The feasibility of using a low-cost near-infrared, sensitive, consumer-grade digital camera mounted on a commercial UAV to assess Bambara groundnut yield

Jewan, Shaikh Yassir Yousouf; Pagay, Vinay; Billa, Lawal; Tyerman, Stephen D.; Gautam, Deepak; Sparkes, Debbie L.; Chai, Hui Hui; Singh, Ajit

doi:10.1080/01431161.2021.1974116

Cited by 14 publications

(17 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The modified Canon S100 collected the three green-red-NIR bands from 520 to 880 nm. The sensor was used because of its low acquisition cost, as well as being widely used in plant evaluation studies and vegetation vigor zoning (Barrows & Bulanon, 2017;Duarte-Carvajalino et al, 2018;Haghighattalab et al, 2017;Jewan et al, 2022;Ogliari et al, 2022;Van der Merwe & Price, 2015), including phenotyping (Haghighattalab et al, 2016).…”

Section: Methodsmentioning

confidence: 99%

Using Remotely Piloted Aircraft (Rpa) Imagery to Map the Profitability of Cotton Crops

Santos,

Moreira,

Santana

et al. 2023

Eng. Agríc.

View full text Add to dashboard Cite

The goal of this paper was to apply a method for the delineation of vegetation homogeneous zones (HZs) to map the profitability of cotton (Gossypium sp.) using NDVI (Normalized Difference Vegetation Index) data from RPA imagery. Two irrigated cotton crops, at the FAU (103 ha) and FRP farms (106 ha), located in the western region of Bahia State, Brazil, were studied. The NDVI images were classified into three HZs: "high", "medium" and "low" plant vigor; using the k-means clustering method. In each HZ the yield was measured, and the profitability estimated. In FAU we found that the lower the HZ's NDVI values, the lower its profitability, because there was profit in the "high vigor" HZ, of US$ 829.40 ha -1 , and loss in the "low vigor" HZ, of about US$ -1.256.09 ha -1 (-251.44% compared with the "high vigor"). In the FRP plantation, the lower the NDVI values, the lower the loss of the plantation, as there were losses in all HZs: from "high" to "low vigor" HZ, the percentage difference in profitability was -343.43%. Thus, the use of a low-cost modified near-infrared Canon S100 on an RPA enabled the mapping of crop profitability, aiding the search for the factors behind yield variability.

show abstract

Section: Methodsmentioning

confidence: 99%

Using Remotely Piloted Aircraft (Rpa) Imagery to Map the Profitability of Cotton Crops

Santos,

Moreira,

Santana

et al. 2023

Eng. Agríc.

View full text Add to dashboard Cite

show abstract

“…Pod yield has been the most important trait to measure in peanut breeding programs. UAV remote sensing-based vegetation indices of peanut canopy at critical phenological stages, such as the pod-filling stage, have shown their value for early yield prediction ( Balota and Oakes, 2017 ; Jewan et al, 2022 ). For direct sensing of peanut pods, ground penetrating radar has shown the potential to explain yield variability up to 51% ( Dobreva et al, 2021 ).…”

Section: High-throughput Phenomics To Accelerate Data Collection In G...mentioning

confidence: 99%

Sustaining yield and nutritional quality of peanuts in harsh environments: Physiological and molecular basis of drought and heat stress tolerance

et al. 2023

View full text Add to dashboard Cite

Climate change is significantly impacting agricultural production worldwide. Peanuts provide food and nutritional security to millions of people across the globe because of its high nutritive values. Drought and heat stress alone or in combination cause substantial yield losses to peanut production. The stress, in addition, adversely impact nutritional quality. Peanuts exposed to drought stress at reproductive stage are prone to aflatoxin contamination, which imposes a restriction on use of peanuts as health food and also adversely impact peanut trade. A comprehensive understanding of the impact of drought and heat stress at physiological and molecular levels may accelerate the development of stress tolerant productive peanut cultivars adapted to a given production system. Significant progress has been achieved towards the characterization of germplasm for drought and heat stress tolerance, unlocking the physiological and molecular basis of stress tolerance, identifying significant marker-trait associations as well major QTLs and candidate genes associated with drought tolerance, which after validation may be deployed to initiate marker-assisted breeding for abiotic stress adaptation in peanut. The proof of concept about the use of transgenic technology to add value to peanuts has been demonstrated. Advances in phenomics and artificial intelligence to accelerate the timely and cost-effective collection of phenotyping data in large germplasm/breeding populations have also been discussed. Greater focus is needed to accelerate research on heat stress tolerance in peanut. A suits of technological innovations are now available in the breeders toolbox to enhance productivity and nutritional quality of peanuts in harsh environments. A holistic breeding approach that considers drought and heat-tolerant traits to simultaneously address both stresses could be a successful strategy to produce climate-resilient peanut genotypes with improved nutritional quality.

show abstract

“…This kind of off-the-shelf RGB cameras have been shown to be useful for the measurement of vegetation indices [ 36 ]. Moreover, the camera filters can be modified by replacing the standard near-infrared (NIR) filter with an appropriate filter, resulting in a low-cost camera capable of detecting two visible bands and one NIR band [ 37 , 38 ].…”

Section: Toolkit Componentsmentioning

confidence: 99%

Open Science Drone Toolkit: Open source hardware and software for aerial data capture

et al. 2023

View full text Add to dashboard Cite

Despite the increased access to scientific publications and data as a result of open science initiatives, access to scientific tools remains limited. Uncrewed aerial vehicles (UAVs, or drones) can be a powerful tool for research in disciplines such as agriculture and environmental sciences, but their use in research is currently dominated by proprietary, closed source tools. The objective of this work was to collect, curate, organize and test a set of open source tools for aerial data capture for research purposes. The Open Science Drone Toolkit was built through a collaborative and iterative process by more than 100 people in five countries, and comprises an open-hardware autonomous drone and off-the-shelf hardware, open-source software, and guides and protocols that enable the user to perform all the necessary tasks to obtain aerial data. Data obtained with this toolkit over a wheat field was compared to data from satellite imagery and a commercial hand-held sensor, finding a high correlation for both instruments. Our results demonstrate the possibility of capturing research-grade aerial data using affordable, accessible, and customizable open source software and hardware, and using open workflows.

show abstract

The feasibility of using a low-cost near-infrared, sensitive, consumer-grade digital camera mounted on a commercial UAV to assess Bambara groundnut yield

Cited by 14 publications

References 84 publications

Using Remotely Piloted Aircraft (Rpa) Imagery to Map the Profitability of Cotton Crops

Using Remotely Piloted Aircraft (Rpa) Imagery to Map the Profitability of Cotton Crops

Sustaining yield and nutritional quality of peanuts in harsh environments: Physiological and molecular basis of drought and heat stress tolerance

Open Science Drone Toolkit: Open source hardware and software for aerial data capture

Contact Info

Product

Resources

About