THRESHOLD MODEL IN STUDIES OF ECOLOGICAL RECOVERY IN BERMUDAGRASS (<i>CYNODON DACTYLON</i>L.) UNDER NUTRIENT STRESS CONDITIONS

Heshmati, Gholam Ali; Pessarakli, Mohammad

doi:10.1080/01904167.2011.618577

Cited by 9 publications

(6 citation statements)

References 32 publications

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“…Although it is widely found in the tropical and warm temperate regions, bermudagrass is predominantly distributed between 45° North and 45° South latitudes [1] , [2] . Currently, C. dactylon is globally used as a turf grass, fodder and medicinal plant, and it was also used for removal of heavy metals from contaminated soils [3] – [5] . This grass is adapted to extremely variable environments, such as fertile fields, arid land, saline land, wet irrigation canals and even contaminated wastelands with high levels of Pb, Cd, Zn and Cu [6] – [10] .…”

Section: Introductionmentioning

confidence: 99%

BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

Mantri

Ngai

et al. 2013

PLoS ONE

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Temperature is one of the most significant environmental factors that affects germination of grass seeds. Reliable prediction of the optimal temperature for seed germination is crucial for determining the suitable regions and favorable sowing timing for turf grass cultivation. In this study, a back-propagation-artificial-neural-network-aided dual quintic equation (BP-ANN-QE) model was developed to improve the prediction of the optimal temperature for seed germination. This BP-ANN-QE model was used to determine optimal sowing times and suitable regions for three Cynodon dactylon cultivars (C. dactylon, ‘Savannah’ and ‘Princess VII’). Prediction of the optimal temperature for these seeds was based on comprehensive germination tests using 36 day/night (high/low) temperature regimes (both ranging from 5/5 to 40/40°C with 5°C increments). Seed germination data from these temperature regimes were used to construct temperature-germination correlation models for estimating germination percentage with confidence intervals. Our tests revealed that the optimal high/low temperature regimes required for all the three bermudagrass cultivars are 30/5, 30/10, 35/5, 35/10, 35/15, 35/20, 40/15 and 40/20°C; constant temperatures ranging from 5 to 40°C inhibited the germination of all three cultivars. While comparing different simulating methods, including DQEM, Bisquare ANN-QE, and BP-ANN-QE in establishing temperature based germination percentage rules, we found that the R2 values of germination prediction function could be significantly improved from about 0.6940–0.8177 (DQEM approach) to 0.9439–0.9813 (BP-ANN-QE). These results indicated that our BP-ANN-QE model has better performance than the rests of the compared models. Furthermore, data of the national temperature grids generated from monthly-average temperature for 25 years were fit into these functions and we were able to map the germination percentage of these C. dactylon cultivars in the national scale of China, and suggested the optimum sowing regions and times for them.

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Section: Introductionmentioning

confidence: 99%

BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

Mantri

Ngai

et al. 2013

PLoS ONE

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“…Rich., family Gramineae, consisting of nine species and ten varieties (Huang et al, 2018). Because of its strong vegetative growth and abilities to tolerate trampling, heat, drought, cadmium stresses (Harivandi et al, 1984;Huang et al, 2014;Huang et al, 2019), it is widely used as a warm-season grass in parks, sports fields, landscapes and remediation of contaminated soil (Heshmati & Pessarakli, 2011;Xie et al, 2015;Xie et al, 2021). With advances in next-generation sequencing technology, an increasing amount of investigations in genetic analysis of bermudagrass has been carried out in recent years, which could be used to identify and validate the biochemical and molecular mechanisms controlling bermudagrass tolerance to various stresses, and then to serve plant breeding for the genetic improvement (Huang et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Genetic manipulation of bermudagrass photosynthetic biosynthesis using Agrobacterium‐mediated transformation

Liu

et al. 2022

Physiologia Plantarum

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Bermudagrass is one of the most extensively used warm‐season grasses. It is widely used in landscaping, stadium construction and soil remediation due to its excellent regeneration, trampling and stress tolerances. However, studies on its regulatory mechanism and variety improvement by genetic engineering are still at a standstill, owing to its genetic variability and intrinsic limits linked with some resistance to Agrobacterium infection. In this study, we established a higher efficient Agrobacterium‐mediated transformation via screening for vital embryogenic callus and improving infection efficiency. The superior callus was light yellow, hard granular and compact, determined with a differentiation rate of more than 95%. The optimized infestation courses by gentle shaking, vacuuming and sonicating were used. The infested calluses were co‐cultured for 3 days, followed by desiccation treatments for 1 day to get higher infection efficiency. Then the CdHEMA1 gene, essential for chlorophyll biosynthesis, was cloned and transferred into bermudagrass to validate the aforementioned optimization procedures integrally. Molecular‐level analyses indicated that the CdHEMA1 gene had successfully integrated and was greatly increased in transgenic seedlings. Results of the photosynthetic capacity assessment showed that CdHEMA1 overexpression may considerably enhance the contents of photosynthetic pigments, OJIP curve and reaction center density (RC/CSo) to absorb (ABS/CSo, ABS/CSM) and capture (TRo/CSo) more light energy, hence improve the performance indices PIABS and PICS compared to the wild type. The successful completion of this project would provide a solid platform for further gene function study and molecular breeding of bermudagrass.

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“…The trial was initiated in August 2018 and ran over 12 months. Two tolerant plants commonly used in mine reclamation, i.e., Bermuda grass (Cynodon dactylon L.) and alfalfa (Medicago sativa L.) (Ye et al 2000;Heshmati and Pessarakli, 2011;Hu et al 2020), and a native grass broad-leaved paspalum (Paspalum wettsteinii Hack. ), were planted in nylon rhizo-bags and placed in plastic pots.…”

Section: Experimental Designmentioning

confidence: 99%

Evaluation of acid mine drainage sludge as soil substitute for the reclamation of mine solid wastes

Chi

Lin

Zhuang

et al. 2021

Environ Sci Pollut Res

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THRESHOLD MODEL IN STUDIES OF ECOLOGICAL RECOVERY IN BERMUDAGRASS (CYNODON DACTYLONL.) UNDER NUTRIENT STRESS CONDITIONS

Cited by 9 publications

References 32 publications

BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

Genetic manipulation of bermudagrass photosynthetic biosynthesis using Agrobacterium‐mediated transformation

Evaluation of acid mine drainage sludge as soil substitute for the reclamation of mine solid wastes

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