Ranging Sensors for Vehicle-Based Measurement of Crop Stand and Orchard Parameters: A Review

Dworak, Volker; Selbeck, Jörn; Ehlert, Detlef

doi:10.13031/2013.39013

Cited by 29 publications

(19 citation statements)

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“…It was also observed that areas with high gap density overlapped areas of low yield, showing the impact of disease incidence on crop yield. This finding shows that application technologies based on presence sensors and canopy volume that automatically avoids application of inputs on plant gaps (DWORAK et al 2011), are of great importance to improve crop efficiency on orchards with high tree gap density. Data from the two maps were compared in a correlation graph to ascertain the influence of gap occurrence on orchard yield ( Figure 5).…”

Section: Resultsmentioning

confidence: 89%

Yield mapping, soil fertility and tree gaps in an orange orchard

Molin

Colaço²,

Carlos³

et al. 2012

Rev. Bras. Frutic.

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ABSTRACT-The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA) has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB) in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production. Index terms: Precision agriculture, spatial variability, citrus blight, huanglongbing (HLB). MAPEAMENTO DA PRODUTIVIDADE, FERTILIDADE DO SOLO E FALHAS DE PLANTAS EM POMAR DE LARANJEIRASRESUMO -A atual competitividade existente no setor citrícola demanda dos produtores novas estratégias de manejo para aumento de eficiência e sustentabilidade. Nesse sentido, a agricultura de precisão (AP) tem desenvolvido técnicas baseadas no mapeamento de produtividade e sistemas de manejos que reconheçam a variabilidade espacial existente no campo, o que contribui para aumentar a lucratividade de pomares comerciais. Como a variabilidade espacial normalmente não é visualizada, os pomares ainda são manejados como uniformes, e a adoção das tecnologias de AP nas fazendas citrícolas é baixa. Dessa forma, o objetivo do trabalho foi carcaterizar a variabilidade espacial de três fatores: produtividade de frutos, fertilidade do solo e ocorrência de falhas de plantas causadas pelo declínio dos citros e pelo (HLB), em um talhão comercial de citros em Brotas-SP. Dados de volume, coordenadas geográficas e área de representação dos sacolões utilizados na colheita fora...

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Section: Resultsmentioning

confidence: 89%

Yield mapping, soil fertility and tree gaps in an orange orchard

Molin

Colaço²,

Carlos³

et al. 2012

Rev. Bras. Frutic.

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“…The 3D modeling of canopies has become an important research topic in precision agriculture, especially in tree crops-see reviews by Dworak et al [1], Rosell-Polo and Sanz [2], Berk et al [3] and Gil et al [4]. This technique seeks to provide accurate information about canopy dimensions and foliage density, which relates to plant development and health.…”

Section: Introductionmentioning

confidence: 99%

A Method to Obtain Orange Crop Geometry Information Using a Mobile Terrestrial Laser Scanner and 3D Modeling

et al. 2017

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LiDAR (Light Detection and Ranging) technology has been used to obtain geometrical attributes of tree crops in small field plots, sometimes using manual steps in data processing. The objective of this study was to develop a method for estimating canopy volume and height based on a mobile terrestrial laser scanner suited for large commercial orange groves. A 2D LiDAR sensor and a GNSS (Global Navigation Satellite System) receiver were mounted on a vehicle for data acquisition. A georeferenced point cloud representing the laser beam impacts on the crop was created and later classified into transversal sections along the row or into individual trees. The convex-hull and the alpha-shape reconstruction algorithms were used to reproduce the shape of the tree crowns. Maps of canopy volume and height were generated for a 25 ha orange grove. The different options of data processing resulted in different values of canopy volume. The alpha-shape algorithm was considered a good option to represent individual trees whereas the convex-hull was better when representing transversal sections of the row. Nevertheless, the canopy volume and height maps produced by those two methods were similar. The proposed system is useful for site-specific management in orange groves.

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“…Advancing sensing technologies are enhancing monitoring capabilities over a range of spatial scales, from small plot to field to whole farm. Agricultural vehicles have been evaluated as mobile platforms for mounting external non-contact sensing systems for a variety of crop characteristic and crop production applications [11] [12] [13] [14] [15].…”

Section: Introductionmentioning

confidence: 99%

Mobile Open-Source Plant-Canopy Monitoring System

Fisher¹,

Huang²

2017

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Many agricultural applications, including improved crop production, precision agriculture, and phenotyping, rely on detailed field and crop information to detect and react to spatial variabilities. Mobile farm vehicles, such as tractors and sprayers, have the potential to operate as mobile sensing platforms, enabling the collection of large amounts of data while working. Open-source hardware and software components were integrated to develop a mobile plant-canopy sensing and monitoring system. The microcontroller-based system, which incorporated a Bluetooth radio, GPS receiver, infrared temperature and ultrasonic distance sensors, micro SD card storage, and voltage regulation components, was developed at a cost of US$292. The system was installed on an agricultural vehicle and tested in a soybean field. The monitoring system demonstrates an application of open-source hardware to agricultural research and provides a framework for similar or additional sensing applications.

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Ranging Sensors for Vehicle-Based Measurement of Crop Stand and Orchard Parameters: A Review

Cited by 29 publications

References 0 publications

Yield mapping, soil fertility and tree gaps in an orange orchard

Yield mapping, soil fertility and tree gaps in an orange orchard

A Method to Obtain Orange Crop Geometry Information Using a Mobile Terrestrial Laser Scanner and 3D Modeling

Mobile Open-Source Plant-Canopy Monitoring System

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