Webservices für die teilschlagspezifische Bereitstellung ökologischer und ökonomischer Kennzahlen und Basisinformationen im Pflanzenschutz

Sinn, Christoph; Pohl, Jan-Philip; Jahncke, Daniel; Golla, Burkhard

doi:10.5073/jfk.2021.05-06.07

Cited by 2 publications

(1 citation statement)

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“…Specific data from the digitalized bug traps, farmspecific crops, and general pest control information will be provided to the tablet or mobile application that serves as an interface between the user and the digital pest management DSS. As a result, the DSS includes data on the crop that was grown, pest organisms, such as types of pests and their damage thresholds, and pest management chemicals, including usage guidelines and application rates [86].…”

Section: Current Approaches and Achievements Of Ai In Horticulturementioning

confidence: 99%

Revolutionary Technologies in Horticultural Crops: A Review

Kale,

Sahrawat,

Sangwan

et al. 2024

J. Adv. Biol. Biotechnol.

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Globally, the topic of agricultural automation is becoming more and more popular. Crop management system enables the systematic management of crops, incorporating all aspects of farming. India offers the opportunity to grow a wide variety of horticultural crops due to its diverse soil and climate conditions as well as its varied agro-ecological regions. These crops enhance farm output, generate employment opportunities, and supply raw materials to a variety of food-processing industries, all of which have a substantial positive economic impact on India. Although very little area is set specifically for horticulture, there is a strong demand for the production of horticulture crops. As a result, it can be difficult to meet demand with the least amount of resources. However, this can be done by introducing revolutionary technological interventions, such as nuclear technology, artificial intelligence, blockchain technology, Internet of Things technological interventions, remote sensing, various breeding programs, hydroponics systems, and others. Remote sensing technologies for monitoring and recognizing plants, weeds, pests, and diseases have been developed and used by means of recent advancements in computer vision, robotics, artificial intelligence, and machine learning. Numerous studies examine the new digital tools and services that farmers may use to purchase inputs, handle their money, and obtain input-output pricing and farm management data.

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Section: Current Approaches and Achievements Of Ai In Horticulturementioning

confidence: 99%