Determining the dynamic responses of cotton root morphological characteristics under waterlogging stress using the minirhizotron technique

Qian, Long; Huang, Taoxing; Zeng, Wenzhi; Chen, Xiaohong; Wang, Xiugui

doi:10.1002/ird.2752

Cited by 2 publications

(2 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wang et al 5 found that under waterlogging stress, the content of soluble protein and MDA in cotton leaves significantly increased. The waterlogging treatment has a significant promoting effect on the morphological growth of cotton roots, but it only has a promoting effect more than 23 days after the waterlogging ends 6 .…”

Section: Introductionmentioning

confidence: 99%

“…Kong et al 6 found that the root system diameter of hydroponically grown spider plant ( Chlorophytumcomosum ) was smaller than that of soil grown plants. The hydroponic roots contain much fewer crystalliferous cells and amyloplasts in the root cap compared to xeric plants, fewer cortical cells and crystalliferous cells in the mature root regions, and thicker endothelial layers and a smaller pith area in the stele.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Morphological and proteomic study of waterlogging tolerance in cotton

Zhang,

Xie,

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Floating seedling cultivation technique is a novel seedling method in cotton and it provides an ideal model to study cotton growing under waterlogging stress. Morphological character and proteomic profile of the primary root from the seedling cultured by the new technology were evaluated in this study. Compared to seedlings cultured by the traditional method, the diameter of the taproot from floating technology is small at all five seedling stages from one-leaf stage to five-leaf stage. There are similar changes between the thickness of cortex and diameter of stele, which increased from the one- to the two-leaf stage but decreased from the two- to the five-leaf stage. At the one-leaf stage, the number and volume of mitochondria in the primary root-tip cells were less than those in the control. At the two-leaf stage, there was significantly less electron-dense material in the primary root-tip cells than those in the control group. From the one- to the two-leaf stage, the vacuole volume was significantly smaller than that in the control. Total 28 differentially expressed proteins were revealed from aquatic and control group roots of cotton seedlings at the three-leaf stage by two-dimensional electrophoresis, which included 24 up-regulated and four down-regulated proteins. The relative expression of the phosphoglycerate kinase (PGK) gene in aquatic roots increased from the one- to the four-leaf stage but declined rapidly from the four- to the five-leaf stage. The relative expression of the 14–3-3b gene tended to decrease from the one- to the five-leaf stage. The PGK and 14–3-3b genes were specifically expressed in the aquatic roots at the three-leaf stage. In brief, these changes induced waterlogging resistance in the aquatic roots of cotton seedlings in the floating nursery, thereby causing the roots to adapt to the aquatic environment, promoting the growth and development of cotton seedlings.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Morphological and proteomic study of waterlogging tolerance in cotton

Zhang,

Xie,

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

Toward improved image‐based root phenotyping: Handling temporal and cross‐site domain shifts in crop root segmentation models

Banet,

Smith,

McGrail

et al. 2024

The Plant Phenome Journal

View full text Add to dashboard Cite

Crop root segmentation models developed through deep learning have increased the throughput of in situ crop phenotyping studies. However, models trained to identify roots in one image dataset may not accurately identify roots in another dataset, especially when the new dataset contains known differences, called domain shifts. The objective of this study was to quantify how model performance changes when models are used to segment image datasets that contain domain shifts and evaluate approaches to reduce error associated with domain shifts. We collected maize root images at two growth stages (V7 and R2) in a field experiment and manually segmented images to measure total root length (TRL). We developed five segmentation models and evaluated each model's ability to handle a temporal (growth‐stage) domain shift. For the V7 growth stage, a growth‐stage‐specific model trained only on images captured at the V7 growth stage was best suited for measuring TRL. At the R2 growth stage, combining images from both growth stages into a single dataset to train a model resulted in the most accurate TRL measurements. We applied two of the field models to images from a greenhouse experiment to evaluate how model performance changed when exposed to a cross‐site domain shift. Field models were less accurate than models trained only on the greenhouse images even when crop growth stage was identical. Although models may perform well for one experiment, model error increases when applied to images from different experiments even when crop species, growth stage, and soil type are similar.

show abstract

Determining the dynamic responses of cotton root morphological characteristics under waterlogging stress using the minirhizotron technique

Cited by 2 publications

References 38 publications

Morphological and proteomic study of waterlogging tolerance in cotton

Morphological and proteomic study of waterlogging tolerance in cotton

Toward improved image‐based root phenotyping: Handling temporal and cross‐site domain shifts in crop root segmentation models

Contact Info

Product

Resources

About