Software AgDataBox-Map to precision agriculture management

Michelon, Gabriela Karoline; Bazzi, Claudio; Upadhyaya, Shrinivasa K.; Souza, Eduardo Godoy de; Magalhães, Paulo Sérgio Graziano; Borges, Ligia F.; Schenatto, Kelyn; Sobjak, Ricardo; Gavioli, Alan; Betzek, Nelson Miguel

doi:10.1016/j.softx.2019.100320

Cited by 12 publications

(3 citation statements)

References 8 publications

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“…Quantum GIS (QGIS Development Team, 2021) and AgDataBox Map (Bazzi et al, 2019;Michelon et al, 2019) software programs were used for data processing and statistical analysis.…”

Section: 𝑚𝑎𝑥|mentioning

confidence: 99%

Orbital Remote Sensing for the Management of Areas Irrigated With a Central Pivot System

et al. 2023

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Irrigated agriculture is considered one of the most important techniques for agricultural production in the world, despite being the sector that uses water resources the most. Thus, technological advances have been constantly developed and applied in the sector as a way to improve water management and reduce its consumption, considering that some cultures are affected by economic costs and feasibilities of production, because the water cost has increased significantly in recent years. Remote sensing is a technology that has provided good results for estimating evapotranspiration (ETr) in producing areas, enabling more efficient irrigation management for low costs. This study aimed to answer the question about how the generation of irrigation management zones (IMZs) can be used to optimize water use and improve irrigation systems and which ETr models are better for it. Three ETr estimation models (Surface Energy Balance Algorithm for Land [SEBAL], Mapping Evapotranspiration at High Resolution and with Internalized Calibration [METRIC] and Simple Algorithm for Evapotranspiration Retrieving [SAFER]) were used to design IMZs in center pivot cultivated with cotton. The design of IMZs with ETr data proved to be a viable alternative, making it possible to improve water management in irrigated systems, reducing costs with viability irrigation for cotton and others cultures. The METRIC method displayed the greatest ease in obtaining the data used in the ETr estimation for generating the IMZs.

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“…Quantum GIS (QGIS Development Team, 2021) and AgDataBox Map (Bazzi et al, 2019;Michelon et al, 2019) software programs were used for data processing and statistical analysis.…”

Section: 𝑚𝑎𝑥|mentioning

confidence: 99%

Orbital Remote Sensing for the Management of Areas Irrigated With a Central Pivot System

et al. 2023

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“…The software allowed the stored data to be visualized punctually on the map, as well as the creation of thematic maps of productivity, which are generated through the application ADB-Map (Dall'Agnol et al, 2020) of the platform AgDataBox (Bazzi et al, 2019;Borges et al, 2020;Dall'Agnol et al, 2020;Michelon et al, 2019). In addition, the software allows performing geostatistical analysis automatically and creating productivity maps by inverse distance weighting (IDW) or kriging (Kri) (Fig.…”

Section: Software For Importing Analyzing and Creating A Thematic Mapmentioning

confidence: 99%

Yield map generation of perennial crops for fresh consumption

et al. 2021

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Yield mapping technologies can help to increase the quantity and quality of agricultural production. Current systems only focus on the quantification of the harvest, but the quality has equal or greater importance in some perennial crops and impacts directly on the financial profitability. Therefore, a system was developed to quantify and relate the quality obtained in the classification line with the plants of the orchard and for decision-making. The system is comprised of hardware, which obtains the location of the harvester bag during harvesting and unloading at the unloading site, and software that processes the collected data. The cloud of real-time data contributed from the different collectors (bins) allows the construction of yield maps, considering the multi-stage harvesting system. Further, the system enables the creation of a detailed map of the plants and fruits harvested. As the harvest focuses on quality, it takes place in stages, depending on the ripening of the fruits. In addition to the yield maps, the system allows identification of the efficiency of each worker undertaking the harvest by the number of performed discharges and by the time spent. The system was developed in partnership with the Federal Technological University of Paraná and Embrapa Uva & Vinho and was tested in apple orchards in southern Brazil. Although the system was evaluated with only data from apple cultivation, monitoring the quality and quantifying other orchard fruits can positively impact the fruit sector.

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“…Over the years, automation and data acquisition systems have received special interest due to their potential to solve tasks efficiently in many areas such as medicine [1], manufacture industries [2], video processing [3], agriculture [4], imaging [5], meteorological systems [6], remote laboratory [7], and others. Besides, in some research tasks it is necessary to acquire a considerable number of samples in manual mode by using electronic devices; during this process, the measurements can be affected by errors and information loss for the analysis.…”

Section: Introductionmentioning

confidence: 99%

Automated Data Acquisition System Using a Neural Network for Prediction Response in a Mode-Locked Fiber Laser

et al. 2020

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In this paper, we proposed a system to integrate optical and electronic instrumentation devices to predict a mode-locking fiber laser response, using a remote data acquisition with processing through an artificial neural network (ANN). The system is made up of an optical spectrum analyzer (OSA), oscilloscope (OSC), polarimeter (PAX), and the data acquisition automation through transmission control protocol/internet protocol (TCP/IP). A graphic user interface (GUI) was developed for automated data acquisition with the purpose to study the operational characteristics and stability at the passively mode-locked fiber laser (figure-eight laser, F8L) output. Moreover, the evolution of the polarization state and the behavior of the pulses are analyzed when polarization is changed by proper control plate adjustments. The data is processed using deep learning techniques, which provide the characteristics of the pulse at the output. Therefore, the parameter classification-identification is in accordance with the input polarization tilt used for the laser optimization.

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Software AgDataBox-Map to precision agriculture management

Cited by 12 publications

References 8 publications

Orbital Remote Sensing for the Management of Areas Irrigated With a Central Pivot System

Orbital Remote Sensing for the Management of Areas Irrigated With a Central Pivot System

Yield map generation of perennial crops for fresh consumption

Automated Data Acquisition System Using a Neural Network for Prediction Response in a Mode-Locked Fiber Laser

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