Drought stress induced by polyethylene glycol (PEG) in local maize at the early seedling stage

Elizabeth Mustamu, Novilda; Tampubolon, Koko; Alridiwirsah,; Basyuni, Mohammad; AL-Taey, Duraid K.A.; Jawad Kadhim AL Janabi, Haider; Mehdizadeh, Mohammad

doi:10.1016/j.heliyon.2023.e20209

Cited by 8 publications

(1 citation statement)

References 35 publications

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“…Wang et al [60] measured aboveground dry weight, underground dry weight, root length, and other indicators to evaluate maize seedling quality. Mustamu et al [61] selected indicators such as root length, plant height, root crown ratio, aboveground fresh weight, underground fresh weight, aboveground dry weight, and underground dry weight based on traditional methods to evaluate maize seedling quality. Compared with previous studies, in the field of crop seedling quality, in the present study, 27 maize seedling phenotypic quality indicators were extracted by combining the growth characteristics of maize in the field, further enriching the comprehensive evaluation index system of maize seedling quality.…”

Section: Analysis Of the Methodological Strengths Of This Studymentioning

confidence: 99%

A Phenotypic Extraction and Deep Learning-Based Method for Grading the Seedling Quality of Maize in a Cold Region

Zhang,

Lu,

Guan

et al. 2024

Agronomy

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Background: Low-temperature stress significantly restricts maize germination, seedling growth and development, and yield formation. However, traditional methods of evaluating maize seedling quality are inefficient. This study established a method of grading maize seedling quality based on phenotypic extraction and deep learning. Methods: A pot experiment was conducted using different low-temperature combinations and treatment durations at six different stages between the sowing and seedling phases. Changes in 27 seedling quality indices, including plant morphology and photosynthetic performance, were investigated 35 d after sowing and seedling quality grades were classified based on maize yield at maturity. The 27 quality indices were extracted, and a total of 3623 sample datasets were obtained and grouped into training and test sets in a 3:1 ratio. A convolutional neural network-based grading method was constructed using a deep learning model. Results: The model achieved an average precision of 98.575%, with a recall and F1-Score of 98.7% and 98.625%, respectively. Compared with the traditional partial least squares and back propagation neural network, the model improved recognition accuracy by 8.1% and 4.19%, respectively. Conclusions: This study provided an accurate grading of maize seedling quality as a reference basis for the standardized production management of maize in cold regions.

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Section: Analysis Of the Methodological Strengths Of This Studymentioning

confidence: 99%

A Phenotypic Extraction and Deep Learning-Based Method for Grading the Seedling Quality of Maize in a Cold Region

Zhang,

Lu,

Guan

et al. 2024

Agronomy

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Plant Growth‐Promoting Bacteria Associated With Some Salt‐Tolerant Plants

Beitsayahi,

Enayatizamir,

Nejadsadeghi

et al. 2024

Journal of Basic Microbiology

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Given the benefits of bacteria associated with the rhizosphere and phytoplane of halophytes, this research focused on examining the plant growth‐promoting characteristics of bacteria isolated from Cressa cretica, Suaeda aegyptiaca, and Alhagi graecorum. From the 33 isolates tested, 9 exhibited plant growth‐promoting traits. Bacillus rugosus strain CS5 and Bacillus sp. strain SS4 exhibited the notable growth inhibition of the pathogenic fungus Fusarium oxysporum, with values of 47% and 45%, respectively. Bacillus sp. strains SS4 and CS1 demonstrated impressive results in solubilizing phosphorus and zinc, respectively, achieving concentrations of 259 and 271 mg L−1. Additionally, Staphylococcus xylosus strain SR2, Bacillus sp. strain SS4, and Bacillus paralicheniformis strain CR1 thrived in nitrogen‐free media. The Priestia filamentosa strain AL4 showed the greatest HCN production, whereas B. paralicheniformis strain CR1 was notable for higher auxin production. The Bacillus sp. strains SS4 and CS1 exhibited greater tolerance than other isolates in a medium containing 600 mM of NaCl. Additionally, inoculating these isolates into soil significantly alleviated the salinity and drought stress on Zea mays seedlings. These findings suggest that further investigation into these strains as microbial inoculants could be beneficial for mitigating salt and drought stress in plants.

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Genome-Wide Identification, Evolutionary and Expression Analysis of Cyclin-Dependent Kinase Gene Family Members in Moso Bamboo (Phyllostachys edulis)

Dong,

Lan,

Liu

et al. 2024

J Plant Growth Regul

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Drought stress induced by polyethylene glycol (PEG) in local maize at the early seedling stage

Cited by 8 publications

References 35 publications

A Phenotypic Extraction and Deep Learning-Based Method for Grading the Seedling Quality of Maize in a Cold Region

A Phenotypic Extraction and Deep Learning-Based Method for Grading the Seedling Quality of Maize in a Cold Region

Plant Growth‐Promoting Bacteria Associated With Some Salt‐Tolerant Plants

Genome-Wide Identification, Evolutionary and Expression Analysis of Cyclin-Dependent Kinase Gene Family Members in Moso Bamboo (Phyllostachys edulis)

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