Fine-scale prediction of biomass and leaf nitrogen content in sugarcane using UAV LiDAR and multispectral imaging

Shendryk, Yuri; Sofonia, Jeremy; Garrard, Robert; Rist, Yannik; Skocaj, Danielle; Thorburn, Peter J.

doi:10.1016/j.jag.2020.102177

Cited by 78 publications

(49 citation statements)

References 53 publications

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“…Furthermore, LiDAR is amenable for time series tracking of object or plant organ geometries [ 63 ]. UAS-mounted LiDAR-based phenotyping has been used for the estimation of canopy biomass and plant height, for example, canopy height in winter wheat to the effect on nitrogen fertilizer rates [ 64 ], sugarcane biomass estimation [ 65 ], and maize height tracking in lodged plots [ 66 ]. The current challenges with routine utilization of LiDAR on UAS are the cost vs. quality trade-off of data [ 67 ].…”

Section: Uas Types and Imaging Modalitiesmentioning

confidence: 99%

UAS-Based Plant Phenotyping for Research and Breeding Applications

et al. 2021

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Unmanned aircraft system (UAS) is a particularly powerful tool for plant phenotyping, due to reasonable cost of procurement and deployment, ease and flexibility for control and operation, ability to reconfigure sensor payloads to diversify sensing, and the ability to seamlessly fit into a larger connected phenotyping network. These advantages have expanded the use of UAS-based plant phenotyping approach in research and breeding applications. This paper reviews the state of the art in the deployment, collection, curation, storage, and analysis of data from UAS-based phenotyping platforms. We discuss pressing technical challenges, identify future trends in UAS-based phenotyping that the plant research community should be aware of, and pinpoint key plant science and agronomic questions that can be resolved with the next generation of UAS-based imaging modalities and associated data analysis pipelines. This review provides a broad account of the state of the art in UAS-based phenotyping to reduce the barrier to entry to plant science practitioners interested in deploying this imaging modality for phenotyping in plant breeding and research areas.

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Section: Uas Types and Imaging Modalitiesmentioning

confidence: 99%

UAS-Based Plant Phenotyping for Research and Breeding Applications

et al. 2021

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“…These models can estimate a wide range of agronomic traits and other physio-biological variables. The technique has been used for crop monitoring and high throughput phenotyping [17,167,175] and estimating various agronomic traits such as yield [176,177], canopy dimensions [178], leaf nutrient concentrations [174,179], and biomass [180]. Moreover, they have also been used in disease identification and quantification [181][182][183], identifying water-related stress [184], scouting weeds and insects [185,186], etc.…”

Section: Crop Diversification In the Precision Agriculture Eramentioning

confidence: 99%

Crop Diversification for Improved Weed Management: A Review

et al. 2021

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Weeds are among the major constraints to any crop production system, reducing productivity and profitability. Herbicides are among the most effective methods to control weeds, and reliance on herbicides for weed control has increased significantly with the advent of herbicide-resistant crops. Unfortunately, over-reliance on herbicides leads to environmental-health issues and herbicide-resistant weeds, causing human health and ecological concerns. Crop diversification can help manage weeds sustainably in major crop production systems. It acts as an organizing principle under which technological innovations and ecological insights can be combined to manage weeds sustainably. Diversified cropping can be defined as the conscious inclusion of functional biodiversity at temporal and/or spatial levels to improve the productivity and stability of ecosystem services. Crop diversification helps to reduce weed density by negatively impacting weed seed germination and weed growth. Additionally, diversified farming systems are more resilient to climate change than monoculture systems and provide better crop yield. However, there are a few challenges to adopting a diversified cropping system, ranging from technology innovations, government policies, farm-level decisions, climate change, and market conditions. In this review, we discuss how crop diversification supports sustainable weed management, the challenges associated with it, and the future of weed management with respect to the diversification concept.

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“…These models can estimate a wide range of agronomic traits and other physio-biological variables. The technique has been used for crop monitoring and high throughput phenotyping [143,152,153] and estimating various agronomic traits such as yield [154,155], canopy dimensions [156], leaf nutrient concentrations [157,151], and biomass [158]. Moreover, they have also been used in disease identification and quantification [159,160,161], identifying water-related stress [162], scouting weeds and insects [163,164], etc.…”

Section: Crop Diversification In the Precision Agriculture Eramentioning

confidence: 99%

Crop Diversification for Improved Weed Management: A Review

Sharma¹,

Shrestha²,

Kunwar³

et al. 2021

Preprint

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Weeds are among the major constraints to any crop production system, reducing productivity and profitability. Herbicides are among the most effective methods to control weeds, and reliance on herbicides for weed control has increased significantly with the advent of herbicide-resistant crops. Unfortunately, over-reliance on herbicides leads to environmental-health issues and herbicide-resistant weeds, causing human-health and ecological concerns. Crop diversification can help manage weeds sustainably in major crop production systems. It acts as an organizing principle under which technological innovations and ecological insights can be combined to manage weeds sustainably. Diversified cropping can be defined as the conscious inclusion of functional biodiversity at temporal and/or spatial levels to improve the productivity and stability of ecosystem services. Crop diversification helps to reduce weed density by negatively impacting weed seed germination and weed growth. Additionally, diversified farming systems are more resilient to climate change than monoculture systems and provide better crop yield. However, there are a few challenges to adopting a diversified cropping system, which ranges from technology innovations, government policies, farm-level decisions, climate change, and market conditions. In this review, we discuss how crop diversification supports sustainable weed management, the challenges associated with it, and the future of weed management with respect to the diversification concept.

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Fine-scale prediction of biomass and leaf nitrogen content in sugarcane using UAV LiDAR and multispectral imaging

Cited by 78 publications

References 53 publications

UAS-Based Plant Phenotyping for Research and Breeding Applications

UAS-Based Plant Phenotyping for Research and Breeding Applications

Crop Diversification for Improved Weed Management: A Review

Crop Diversification for Improved Weed Management: A Review

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