LIDAR-Based Phenotyping for Drought Response and Drought Tolerance in Potato

Aneley, Gedif Mulugeta; Haas, Manuela; Köhl, Karin

doi:10.1007/s11540-022-09567-8

Cited by 11 publications

(20 citation statements)

References 85 publications

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“…Image-based high-throughput phenotyping is especially important when screening a large number of accessions. Various imaging techniques have been used to measure the response of horticultural plants to different abiotic stresses [ 82 , 112 , 113 , 114 ]. Hyperspectral images were used to detect heat stress tolerance in ginseng [ 115 ].…”

Section: Applications Of Image-based High-throughput Phenotyping In H...mentioning

confidence: 99%

Image-Based High-Throughput Phenotyping in Horticultural Crops

Abebe

Kim

et al. 2023

Plants

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Plant phenotyping is the primary task of any plant breeding program, and accurate measurement of plant traits is essential to select genotypes with better quality, high yield, and climate resilience. The majority of currently used phenotyping techniques are destructive and time-consuming. Recently, the development of various sensors and imaging platforms for rapid and efficient quantitative measurement of plant traits has become the mainstream approach in plant phenotyping studies. Here, we reviewed the trends of image-based high-throughput phenotyping methods applied to horticultural crops. High-throughput phenotyping is carried out using various types of imaging platforms developed for indoor or field conditions. We highlighted the applications of different imaging platforms in the horticulture sector with their advantages and limitations. Furthermore, the principles and applications of commonly used imaging techniques, visible light (RGB) imaging, thermal imaging, chlorophyll fluorescence, hyperspectral imaging, and tomographic imaging for high-throughput plant phenotyping, are discussed. High-throughput phenotyping has been widely used for phenotyping various horticultural traits, which can be morphological, physiological, biochemical, yield, biotic, and abiotic stress responses. Moreover, the ability of high-throughput phenotyping with the help of various optical sensors will lead to the discovery of new phenotypic traits which need to be explored in the future. We summarized the applications of image analysis for the quantitative evaluation of various traits with several examples of horticultural crops in the literature. Finally, we summarized the current trend of high-throughput phenotyping in horticultural crops and highlighted future perspectives.

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Section: Applications Of Image-based High-throughput Phenotyping In H...mentioning

confidence: 99%

Image-Based High-Throughput Phenotyping in Horticultural Crops

Abebe

Kim

et al. 2023

Plants

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“…The UAV images contain canopy information, which is easily affected by the mutual shading between the leaves, the size of the leaves, and the degree of leaf curl [60,61]. As the image spatial resolution decreases with increasing flight height, the boundaries between soil and vegetation, canopy shading, and vegetation are blurred.…”

Section: Effect Of Image Resolutions On Spectral and Texture Featuresmentioning

confidence: 99%

Effects of the Spatial Resolution of UAV Images on the Prediction and Transferability of Nitrogen Content Model for Winter Wheat

Guo

Huang

et al. 2022

Drones

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UAV imaging provides an efficient and non-destructive tool for characterizing farm information, but the quality of the UAV model is often affected by the image’s spatial resolution. In this paper, the predictability of models established using UAV multispectral images with different spatial resolutions for nitrogen content of winter wheat was evaluated during the critical growth stages of winter wheat over the period 2021–2022. Feature selection based on UAV image reflectance, vegetation indices, and texture was conducted using the competitive adaptive reweighted sampling, and the random forest machine learning method was used to construct the prediction model with the optimized features. Results showed that model performance increased with decreasing image spatial resolution with a R2, a RMSE, a MAE and a RPD of 0.84, 4.57 g m−2, 2.50 g m−2 and 2.34 (0.01 m spatial resolution image), 0.86, 4.15 g m−2, 2.82 g m−2 and 2.65 (0.02 m), and 0.92, 3.17 g m−2, 2.45 g m−2 and 2.86 (0.05 m), respectively. Further, the transferability of models differed when applied to images with coarser (upscaling) or finer (downscaling) resolutions. For upscaling, the model established with the 0.01 m images had a R2 of 0.84 and 0.89 when applied to images with 0.02 m and 0.05 m resolutions, respectively. For downscaling, the model established with the 0.05 m image features had a R2 of 0.86 and 0.83 when applied to images of 0.01 m and 0.02 m resolutions. Though the image spatial resolution affects image texture features more than the spectral features and the effects of image spatial resolution on model performance and transferability decrease with increasing plant wetness under irrigation treatment, it can be concluded that all the UAV images acquired in this study with different resolutions could achieve good predictions and transferability of the nitrogen content of winter wheat plants.

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“…Secondary traits can be used to obtain a tolerance classification, if they are highly heritable and genetically correlated with yield [16,17]. Canopy development parameters, the stay-green trait, and canopy temperature depression are associated with yield and drought tolerance in crops such as maize, wheat, rice and potato [16][17][18][19][20][21][22]. The third prerequisite for a good secondary trait is being 'easy to measure' [16,17].…”

Section: Introductionmentioning

confidence: 99%

“…In a previous study, we analyzed the relationship between canopy feature dynamics and drought tolerance in a population of siblings that segregated for drought tolerance [21,44]. Canopy growth was analyzed by laser scanner measurement of plant height (PH), total leaf area (A3), and projected leaf area (A2) in long-term drought tolerance trials under variable climate conditions.…”

Section: Introductionmentioning

confidence: 99%

“…We found that tolerant genotypes increased leaf area for longer and achieved a higher maximum of A2 than sensitive genotypes. Additionally, tolerant genotypes had a lower maximum of plant height than sensitive genotypes and maintained the leaf movement pattern typical for optimally watered plants under stress [21]. These features were derived from time-series analysis on a genetically uniform population.…”

Section: Introductionmentioning

confidence: 99%

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Finding Phenotypic Biomarkers for Drought Tolerance in Solanum tuberosum

2023

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Climate change models predict increased drought frequencies. Maintaining yield stability necessitates drought-tolerant crops. However, their breeding is challenging; drought tolerance is a multigene trait with significant environment interaction. Thus, the training of genomic selection models requires phenotyping a large genotype population under arid conditions. We aimed to identify phenotypic tolerance traits that facilitate the screening of large populations in the field. We performed three trials on 20 tetraploid Solanum tuberosum ssp. tuberosum genotypes with significant drought tolerance variation. Plants were subjected to early, late and long-term drought under variable climate conditions. For each stress scenario, the drought tolerance index DRYMp was calculated from the relative tuber starch yield. A laser scanner system measured canopy development continuously over the crop’s lifecycle and provided estimates of leaf movement and canopy growth features. Growth curves were evaluated by logistic regression. Different multiple regression approaches were compared for their ability to predict tolerance from phenotype data of optimally watered or stressed plants. We established that early short-term stress can be used as a proxy for long-term stress in the absence of genetic variation for drought stress recovery or memory. The gen-otypes varied significantly in most canopy features. Leaf-area-based features combined significant genotype effects with environmental stability. Multiple regression models based on single-day data outperformed those based on the regression curve parameter. The models included leaf area and leaf position parameters and partially reproduced prior findings on siblings in a genetically more diverse population.

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LIDAR-Based Phenotyping for Drought Response and Drought Tolerance in Potato

Cited by 11 publications

References 85 publications

Image-Based High-Throughput Phenotyping in Horticultural Crops

Image-Based High-Throughput Phenotyping in Horticultural Crops

Effects of the Spatial Resolution of UAV Images on the Prediction and Transferability of Nitrogen Content Model for Winter Wheat

Finding Phenotypic Biomarkers for Drought Tolerance in Solanum tuberosum

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