Plant Phenomics / 2021 / Article / Tab 5

Review Article

UAS-Based Plant Phenotyping for Research and Breeding Applications

Table 5

Examples of the use of UAS for field phenotyping using the criteria of identification, classification, quantification, and prediction (ICQP) of traits. This is a nonexhaustive list.

ICQPType of plant traitUAV typeFlight altitude (m)Image resolutionPlant speciesPlant trait analysis/modelSensor on UAVPlant phenotypeRef.

ClassificationMorphological and physiologicalMultirotor30-VineyardANNMultispectral sensorStem water potential, water stress[172]
QuantificationPhysiologicalMulti rotor50~2.2 cm and 1.11Winter wheatANN, SVM, RF, BBRT, DT, MLR, PLSR, and PCRHyperspectral and RGBAboveground biomass (AGB)[173]
QuantificationPhysiologicalMultirotor & fixed-wing40-Forest, soybean, SorghumANOVA, correlation and heritabilityThermal imagingWater stress[58]
QuantificationPhysiologicalMultirotor801.51 cm per pixelMaizeBroad-sense heritability and genetic correlationsRGBCrop cover and senescence[174]
QuantificationPhysiologicalMultirotor300.5 cmPotatoCorrelation, RFRGBCrop emergence[175]
IdentificationMorphological traitMultirotor755 cm/pixelCitrus treesDCNNMultispectralCounting trees[176]
QuantificationMorphologicalMultirotor40 and 5013 and 10 mm/pixelSorghumGenomic predictionRGB or near-infrared green and blue (NIR-GB)Plant height[27]
QuantificationPhysiological, abiotic stressMultirotor50, 1207.2, 3 cm/pixelDry beansGNDVI, correlationMultispectralSeed yield, biomass, flowering, drought[177]
Classification and quantificationPhysiologicalMultirotor251.5–3.5 cm per pixelWheatHeritability, correlation and GWASRGB and multispectralLodging[178]
QuantificationMorphological and physiological traitMultirotor50 (snapshot), (digital)WheatLinear regression, RF, PLSRRGB, spectroradiometer, and snapshot hyperspectral sensorCrop height, LAI, biomass[179]
QuantificationPhysiologicalMultirotor30, 402.5, 2.8 cmBread wheatLinear regressions, correlation matrix, and broad sense heritabilityMultispectralSenescence[180]
QuantificationPhysiologicalMultirotor755 cm/pixelCottonMixed linear modelMultispectralCrop WUE[181]
QuantificationPhysiologicalMultirotor50-MaizeMultitemporal modelling3D imaging and RGBAGB[182]
QuantificationBiotic stressMultirotor-0.8cmPotatoMultilayer perceptron and CNNRGB and multispectralLate blight severity[183]
QuantificationMorphologicalMultirotor3-8-Blueberry bushMultivariate analysisRGBHeight, extents, canopy area and volume canopy width, and diameter[184]
QuantificationBiotic stressMultirotor5.5, 27-RiceNDVI and correlationRGB and multispectralSheath blight[185]
QuantificationAbiotic stressMultirotor130.5 and 1.12 cmTomatoOBIARGB and multispectralSalinity stress plant area[186]
QuantificationBiotic stressMultirotor150.6 cmCottonOBIARGBCotton boll[187]
IdentificationBiotic stressMultirotor30, 600.01-0.03 m/pixelSunflowerOBIARGB, multispectralWeed[188]
QuantificationPhysiological and morphologicalMultirotor206-8 mmEggplant, tomato, cabbageRF and support vector regressionRGB imagesCrop height, biomass[189]
ClassificationBiotic stressFixed1500.08 m/pixelVineyardReceiver operator characteristic analysisMultispectralFlavescens dorée, grapevine trunk diseases[190]
QuantificationMorphologicalFixed-wing>1002.5, 5, 10, 20 cmMaizeRegressionRGBHeight[80]
QuantificationMorphologicalMultirotor50, 29, 130.01 mCottonRegressionRGBHeight[191]
QuantificationMorphologicalMultirotor52.51.13 cm/pixelMaizeRegressionRGBPlant height[192]
QuantificationPhysiologicalMultirotor35, 70, 1000.54, 1.09, and 1.57 cm)BarleyRegression analysisRGBLodging severity, canopy height[193]
QuantificationPhysiologicalMultirotor76 mmWheatRegression analysisRGBSeed emergence[194]
QuantificationMorphological and physiologicalMultirotor--WheatRegression analysisRGB imagesCanopy traits[195]
QuantificationMorphologicalMultirotor302.5 cm/pixelBread wheatRegression, QTL mapping, and genomic predictionRGB camera and 4 monochrome sensors (NIR, red, green, and red-edge)Plant height[196]
QuantificationMorphologicalMultirotor25-Oilseed rapeRF, regression analysisRGB and multispectralFlower number[197]
IdentificationBiotic stressMultirotor1, 2, 4, 8, 16-SoybeanSVM, KNNRGBFoliar diseases[198]
QuantificationMorphologicalMultirotor30, 50, 70-Lychee cropTree height, crown width, crown perimeter, and plant projective coverMultispectralCrop structural properties[199]
QuantificationPhysiologicalMultirotor40, 60-MaizeUnivariate and multivariate logistic regression modelsRGB and multispectralLodging[200]
QuantificationBiotic stressMultirotor80-BeetUnivariate decision treesHyperspectralBeet cyst nematode[201]
QuantificationBiotic stressMultirotor--PeanutVegetation indexMultispectralSpot wilt[202]
QuantificationMorphological and physiological traitsMultirotor20-CottonVegetation index, SVMMultispectralPlant height, canopy cover, vegetation index, and flower[203]
QuantificationPhysiologicalMultirotor1508.2 cmWheatVegetative indexMultispectralLAI[204]
IdentificationBiotic stressMultirotor~10-RadishVGG-A, CNNRGBFusarium wilt[205]