicates data to the hub. The hub is communicatively coupled to the modules, so that it may exchange data between the modules and with a remote computing system.
CANNABIS FARMING METHODS
Methods to grow cannabis plants within an interior of an enclosure are described, the method comprises condensing water vapor from the interior of the enclosure to produce a source of liquid water and supplying the liquid water to the cannabis plants. The source of liquid water may be supplied to a common reservoir and then transferred to the cannabis plants. The common reservoir includes fish, a microorganism, or treated water. Water drained from the cannabis plants may be recycled back to the common reservoir. The water may be filtered or oxygenated and mixed with a pH adjustment solution, a macro-nutrient, a micro-nutrient, a carbohydrate, an enzyme, or a vitamin. Solar panels may be used to provide electricity for electrically powered lights that illuminate the cannabis plants. The cannabis plants may be grown within a growing medium, harvested, trimmed, ground, heated, and made into multifunctional compositions or foodstuffs.
CANNABIS FARMING METHODS
Methods to grow cannabis plants within an interior of an enclosure are described, the method comprises condensing water vapor from the interior of the enclosure to produce a source of liquid water and supplying the liquid water to the cannabis plants. The source of liquid water may be supplied to a common reservoir and then transferred to the cannabis plants. The common reservoir includes fish, a microorganism, or treated water. Water drained from the cannabis plants may be recycled back to the common reservoir. The water may be filtered or oxygenated and mixed with a pH adjustment solution, a macro-nutrient, a micro-nutrient, a carbohydrate, an enzyme, or a vitamin. Solar panels may be used to provide electricity for electrically powered lights that illuminate the cannabis plants. The cannabis plants may be grown within a growing medium, harvested, trimmed, ground, heated, and made into multifunctional compositions or foodstuffs.
Lawn Amendment and Packaging
Embodiments of the invention are biodegradable pods containing materials to repair damaged turf (lawns, fields). Each pod is sized and configured to repair an area ranging in size from about 9 square inches to about 36 square inches (60 cm.sup.2 to 230 cm.sup.2). The pods contain granulated ingredients including fertilizer, grass seed, gypsum, humic acid and calcium, in a material that expands when moistened. The pods are covered with a water-disruptable covering such as a polyvinyl alcohol film or a biodegradable paper.
Lawn Amendment and Packaging
Embodiments of the invention are biodegradable pods containing materials to repair damaged turf (lawns, fields). Each pod is sized and configured to repair an area ranging in size from about 9 square inches to about 36 square inches (60 cm.sup.2 to 230 cm.sup.2). The pods contain granulated ingredients including fertilizer, grass seed, gypsum, humic acid and calcium, in a material that expands when moistened. The pods are covered with a water-disruptable covering such as a polyvinyl alcohol film or a biodegradable paper.
Modeling and prediction of below-ground performance of agricultural biological products in precision agriculture
A below-ground agricultural biological performance modeling approach in precision agriculture combines customized field modeling with machine learning techniques for environmental matching of variables to describe a below-surface soil state, to understand and predict the performance of soil-active agricultural biological products such as bio-pesticides, bio-stimulants, plant growth regulators, and other biologically-derives soil adjuvants. The modeling approach characterizes the influence of environmental relationships on the performance of such soil-active agricultural biological products to develop a suite of predictive models to provide notifications, advisories, and recommendations for appropriate products for individual fields.
Modeling and prediction of below-ground performance of agricultural biological products in precision agriculture
A below-ground agricultural biological performance modeling approach in precision agriculture combines customized field modeling with machine learning techniques for environmental matching of variables to describe a below-surface soil state, to understand and predict the performance of soil-active agricultural biological products such as bio-pesticides, bio-stimulants, plant growth regulators, and other biologically-derives soil adjuvants. The modeling approach characterizes the influence of environmental relationships on the performance of such soil-active agricultural biological products to develop a suite of predictive models to provide notifications, advisories, and recommendations for appropriate products for individual fields.
IoT-based farming and plant growth ecosystem
An agricultural method includes providing a positive air pressure chamber to prevent outside contaminants from entering the chamber; growing crops in a plurality of cells in the chamber, each cell having multi-grow benches or levels, each cell further having connectors to vertical hoists for vertical movements in the chamber; maintaining pre-set temperature, humidity, carbon dioxide, watering and lighting levels to achieve predetermined plant growth; using motorized transport rails to deliver benches for operations including seeding, harvesting, grow media recovery, and bench wash; dispensing seeds in the cell with a mechanical seeder coupled to the transport rails; growing the crops with computer controlled nutrients, light and air level; and harvesting the crops and delivering the harvested crop at a selected outlet of the chamber.