Table 2.
Summary of research work that used imaging technologies to specifically study abiotic stress.
| stress | growing conditions | species | year | imaging | traits measured | destructive (non-HTP) measurements | instrument/Phenotyping platform | reference |
|---|---|---|---|---|---|---|---|---|
| cold | controlled | pea | 2015 | RGB—fluorescence | biomass/growth related traits—chlorophyll fluorescence parameters | — | PlantScreen Photon Systems Instruments (PSI), Czech Republic | Humplík et al. [14] |
| cold | field | maize | 2019 | RGB—multispectral | stress detection, quantification and classification | — | Multispectral UAV, field of ICAR-NEH at Indian states of Meghalaya, India | Goswami et al. [90] |
| drought | controlled | barley | 2014 | RGB | biomass/growth related traits, plant hue | shoot biomass, tiller number, height | The Plant Accelerator, Adelaide, Australia | Honsdorf et al. [91] |
| drought | controlled | wheat | 2015 | RGB | biomass/growth related traits | — | The Plant Accelerator, Adelaide, Australia | Parent et al. [92] |
| drought | controlled | rice | 2018 | RGB | biomass/growth related traits, plant hue, architectural traits | shoot biomass and yield and yield components | High-throughput rice phenotyping facility at Huazhong Agricultural University, China | Guo et al. [93] |
| drought | controlled | green millet and foxtail millet | 2015 | RGB—fluorescence—near-infrared (NIR) | morphological traits—photosynthetic efficiency and chlorophyll fluorescence parameters—tissue water content | — | Bellwether Phenotyping Platform at the Donald Danforth Plant Science Center, USA | Fahlgren et al. [12,13] |
| drought | controlled | barley | 2019 | RGB | biomass/growth related traits, architectural traits | shoot biomass, plant height, tiller number | The Plant Accelerator, Adelaide, Australia | Pham et al. [94] |
| drought | controlled | barley | 2019 | RGB—fluorescence | height—chlorophyll fluorescence parameters | shoot biomass, relative water content | PlantScreen Photon Systems Instruments (PSI), Czech Republic | Marchetti et al. [43] |
| drought | controlled | rice | 2020 | RGB—near-infrared (NIR)—infrared—fluorescence | biomass/growth related traits, plant hue, architectural traits—water content—plant temperature—photosynthesis efficiency | — | LemnaTec, GmbH, Aachen, Germany | Kim et al. [79] |
| drought | controlled | lettuce | 2020 | RGB—fluorescence | biomass/growth related traits moprhological traits—chlorophyll Fluorescence parameters | — | PlantScreen Photon Systems Instruments (PSI), Czech Republic | Sorrentino et al. [44] |
| drought | controlled | maize | 2018 | hyperspectral | the leaf angle and surface area | — | PHENOVISION HTPPP located in the greenhouse of the VIB-UGent Center for Plant Systems Biology (Ghent, Belgium) | Mohd Asaari et al. [68] |
| drought | controlled | maize | 2019 | hyperspectral | vegetation indices | — | PHENOVISION, the HTPP infrastructure located at VIB, Ghent, Belgium | Asaari et al. [95] |
| drought | controlled | barley | 2019 | RGB | biomass/growth related traits | shoot biomass | IPK Gatersleben, Germany | Dhanagond et al. [96] |
| drought and nitrogen deficiency | controlled | sorghum | 2015 | RGB—near-infrared (NIR) | biomass/growth related traits, plant hue, architectural traits—senescence (%), NIR, water content composition parameters | shoot biomass, leaf area, plant height, dry matter content (%), moisture content (%), chlorophyll content | The Plant Accelerator, Adelaide, Australia | Neilson et al. [39] |
| drought and nitrogen deficiency | field | wheat | 2019 | RGB | biomass/growth related traits, plant hue | — | PhénoField, applied research institute ARVALIS, France | Beauchêne et al. [53] |
| drought and nitrogen deficiency | controlled | maize—soya bean | 2017 | hyperspectral | NDVI, leaf water content, concentrations of macronutrients | biomass, concentration of macronutrients | University of Nebraska-Lincoln | Pandey et al. [97] |
| heat | controlled | mung bean | 2019 | fluorescence | chlorophyll fluorescence parameters | — | Wals, Germany (Model not given) | Basu et al. [98] |
