Growth and Yield Responses of Switchgrass Ecotypes to Temperature

Kandel, Tanka P.; Wu, Yanqi; Kakani, Vijaya Gopal

doi:10.4236/ajps.2013.46145

Cited by 20 publications

(18 citation statements)

References 15 publications

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“…The greater LAI in 2012 might be the result of higher temperatures during early growth periods, which also decreased the LAI differences among upland and lowland ecotypes. These results are in agreement with previous research that switchgrass leaf/stem ratio increases at higher temperatures in both upland and lowland ecotypes [51]. However, in 2013, clear differences between upland and lowland switchgrass varieties for their LAI throughout the growing season occurred, clearly indicating an ecotypic effect.…”

Section: Discussionsupporting

confidence: 93%

“…This might be explained by the fact that at higher temperatures switchgrass varieties produced greater tiller numbers in 2012, and resulted in higher DMY than 2013. Kandel et al [51] reported similar findings that at higher temperatures root/shoot and leaf/stem ratios increase in both upland and lowland ecotypes. Biomass yields of switchgrass ecotypes increased in a somewhat linear manner as the growing season progressed in both years.…”

Section: Discussionmentioning

confidence: 64%

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Developmental Morphology and Biomass Yield of Upland and Lowland Switchgrass Ecotypes Grown in Iowa

et al. 2018

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Sustainable development of the bioenergy industry will depend upon the amount and quality of bioenergy feedstock produced. Switchgrass (Panicum virgatum L.) is a model lignocellulosic bioenergy crop but critical information is lacking for improved management, growth, and development simulation model calibration. A field study was conducted near Ames, IA during 2012-2013 with the objective to evaluate upland ("Cave-in-Rock", 'Trailblazer' and 'Blackwell') and lowland ("Kanlow" and "Alamo") switchgrass ecotypes for harvest timing on morphology (i.e., phenology, leaf area index (LAI), and biomass yield). The experiment used a randomized complete block design, with three upland and two lowland varieties harvested at six dates annually. In both years, delaying harvest to later maturity increased biomass yield; lowland cultivars produced greater biomass yield (6.15 tons ha −1 ) than upland ecotypes (5.10 tons ha −1 ). Lowland ecotypes had delayed reproductive development compared with upland ecotypes. At the end of both growing seasons, upland ecotypes had greater mean stage count (MSC) than lowland ecotypes. "Cave-in-Rock" had greatest MSC and LAI, but did not produce the greatest biomass. Relationships were nonlinear between MSC and biomass yield, with significant cultivar-year interaction. The relationship between biomass yield and MSC will be useful for improving switchgrass, including cultivar selection, fertilizer application, and optimum harvest time.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 64%

Developmental Morphology and Biomass Yield of Upland and Lowland Switchgrass Ecotypes Grown in Iowa

et al. 2018

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“…The strong repression of the genes involved in glucose metabolism strongly supports the significant reduction reported in the cellulose and hemicellulose levels in response to heat stress in switchgrass cultivars [27]. The down regulation of metabolism in general, nitrogen and phosphorus metabolism in particular will have pronounced impact on vegetative growth (Figure 1).…”

Section: Resultssupporting

confidence: 70%

Transcriptome analysis of heat stress response in switchgrass (Panicum virgatumL.)

