Dynamic monitoring of NDVI in wheat agronomy and breeding trials using an unmanned aerial vehicle

Duan, Tao; Chapman, Scott C.; Guo, Yan; Zheng, Bangyou

doi:10.1016/j.fcr.2017.05.025

Cited by 237 publications

(174 citation statements)

References 52 publications

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“…The NDVI correlations were improved through the index's reformulations as SAVI and OSAVI, which include parameters for reduction of the brightness effect of the soil [35,36]. In accordance with Duan et al [68], who dynamically monitored NDVI during a growing season for contrasting wheat cultivars and growing conditions, we also reported a higher correlation with GY during the anthesis period. In most cases, the spectral-resolution precision of the multispectral indexes provides benefits in assessing genotypic differences in GY, but when canopies were found to be very dense (for example under support irrigation during most of the reproductive period), the vegetation indexes reported values near their saturation point.…”

Section: Ability Of the Remote Sensing Measurements To Assess Genotypsupporting

confidence: 87%

UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat

et al. 2019

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Climate change is one of the primary culprits behind the restraint in the increase of cereal crop yields. In order to address its effects, effort has been focused on understanding the interaction between genotypic performance and the environment. Recent advances in unmanned aerial vehicles (UAV) have enabled the assembly of imaging sensors into precision aerial phenotyping platforms, so that a large number of plots can be screened effectively and rapidly. However, ground evaluations may still be an alternative in terms of cost and resolution. We compared the performance of red-green-blue (RGB), multispectral, and thermal data of individual plots captured from the ground and taken from a UAV, to assess genotypic differences in yield. Our results showed that crop vigor, together with the quantity and duration of green biomass that contributed to grain filling, were critical phenotypic traits for the selection of germplasm that is better adapted to present and future Mediterranean conditions. In this sense, the use of RGB images is presented as a powerful and low-cost approach for assessing crop performance. For example, broad sense heritability for some RGB indices was clearly higher than that of grain yield in the support irrigation (four times), rainfed (by 50%), and late planting (10%). Moreover, there wasn't any significant effect from platform proximity (distance between the sensor and crop canopy) on the vegetation indexes, and both ground and aerial measurements performed similarly in assessing yield.2 of 25 principal goal for breeders. Durum wheat is, by extension, the main cereal cultivated on the southern and eastern shores of the Mediterranean Basin and one of the main cereals in southern Europe [4].Yield is a phenotypically complicated trait, not only because of its genetic complexity [5], but also due to the relative magnitude of gene-environment interactions [6,7], and it is one of the most integrative traits influenced by known and unknown factors. Thus, genotype evaluations in multi-environment trials are needed, at least in the advanced (generations) stages of selection. However, the major point at issue is that high-throughput plant phenotyping (HTPP) may still represent a bottleneck in breeding programs [7], owing to the need to increase the accuracy, precision, and throughput of the methodologies used, while reducing costs and minimizing labor [8,9]. Furthermore, HTPP approaches should allow multi-temporal trait-specific measurements to evaluate the yield components at different phenological moments.Nowadays, and almost by definition, HTPP implies the use of non-invasive remote sensing approaches of different nature [5,10], given the possibility of screening larger populations faster than conventional phenotyping procedures. Moreover, recent progress and advances in the technology of aeronautics and sensors have allowed the adoption of unmanned aerial vehicle (UAV) platforms, capable of precisely screening hundreds of plots in a short period of time [7,11]. Further benefits of the simultaneous c...

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Section: Ability Of the Remote Sensing Measurements To Assess Genotypsupporting

confidence: 87%

UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat

et al. 2019

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“…A recording technique measures the status of crop, soil, weeds, pests, or diseases, typically using sensors on mobile equipment. Examples are soil scans, canopy reflectance measurements, weed detection using cameras, yield monitors on grain combines or potato harvesters, and sensors mounted on satellites, airplanes and Unmanned Aerial Vehicles (UAVs) [5,6]. Typical examples of reacting techniques are variable rate application of fertilizers and pesticides, usually on the basis of prepared maps, but this can also be on-the-go in response to a sensor signal.…”

Section: Introductionmentioning

confidence: 99%

Can Precision Agriculture Increase the Profitability and Sustainability of the Production of Potatoes and Olives?

et al. 2017

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For farmers, the application of Precision Agriculture (PA) technology is expected to lead to an increase in profitability. For society, PA is expected to lead to increased sustainability. The objective of this paper is to determine for a number of common PA practices how much they increase profitability and sustainability. For potato production in The Netherlands, we considered variable rate application (VRA) of soil herbicide, fungicide for late blight control, sidedress N, and haulm killing herbicide. For olive production in Greece, we considered spatially variable application of P and K fertilizer and lime. For each of the above scenarios, we quantified the value of outputs, the cost of inputs, and the environmental costs. This allowed us to calculate profit as well as social profit, where the latter is defined as revenues minus conventional costs minus the external costs of production. Social profit can be considered an overall measure of sustainability. Our calculations show that PA in potatoes increases profit by 21% (420 € ha −1 ) and social profit by 26%. In olives, VRA application of P, K, and lime leads to a strong reduction in nutrient use and although this leads to an increase in sustainability, it has only a small effect on profit and on social profit. In conclusion, PA increases sustainability in olives and both profitability and sustainability in potatoes.

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“…The advantages of using multispectral imaging that includes the near infra-red (NIR) include a wider spectral range for general surface reflection properties and the use of the normalized difference vegetation index (NDVI), which is the differenced ratio of reflectance in Remote Sens. 2020, 12, 41 5 of 31 the red and near-infrared wavelength [31], to reveal an indication of crop health [32]. The equation for NDVI is given as:…”

Section: Aerial Photography In Archaeologymentioning

confidence: 99%

Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles

Brooke

Clutterbuck

2019

Remote Sensing

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There is a long history of the use of aerial imagery for archaeological research, but the application of multisensor image data has only recently been facilitated by the development of unmanned aerial vehicles (UAVs). Two archaeological sites in the East Midlands U.K. that differ in age and topography were selected for survey using multisensor imaging from a fixed-wing UAV. The aim of this study was to determine optimum methodology for the use of UAVs in examining archaeological sites that have no obvious surface features and examine issues of ground control target design, thermal effects, image processing and advanced filtration. The information derived from the range of sensors used in this study enabled interpretation of buried archaeology at both sites. For any archaeological survey using UAVs, the acquisition of visible colour (RGB), multispectral, and thermal imagery as a minimum are advised, as no single technique is sufficient to attempt to reveal the maximum amount of potential information.

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Dynamic monitoring of NDVI in wheat agronomy and breeding trials using an unmanned aerial vehicle

Cited by 237 publications

References 52 publications

UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat

UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat

Can Precision Agriculture Increase the Profitability and Sustainability of the Production of Potatoes and Olives?

Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles

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