| nitrogen deficiency | controlled | sorghum | 2017 | RGB | biomass/growth related traits, plant hue | ionomic profiling | Bellwether Phenotyping Platform at the Donald Danforth Plant Science Center, USA | Veley et al. [99] |
| nitrogen deficiency | field | barley | 2017 | RGB—multispectral—thermal | plant hue—Crop Senescence Index (CSI), Photochemical Reflectance Index (PRI), various vegetation indices, Water Band Index (WBI) | yield and yield components | Arazuri Station of the Institute of Agrifood Technologies and Infrastructures of Navarra (INTIA), Spain | Kefauver et al. [100] |
| nitrogen deficiency | controlled | wheat | 2020 | RGB—hyperspectral | biomass/growth related traits, morphological and architectural traits—vegetation indices relating to chlorophyll levels | shoot biomass and yield and yield components; chlorophyll content | Agriculture Victoria's Plant Phenomics Victoria, Horsham (PPVH), Australia | Banerjee et al. [101] |
| nitrogen deficiency | field | maize | 2020 | hyperspectral | NDVI | — | LeafSpec, developed by the Purdue Phenotyping Lab group, USA | Ma et al. [102] |
| nitrogen deficiency | field | maize | 2006 | multispectral | leaf reflectance | — | multi-spectral charge-coupled device (CCD) camera s mounted on a mobile liquid nitrogen sprayer | Noh et al. [103] |
| nutrient deficiency | field | alfalfa | 2019 | RGB—multispectral | NDVI, leaf area index, ground coverage | biomass, yield, plant height | UAVs and sensors mounted on a phenomobile, USA | Cazenave et al. [104] |
| salinity | controlled | rice | 2014 | RGB—fluorescence | biomass—shoot senescence (%) | shoot biomass, leaf Na+ and K+ concentration | The Plant Accelerator, Adelaide, Australia | Hairmansis et al. [105] |
| salinity | controlled | rice | 2015 | RGB—fluorescence | biomass—chlorophyll fluorescence parameters | leaf Na+ and K+ concentration | The Plant Accelerator, Adelaide, Australia | Campbell [48] |
| salinity | controlled | rice | 2016 | RGB | biomass/growth related traits | shoot biomass | The Plant Accelerator, Adelaide, Australia | Al-Tamimi et al. [37] |
| salinity | controlled | chickpea | 2017 | RGB | biomass/growth related traits | shoot biomass, plant height, leaf Na+ and K+ concentrations, flowering time, leaf chlorosis and necrosis, yield and yield components | The Plant Accelerator, Adelaide, Australia | Atieno et al. [106] |
| salinity | controlled | barley | 2017 | RGB | growth curve registration (statistics paper) | — | The Plant Accelerator, Adelaide, Australia | Meng et al. [107] |
| salinity | controlled | wheat | 2018 | RGB | biomass/growth related traits | leaf Na+ and K+ concentrations | The Plant Accelerator, Adelaide, Australia | Asif et al. [108] |
| salinity | controlled | rice | 2018 | RGB—fluorescence | biomass/growth related traits | shoot biomass, gas exchange parameters (photosynthesis, stomatal conductance and transpiration), chlorophyll concentrations | The Plant Accelerator, Adelaide, Australia | Yichie et al. [109] |
| salinity | controlled | wheat | 2018 | hyperspectral | NDVI and EGI | shoot and root biomass | University of Minnesota, Minneapolis, MN, United States | Moghimi et al. [70] |
| salinity | field | tomato | 2018 | RGB | biomass/growth related traits, prediction of yield and yield components | shoot biomass and yield and yield components | UAVs. King Abdullah University for Science and Technology, Thuwal, Saudi Arabia. | Johansen et al. [110] |
| salinity | controlled | lettuce | 2019 | fluorescence | chlorophyll fluorescence parameters | shoot biomass | PlantScreen TRANSECT XZ SYSTEM | Adhikari et al. [111] |
| salinity | controlled | okra (Abelmoschus esculentus L.) | 2019 | hyperspectral | plant and leaf segmentation | biomass, SPAD, sodium concentration, photosynthetic rate and transpiration rate | — | Feng et al. [112] |
| salinity | controlled | wheat | 2017 | hyperspectral | stress detection, vegetation indices, leaf segmentation | shoot and root biomass | hyperspectral camera (PIKA II, Resonon, Inc, Bozeman, MT 59715, USA) | Moghimi et al. [113] |