Wang

Tang

et al. 2013

BMC Plant Biol

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BackgroundGlobal warming predictions indicate that temperatures will increase by another 2-6°C by the end of this century. High temperature is a major abiotic stress limiting plant growth and productivity in many areas of the world. Switchgrass (Panicum virgatum L.) is a model herbaceous bioenergy crop, due to its rapid growth rate, reliable biomass yield, minimal requirements of water and nutrients, adaptability to grow on marginal lands and widespread distribution throughout North America. The effect of high temperature on switchgrass physiology, cell wall composition and biomass yields has been reported. However, there is void in the knowledge of the molecular responses to heat stress in switchgrass.ResultsWe conducted long-term heat stress treatment (38°/30°C, day/night, for 50 days) in the switchgrass cultivar Alamo. A significant decrease in the plant height and total biomass was evident in the heat stressed plants compared to controls. Total RNA from control and heat stress samples were used for transcriptome analysis with switchgrass Affymetrix genechips. Following normalization and pre-processing, 5365 probesets were identified as differentially expressed using a 2-fold cutoff. Of these, 2233 probesets (2000 switchgrass unigenes) were up-regulated, and 3132 probesets (2809 unigenes) were down-regulated. Differential expression of 42 randomly selected genes from this list was validated using RT-PCR. Rice orthologs were retrieved for 78.7% of the heat stress responsive switchgrass probesets. Gene ontology (GOs) enrichment analysis using AgriGO program showed that genes related to ATPase regulator, chaperone binding, and protein folding was significantly up-regulated. GOs associated with protein modification, transcription, phosphorus and nitrogen metabolic processes, were significantly down-regulated by heat stress.ConclusionsPlausible connections were identified between the identified GOs, physiological responses and heat response phenotype observed in switchgrass plants. Comparative transcriptome analysis in response to heat stress among four monocots – switchgrass, rice, wheat and maize identified 16 common genes, most of which were associated with protein refolding processes. These core genes will be valuable biomarkers for identifying heat sensitive plant germplasm since they are responsive to both short duration as well as chronic heat stress treatments, and are also expressed in different plant growth stages and tissue types.

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“…S4-S6). Another study documented similar leaf area decline under high temperatures for switchgrass [28]. Additionally, during the high temperature period, we observed that switchgrass leaves rolled causing a possible under-measurement of LAI in the experimental data collected by a ceptometer.…”

Section: Discussionsupporting

confidence: 70%

Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas

Zhang

Juenger

Osorio³

et al. 2017

Bioenerg. Res.

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Crop simulation models are increasingly being used to understand the feasibility of large-scale cellulosic biofuel production along with the multi-dimensional impacts on environmental sustainability. However, how the uncertainty in model parameters impacts model performance for sustainability is unclear. In this case study, sensitivity analyses were conducted for three switchgrass sustainability metrics: total biomass production, nitrogen loss, and soil carbon change using the APEX (Agricultural Policy/Environmental eXtender) model. Fifteen out of the 45 parameters (25 crop growth (CROP) parameters and 20 additional model parameters (PARM)) were identified as influential for the three sustainability metrics for three lowland genotypes (WBC, AP13, and KAN) across two locations (Temple, TX, and Austin, TX). Our sensitivity results showed that parameter importance was not dependent on the genotypes but depended on the variables of interest, and differed only slightly between locations. Influential belowground-related CROP and PARM parameters were identified for each sustainability metric, indicating that belowground-related parameters are just as important as commonly measured aboveground CROP parameters.Further investigation of the linear or non-linear relationships and the two-way interactions between each of the individual influential parameters with the three sustainability metrics reflected the functions and characteristics within the APEX model and the interrelations among different processes. Strong interactions between the most influential parameters for total biomass, nitrogen loss, and soil carbon change also highlighted the importance of accurately setting these parameters. Identification of influential model parameters for switchgrass sustainability may help guide field measurements and provide further understanding of the interrelated processes in the APEX model. Furthermore, future field experiments can be designed to measure these influential parameters and understand the non-linear relationships identified between influential parameters and response variables. More accurate model parameterization will help improve APEX model performance and our understanding of the possible underlying physiological mechanisms.

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Growth and Yield Responses of Switchgrass Ecotypes to Temperature

Cited by 20 publications

References 15 publications

Developmental Morphology and Biomass Yield of Upland and Lowland Switchgrass Ecotypes Grown in Iowa

Developmental Morphology and Biomass Yield of Upland and Lowland Switchgrass Ecotypes Grown in Iowa

Transcriptome analysis of heat stress response in switchgrass (Panicum virgatumL.)

Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas

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