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How Artificial Intelligence Can Support Modern Horticulture?

cris.virtual.author-orcid0000-0002-0102-0084
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid51a5a68b-106b-4e9d-bd9b-79d15d3ec0c1
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.abstract.enModern horticulture faces increasing challenges related to the rising demand for high-quality crops, limited environmental resources, and the need for improved production efficiency. Artificial intelligence (AI), encompassing machine learning, deep learning, and advanced analysis of sensor and image data, offers significant potential to support decision-making and automation in plant cultivation systems. The aim of this manuscript is to examine current and emerging applications of AI in horticulture, with particular emphasis on disease and stress detection, microclimate control in controlled-environment agriculture, robotic harvesting, and the enhancement of breeding programs. A review of scientific literature and industrial deployment cases demonstrates that AI can contribute to improved precision of cultivation practices, reduction of production losses, and more sustainable resource management. However, several challenges remain, including data standardization, model interpretability, and the economic feasibility of implementation. The findings highlight that further development of AI applications in horticulture requires close collaboration between researchers, practitioners, and technology providers, as well as progress in digital infrastructure and agronomic competence-building.
dc.affiliationWydział Rolnictwa, Ogrodnictwa i Biotechnologii
dc.affiliation.instituteKatedra Metod Matematycznych i Statystycznych
dc.contributor.authorBocianowski, Jan
dc.contributor.authorLeśniewska-Bocianowska, Agnieszka
dc.date.access2025-11-27
dc.date.accessioned2025-11-27T13:44:25Z
dc.date.available2025-11-27T13:44:25Z
dc.date.copyright2025-11-24
dc.date.issued2025
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.number1
dc.description.points5
dc.description.versionfinal_published
dc.description.volume6
dc.identifier.doi10.19080/JOJHA.2025.06.555676
dc.identifier.issn2641-8215
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/6156
dc.identifier.weblinkhttps://juniperpublishers.com/jojha/volume6-issue1-jojha.php
dc.languageen
dc.pbn.affiliationagriculture and horticulture
dc.relation.ispartofJOJ Horticulture & Arboriculture
dc.relation.pagesart. 555676
dc.rightsCC-BY
dc.sciencecloudnosend
dc.share.typeOPEN_JOURNAL
dc.subject.enartificial intelligence
dc.subject.enconvolutional neural network
dc.subject.enrecurrent neural network
dc.subject.enclassification algorithms
dc.titleHow Artificial Intelligence Can Support Modern Horticulture?
dc.typeJournalArticle
dspace.entity.typePublication