Effects of Auxin-Type Plant Growth Regulators and Cold Stress on the Endogenous Polyamines in Pea Plants

Jankovska-Bortkevič, Elžbieta; Katerova, Zornitsa; Todorova, Dessislava; Jankauskienė, Jurga; Mockevičiūtė, Rima; Sergiev, Iskren; Jurkonienė, Sigita

doi:10.3390/horticulturae9020244

Cited by 5 publications

(3 citation statements)

References 46 publications

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“…High ambient temperatures pose a substantial threat to agricultural productivity worldwide throughout plant growth and germination phases [38]. Additionally, plants exposed to low temperatures within the temperature range of 0 to 15 • C face challenges in productivity due to osmotic and oxidative stress, which necessitates the activation of various stress-related signaling pathways to restore cellular balance [41,42]. For plants that are susceptible to heat limitations, germination may provide early research for determining the threshold tolerance of the plant.…”

Section: Discussionmentioning

confidence: 99%

Using Machine Learning Algorithms to Investigate the Impact of Temperature Treatment and Salt Stress on Four Forage Peas (Pisum sativum var. arvense L.)

Okumuş,

Say,

Eren

et al. 2024

Horticulturae

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The combination of high or low temperatures and high salt may cause significant harm to the yield, quality, and overall productivity of forage pea crops. The germination process, a crucial phase in the life cycle of forage peas, may be greatly influenced by varying temperature and salinity conditions. To comprehend the influence of these elements on the germination of forage peas, one must use many tactics, including the choice of resilient forage pea cultivars. The experiment aimed to evaluate the response of four forage pea cultivars (Arda, Ozkaynak, Taskent, and Tore) caused by various temperature (10 °C, 15 °C, and 20 °C) and salt (0, 5, 10, 15, and 20 dS m−1) conditions at the germination stage using multivariate analysis and machine learning methods. An observation of statistical significance (p < 0.01) was made regarding the variations between genotypes, temperature–salt levels, and the interaction of the observed factors: germination percentage (GP), shoot length (SL), root length (RL), fresh weight (FW), and dry weight (DW). The cultivar Tore had the best values for SL (1.63 cm), RL (5.38 cm), FW (1.10 g), and DW (0.13 g) among all the cultivars. On the other hand, the Ozkaynak cultivar had the highest value for GP (89.13%). The values of all of the parameters that were investigated decreased as the salt level rose, whereas the values increased when the temperature level increased. As a result, the Tore cultivar exhibited the highest values for shoot length, root length, fresh weight, and dry weight variables when exposed to a maximum temperature of 20 °C and a saline level of 0 dS m−1. It was determined that temperature treatment of fodder peas can reduce salt stress if kept at optimum levels. The effects of temperature and salt treatments on the germination data of several fodder pea cultivars were analyzed and predicted. Three distinct machine learning algorithms were used to create predictions. Based on R2 (0.899), MSE (5.344), MAPE (6.953), and MAD (4.125) measures, the MARS model predicted germination power (GP) better. The GPC model performed better in predicting shoot length (R2 = 0.922, MSE = 0.602, MAPE = 11.850, and MAD = 0.326) and root length (R2 = 0.900, MSE = 0.719, MAPE = 12.673, and MAD = 0.554), whereas the Xgboost model performed better in estimating fresh weight (R2 = 0.966, MSE = 0.130, MAPE = 11.635, and MAD = 0.090) and dry weight (R2 = 0.895, MSE = 0.021, MAPE = 12.395, and MAD = 0.013). The results of the research show that the techniques and analyses used can estimate stress tolerance, susceptibility levels, and other plant parameters, making it a cost-effective and reliable way to quickly and accurately study forage peas and related species.

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Section: Discussionmentioning

confidence: 99%

Using Machine Learning Algorithms to Investigate the Impact of Temperature Treatment and Salt Stress on Four Forage Peas (Pisum sativum var. arvense L.)

Okumuş,

Say,

Eren

et al. 2024

Horticulturae

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“…Because of their multifunctionality, auxins can be used in strategic plantations as plant growth promoters, and this approach has shown promising results in sugarcane [174], potato [175], and tomato plantations [176]. Auxins also help to obtain higher yields of good quality carrot seeds [177], improve the root morphology and growth of grafted cucumber seedlings [178], and can be used to alleviate abiotic stresses [179][180][181] The most well-known compound used to treat weeds using auxin-based products in plantations is 2,4-dichlorophenoxyacetic acid (2,4-D), which was discovered in the 1940s and has been used extensively for more than 70 years worldwide. Arylex™ (developed mainly for cereal plantations) and Rinskor™ (used in rice fields) are new types of auxin herbicides produced on the market which have proven to be an attractive alternative to auxin application [182].…”

Section: Auxinsmentioning

confidence: 99%

Section: Auxinsmentioning

confidence: 99%

Agricultural Bioinputs Obtained by Solid-State Fermentation: From Production in Biorefineries to Sustainable Agriculture

Rocha,

Marcelino,

Da Costa

et al. 2024

Sustainability

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Agriculture plays a major role on society, especially in developing countries which rely on commodity exportation markets. To maintain high crop productivity, the use of agrochemicals was once employed as the main strategy, which in turn affected soil, water, and human health. In order to aid this issue, identifying some alternatives, such as the implementation of biofertilizers and inoculants as bioinputs in modern agriculture, are imperative to improve ecosystem quality. Among these bioinputs, a few bioproducts have shown good performances, such as phytohormones (e.g., auxins and giberellins), biosurfactants, and other enzymes; thus, it is extremely important to assure the quality and feasibility of their production in biorefinery scenarios. These bioproducts can be synthesized through fermentation processes through utilizing plant biomasses and agricultural byproducts as carbon sources. In this sense, to increase the tecno-economical availability of these processes, the implementation of solid-state fermentation (SSF) has shown great potential due to its ease of operation and cost-attractiveness. Therefore, this study aims to describe the main substrates used in SSF systems for the production of potential bioinputs; their associated operation hurdles, parameters, and conditions selection; the most suitable microorganisms; and the underlying mechanisms of these molecules in soil dynamics. Within this context, this study is expected to contribute to the development of new processes in modern biorefineries and to the mitigation of environmental impacts.

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Polyamines metabolism and their biological role in plant cells: what do we really know?

Kolesnikov,

Kretynin,

Filepova

et al. 2024

Phytochem Rev

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Effects of Auxin-Type Plant Growth Regulators and Cold Stress on the Endogenous Polyamines in Pea Plants

Cited by 5 publications

References 46 publications

Using Machine Learning Algorithms to Investigate the Impact of Temperature Treatment and Salt Stress on Four Forage Peas (Pisum sativum var. arvense L.)

Using Machine Learning Algorithms to Investigate the Impact of Temperature Treatment and Salt Stress on Four Forage Peas (Pisum sativum var. arvense L.)

Agricultural Bioinputs Obtained by Solid-State Fermentation: From Production in Biorefineries to Sustainable Agriculture

Polyamines metabolism and their biological role in plant cells: what do we really know?

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