Automatic detection of fruits in coffee crops from aerial images

Carrijo, Gabriel; Oliveira, Danilo Elias de; Assis, Gleice Aparecida de; Carneiro, Murillo G.; Guizilini, Vitor; Souza, Jefferson R.

doi:10.1109/sbr-lars-r.2017.8215283

Cited by 19 publications

(15 citation statements)

References 13 publications

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“…The size of the 'PRECISION-AGRICULTURE' cluster shows the strong relationship between the themes. Other works used ML [97]- [99], IoT and remote sensing [7], [78], [100], [101] to assist in data collection and production management.…”

Section: Internet Of Thingsmentioning

confidence: 99%

Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends

et al. 2020

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Precision Agriculture (PA) and Agriculture 4.0 (A4.0) have been widely discussed as a medium to address the challenges related to agricultural production. In this research, we present a Systematic Literature Review (SLR) supported by a Bibliometric Performance and Network Analysis (BPNA) of the use of A4.0 technologies and PA techniques in the coffee sector. To perform the SLR, 87 documents published since 2011 were extracted from the Scopus and Web of Science databases and processed through the Preferred Reporting Items for Systematic reviews and Meta-Analyzes (PRISMA) protocol. The BPNA was carried out to identify the strategic themes in the field of study. The results present 23 clusters with different levels of development and maturity. We also discovered and presented the thematic network structure of the most used A4.0 technologies in the coffee sector. Our findings shows that Internet of Things, Machine Learning and geostatistics are the most used technologies in the coffee sector, we also present the main challenges and trends related to technological adoption in coffee systems. We believe that the demonstrated results have the potential to be considered by researchers in future works and decision making related to the field of study.

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Section: Internet Of Thingsmentioning

confidence: 99%

Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends

et al. 2020

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“…In this regard, Unmanned Aerial Vehicles (UAVs) are the new technological step for crop monitoring [11,19,2]. In the last decade, UAVs have been key to solve di↵erent problems in agriculture that mostly required high-precision crop data, e.g., crop parcels detection [10], fruit detection [4], crop yield improvement [21], crop variable measurement [15,14], and crop terrain mapping [8,13]. In this sense, UAVs have turned into mobile sensors with powerful processing capabilities that allow for a non-destructive and highly e cient crop monitoring in real-time [20,5].…”

Section: Introductionmentioning

confidence: 99%

High-Throughput Biomass Estimation in Rice Crops Using UAV Multispectral Imagery

Devia

Rojas

Petro

et al. 2019

J Intell Robot Syst

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High-Throughput Biomass Estimation in Rice Crops Using UAV Multispectral Imagery The International Center for Tropical Agriculture (CIAT) believes that open access contributes to its mission of reducing hunger and poverty, and improving human nutrition in the tropics through research aimed at increasing the eco-efficiency of agriculture. CIAT is committed to creating and sharing knowledge and information openly and globally. We do this through collaborative research as well as through the open sharing of our data, tools, and publications.

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“…In Brazil, some studies on the use and application of RS in coffee monitoring are under development, such as the detection of diseases in coffee using RS techniques through satellite images [14][15][16][17][18][19] and water stress assessment [18]. Regarding the use of UAV and RGB cameras for coffee crops, studies have presented applications for detecting planting failures [20], estimating the volume of harvested fruits [21], estimating the plant volume [22], detecting nematodes [23], and determining the biophysical coffee parameters [24], showing the potential of these tools.…”

Section: Introductionmentioning

confidence: 99%

“…Some studies have used image processing techniques such as mathematical morphology operators to detect failures [20], supervised machine learning (ML) techniques to classify areas as coffee fruits and non-fruits [21], and robust object-based image analysis (OBIA) for the 3D structure of vineyards [11]. This research requires knowledge and computational power to achieve good performance, which may hinder product acceptance for some farmers due to high costs.…”

Section: Introductionmentioning

confidence: 99%

Application of RGB Images Obtained by UAV in Coffee Farming

et al. 2021

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The objective of this study was to evaluate the potential of the practical application of unmanned aerial vehicles and RGB vegetation indices (VIs) in the monitoring of a coffee crop. The study was conducted in an experimental coffee field over a 12-month period. An RGB digital camera coupled to a UAV was used. Nine VIs were evaluated in this study. These VIs were subjected to a Pearson correlation analysis with the leaf area index (LAI), and subsequently, the VIs with higher R2 values were selected. The LAI was estimated by plant height and crown diameter values obtained by imaging, which were correlated with these values measured in the field. Among the VIs evaluated, MPRI (0.31) and GLI (0.41) presented greater correlation with LAI; however, the correlation was weak. Thematic maps of VIs in the evaluated period showed variability present in the crop. The evolution of weeds in the planting rows was noticeable with both VIs, which can help managers to make the decision to start crop management, thus saving resources. The results show that the use of low-cost UAVs and RGB cameras has potential for monitoring the coffee production cycle, providing producers with information in a more accurate, quick and simple way.

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Automatic detection of fruits in coffee crops from aerial images

Cited by 19 publications

References 13 publications

Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends

Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends

High-Throughput Biomass Estimation in Rice Crops Using UAV Multispectral Imagery

Application of RGB Images Obtained by UAV in Coffee Farming

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