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undergraduate thesis
Utjecaj strojnog učenja u aplikaciji pesticida
2023. urn:nbn:hr:151:849135
Zorko, Luka
Josip Juraj Strossmayer University of Osijek
Faculty of Agrobiotechnical Sciences Osijek
Department of Agricultural Engineering and Renewable Energy Resources

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Zorko, L. (2023). Utjecaj strojnog učenja u aplikaciji pesticida (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:151:849135

Zorko, Luka. "Utjecaj strojnog učenja u aplikaciji pesticida." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:151:849135

Zorko, Luka. "Utjecaj strojnog učenja u aplikaciji pesticida." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:151:849135

Zorko, L. (2023). 'Utjecaj strojnog učenja u aplikaciji pesticida', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, accessed 24 March 2025, https://urn.nsk.hr/urn:nbn:hr:151:849135

Zorko L. Utjecaj strojnog učenja u aplikaciji pesticida [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek; 2023 [cited 2025 March 24] Available at: https://urn.nsk.hr/urn:nbn:hr:151:849135

L. Zorko, "Utjecaj strojnog učenja u aplikaciji pesticida", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:151:849135

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Metadata
TitleUtjecaj strojnog učenja u aplikaciji pesticida
Title (english)Impact of machine learning in pesticide application
AuthorLuka Zorko
MentorDomagoj Zimmer (mentor)
Committee memberLuka Šumanovac (predsjednik povjerenstva)
Committee memberTomislav Jurić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Agrobiotechnical Sciences Osijek
(Department of Agricultural Engineering and Renewable Energy Resources)
Osijek
Defense date and country2023-11-24, Croatia
Scientific / art field,
discipline and subdiscipline		BIOTECHNICAL SCIENCES
Agronomy
Agricultural Engineering and Technology
Abstract
Umjetna inteligencija područje je koje se danas primjenjuje u različitim sektorima među kojima je upravo i poljoprivreda. Tumači se kako umjetna inteligencija, odnosno strojno učenje, mogu revolucionirati poljoprivredu koja utječe na gospodarstvo zemlje, izravno ili neizravno zapošljavajući više od 30 % svjetskog stanovništva. Automatizacijom se na taj način mogu zadovoljiti potrebe sve većeg svjetskog stanovništva. Gledajući tradicionalne prakse na području poljoprivrede kao što su primjerice... More kultivacija, prskanje pesticidima, praćenje statusa hranjivih tvari i drugo, navedene se mogu značajno brže izvesti putem korištenja umjetne inteligencije i strojnog učenja. Zahvaljujući navedenom dolazi do osiguranja smanjenja rasipanja vode, prekomjerne uporabe pesticida, pomoći u smanjenju rada, ali ujedno dolazi do povećanja plodnosti tla, a samim time i usjeva. Primjena umjetne inteligencije i strojnog učenja u poljoprivredi je još u razvoju zbog nedostatnosti stručnosti i zahtjeva za točnost velikih podataka. Ono što je za očekivati je kako će područje strojnog učenja i uporabe umjetne inteligencije u poljoprivredi u budućnosti i dalje rasti. Cilj ovog rada je konkretno usmjeren na utjecaj strojnog učenja pri aplikaciji pesticida. Less
Abstract (english)
Artificial intelligence is a field that is applied today in various sectors, one of which is agriculture. It is interpreted as how artificial intelligence, or machine learning, can revolutionize agriculture, which affects the country's economy, directly or indirectly employing more than 30 % of the world's population. Automation can thus meet the needs of the ever-increasing world population. Looking at traditional practices in the field of agriculture such as weeding, spraying with... More pesticides, monitoring the status of nutrients and others, the above can be performed significantly faster through the use of artificial intelligence and machine learning. Thanks to the above, there is a reduction in water wastage, excessive use of pesticides, help in reducing work, but at the same time there is an increase in the fertility of the soil, and thus the crops. The application of artificial intelligence and machine learning in agriculture is still in development due to the lack of expertise and requirements for the accuracy of big data. What can be expected is that the field of machine learning and the use of artificial intelligence in agriculture will continue to grow in the future. The goal of this paper is specifically focused on the influence of machine learning in the application of pesticides. Less
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:151:849135
Study programmeTitle: Agriculture; specializations in: Agroeconomics, Plant production, Mechanization, Zootechnique, Horticulture
Course: Mechanization
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka agronomije (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka agronomije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Public notezavršni rad
Created on2024-03-12 07:52:14
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