Proceedings :: International Society of Precision Agriculture

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Mendes Gaya Lopes dos Santos, I

Pereira, C.E

Peixoto, A.S

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Authors

Videira Menezes, J

Dias, E.M

Rebello Pinho Dias Scoton, M.L

Oliveira, D.H

Mendes Gaya Lopes dos Santos, I

Stallivieri, F

Cunha de Sousa, L

Gallo, B.B

Visintainer Lerman, L

da Silva, R.F

Bolfe, E

da Silva, M.M

Alves, T

Pereira, C.E

Porcino, T.M

Karasinski, M.A

Bendahan, A.B

Jorge, L.A

Gabriel da Silva Carmo , I.L

Barreto, G.F

Peixoto, A.S

Dantas Oliveira, S.V

Thomé Barbosa, R.N

Schurt, D.A

Topics

Precision Agriculture for Sustainability and Environmental Protection

Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture

Type

Oral

Poster

Year

2026

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Filter results3 paper(s) found.
1. Embrapii: What Can We Learn About Precision Agriculture and Environmental Sustainability After Investments of US$100 Million+ in Agricultural Industrial Innovation in Brazil? Innovation policies have increasingly targeted digital and sustainable transformation, yet systematic assessments of large-scale public-private investments in precision agriculture innovation remain scarce, particularly in tropical contexts. This article analyzes the experience of Embrapii (Brazilian Agency for Research and Industrial Innovation) after fostering more than US$100 million in investments in over 600 research, development, and innovation (RD&I) projects applied to agriculture... J. Videira Menezes, E.M. Dias, M.L. Rebello Pinho Dias Scoton, D.H. Oliveira, I. Mendes Gaya Lopes Dos Santos, F. Stallivieri, L. Cunha De Sousa Download paper
2. Smart Resource Use in Precision Agriculture: A Conceptual Framework for Digital Sustainability Development Digital and precision agriculture are expected to play a central role in shaping future sustainable food production systems by enabling more intelligent, adaptive, and resource-efficient practices. This study adopted a forward-looking literature review, composed of bibliometric and systematic aspects, to propose Smart Resource Use as an emerging paradigm for sustainable development in digitally enabled precision agriculture, extending the concept of smart consumption beyond its traditional origins... B.B. Gallo, L. Visintainer Lerman, R.F. Da Silva, E. Bolfe, M.M. Da Silva, T. Alves, C.E. Pereira, T.M. Porcino Download paper
3. YOLOv10x-based deep learning for automated detection and counting of seeds per soybean pod Accurate quantification of the number of seeds per soybean pod is a fundamental step for reliable yield estimation. However, this measurement still relies on manual procedures, which are subject to observational variability and limited scalability. In the context of digital agriculture, deep learning–based techniques have shown promise for automating the detection and counting of reproductive structures. Nevertheless, there is still limited application of models specifically aimed...

Filter results3 paper(s) found.

1. Embrapii: What Can We Learn About Precision Agriculture and Environmental Sustainability After Investments of US$100 Million+ in Agricultural Industrial Innovation in Brazil?

Innovation policies have increasingly targeted digital and sustainable transformation, yet systematic assessments of large-scale public-private investments in precision agriculture innovation remain scarce, particularly in tropical contexts. This article analyzes the experience of Embrapii (Brazilian Agency for Research and Industrial Innovation) after fostering more than US$100 million in investments in over 600 research, development, and innovation (RD&I) projects applied to agriculture... J. Videira Menezes, E.M. Dias, M.L. Rebello Pinho Dias Scoton, D.H. Oliveira, I. Mendes Gaya Lopes Dos Santos, F. Stallivieri, L. Cunha De Sousa

Download paper

2. Smart Resource Use in Precision Agriculture: A Conceptual Framework for Digital Sustainability Development

Digital and precision agriculture are expected to play a central role in shaping future sustainable food production systems by enabling more intelligent, adaptive, and resource-efficient practices. This study adopted a forward-looking literature review, composed of bibliometric and systematic aspects, to propose Smart Resource Use as an emerging paradigm for sustainable development in digitally enabled precision agriculture, extending the concept of smart consumption beyond its traditional origins... B.B. Gallo, L. Visintainer Lerman, R.F. Da Silva, E. Bolfe, M.M. Da Silva, T. Alves, C.E. Pereira, T.M. Porcino

Download paper

3. YOLOv10x-based deep learning for automated detection and counting of seeds per soybean pod

Accurate quantification of the number of seeds per soybean pod is a fundamental step for reliable yield estimation. However, this measurement still relies on manual procedures, which are subject to observational variability and limited scalability. In the context of digital agriculture, deep learning–based techniques have shown promise for automating the detection and counting of reproductive structures. Nevertheless, there is still limited application of models specifically aimed...