Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Sousa, M. (2025). Artificial Intelligence in Agriculture: Revolutionizing Methods and Practices in Portugal. In Economic Sustainability Potentiated by Artificial Intelligence. (pp. 49-70). Singapura: springer.
Exportar Referência (IEEE) 
M. J. Sousa,  "Artificial Intelligence in Agriculture: Revolutionizing Methods and Practices in Portugal", in Economic Sustainability Potentiated by Artificial Intelligence, Singapura, springer, 2025, pp. 49-70
Exportar BibTeX 
@incollection{sousa2025_1777703118052,
	author = "Sousa, M.",
	title = "Artificial Intelligence in Agriculture: Revolutionizing Methods and Practices in Portugal",
	chapter = "",
	booktitle = "Economic Sustainability Potentiated by Artificial Intelligence",
	year = "2025",
	volume = "",
	series = "",
	edition = "",
	pages = "49-49",
	publisher = "springer",
	address = "Singapura",
	url = "https://link.springer.com/chapter/10.1007/978-981-96-8089-4_4#citeas"
}
Exportar RIS 
TY  - CHAP
TI  - Artificial Intelligence in Agriculture: Revolutionizing Methods and Practices in Portugal
T2  - Economic Sustainability Potentiated by Artificial Intelligence
AU  - Sousa, M.
PY  - 2025
SP  - 49-70
DO  - 10.1007/978-981-96-8089-4_4
CY  - Singapura
UR  - https://link.springer.com/chapter/10.1007/978-981-96-8089-4_4#citeas
AB  - As a result of ongoing technical breakthroughs, artificial intelligence (AI) has become an important topic for researchers and industry experts. The creation of machines that mimic human cognitive functions including learning, reasoning, and self-correction is referred to as artificial intelligence (AI). Its numerous uses in various industries have demonstrated its growing accuracy and effectiveness, and agriculture has likewise embraced AI to boost productivity and revenue. In order to fully comprehend the idea, current research, and projects related to AI in agriculture, a review of the literature was conducted. Additionally, this paper takes a practical approach to the potential of AI in agriculture by addressing the emergence of new techniques and practices, utilizing a case study approach, and examining how experts, academics, and agriculture professionals perceive the application of AI in agriculture. It helps build practical applications by providing insights that are relevant to both academic and real-world contexts.
ER  -