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5. In Vitro Seed Germination Response of Corn, Cotton, and Soybean to Temperature

Author

Walne, Charles Hunt, Alsajri, Firas A., Gajanayake, Bandara, Lokhande, Suresh, Seepaul, Ramdeo, Wijewardana, Chathurika, and Reddy, K. Raja

Subjects
Soil temperature -- Influence -- Environmental aspects, Corn -- Physiological aspects, Germination -- Observations, Soybeans -- Physiological aspects, Cotton (Plant) -- Physiological aspects, Science and technology
Abstract

Seed germination is the first developmental phase in a plant's life cycle that is followed by emergence from the soil, successful seedling and establishment, and fruitful yield. Seed germination is influenced by multiple environmental factors such as temperature, moisture, and aeration. An in vitro experiment was conducted to quantify the effects of temperatures ranging from 10[degrees]C to 42.5[degrees]C on germination properties of corn, cotton, and soybean seeds. Cumulative seed germination was recorded over time, was fitted with a three-parameter sigmoidal function to calculate maximum seed germination and seed germination rate. Maximum seed germination was significantly influenced by the interaction of temperature and species. The seed germination rate was further analyzed as a function of temperature by fitting bilinear and quadratic functions to the data. Cardinal temperatures (minimum, optimum, and maximum) were estimated from that regression analysis. Corn displayed the highest optimal temperature of 34.6[degrees]C. Cotton showed higher minimum and maximum cardinal temperatures than both corn and soybean. The cardinal temperatures and functional relationships between seed germination rate and temperature determined in this experiment will be useful to update crop simulation models and assess the best planting dates for rapid, successful germination based on environmental conditions. Keywords: Cardinal temperatures, corn, cotton, soybean, maximum seed germination, optimum temperature, seed germination models, seed germination rate Abbreviations: MSG, maximum seed germination; SGR, seed germination rate, INTRODUCTION In Mississippi, soybean [Glycine max (L.) Merr.], cotton (Gossypium hirsutum L.), and corn (Zea mays L.) are three of the most widely grown agronomically important crop species. In 2018, [...]

Published
2020

13. Modeling Yield, Biogenic Emissions, and Carbon Sequestration in Southeastern Cropping Systems With Winter Carinata

Author

Field, John L., primary, Zhang, Yao, additional, Marx, Ernie, additional, Boote, Kenneth J., additional, Easter, Mark, additional, George, Sheeja, additional, Hoghooghi, Nahal, additional, Johnston, Glenn, additional, Masum, Farhad Hossain, additional, Mulvaney, Michael J., additional, Paustian, Keith, additional, Seepaul, Ramdeo, additional, Swan, Amy, additional, Williams, Steve, additional, Wright, David, additional, and Dwivedi, Puneet, additional

Published
2022
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14. Brassica carinata as an off-season crop in the southeastern USA: Determining optimum sowing dates based on climate risks and potential effects on summer crop yield

Author

Nóia Júnior, Rogério de Souza, primary, Fraisse, Clyde W., additional, Bashyal, Mahesh, additional, Mulvaney, Michael J., additional, Seepaul, Ramdeo, additional, Zientarski Karrei, Mauricio A., additional, Iboyi, Joseph Enye, additional, Perondi, Daniel, additional, Cerbaro, Vinicius Andrei, additional, and Boote, Kenneth J., additional

Published
2022
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20. A regional inter‐disciplinary partnership focusing on the development of a carinata‐centered bioeconomy

Author

George, Sheeja, primary, Seepaul, Ramdeo, additional, Geller, Dan, additional, Dwivedi, Puneet, additional, DiLorenzo, Nicolas, additional, Altman, Rich, additional, Coppola, Ed, additional, Miller, Stephen A., additional, Bennett, Rick, additional, Johnston, Glenn, additional, Streit, Leon, additional, Csonka, Steve, additional, Field, John, additional, Marois, Jim, additional, Wright, David, additional, Small, Ian M., additional, and Philippidis, George P., additional

Published
2021
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22. Brassica carinata : Biology and agronomy as a biofuel crop

Author

Seepaul, Ramdeo, primary, Kumar, Shivendra, additional, Iboyi, Joseph E., additional, Bashyal, Mahesh, additional, Stansly, Theodor L., additional, Bennett, Rick, additional, Boote, Kenneth J., additional, Mulvaney, Michael J., additional, Small, Ian M., additional, George, Sheeja, additional, and Wright, David L., additional

Published
2021
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32. Frost Damage of Carinata Grown in the Southeastern US

Author

Mulvaney, Michael J., primary, Seepaul, Ramdeo (Andy), primary, Small, Ian M., primary, Wright, David L., primary, Paula-Moraes, Silvana V., primary, Crozier, Carl, primary, Cockson, Paul, primary, Whipker, Brian, primary, and Leon, Ramon, primary

Published
2018
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37. Brassica carinataand Brassica napusGrowth, Nitrogen Use, Seed, and Oil Productivity Constrained by Post‐Bolting Nitrogen Deficiency

Author

Seepaul, Ramdeo, Small, Ian M., Marois, Jim, George, Sheeja, and Wright, David L.

Abstract

Nitrogen limitation after bolting in oilseed brassicas limits reproductive performance as nutrients are sequentially translocated from leaves to developing reproductive structures. In addition to limiting crop growth and productivity, N deficiency may also modify the chemical composition and oil output of Brassica carinataA. Braun and B. napusL. A greenhouse study was conducted at the North Florida Research and Education Center in Quincy, FL, during 2014–2015 to determine the effects of N limitation on B. carinata(cultivar AAC A110) and B. napus(cultivar Canterra 1918) growth, seed and oil yields, N use, and fatty acid composition. Four N treatments (0, 33, 66, and 100% of N in full strength Hoagland solution) were imposed 78 d after planting (DAP) at bolting. At 154 DAP, carinata accumulated 19% greater biomass and nine times more reproductive branches than napus across all N levels. As a result, carinata produced 43% greater seed yield across all N levels than napus. This increased seed productivity resulted in greater agronomic efficiency (58%), apparent N recovery (59%), N utilization efficiency (41%), and partial factor productivity (29%) than napus, respectively. Restricting N availability (0 N) reduced carinata and napus oil yield by 35 and 50% respectively, relative to 100% N. Nitrogen availability during seed development and maturation had an effect on the synthesis of fatty acids and their quantities in the oils of mature carinata and napus seeds. This study demonstrated the plasticity of oilseed brassicas and the relationship of reduced growth to seed productivity as a function of N supply.

Published
2019
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38. Brassica carinataSeeding Rate and Row Spacing Effects on Morphology, Yield, and Oil

Author

Mulvaney, Michael J., Leon, Ramon G., Seepaul, Ramdeo, Wright, David L., and Hoffman, Travis L.

Abstract

Carinata growth and yield was influenced more by row spacing than seeding rate.Rows spaced at 36 cm maximized carinata yield.Carinata branching was favored by wider row spacing. Carinata (Brassica carinataA. Braun) is an oilseed crop with potential as a winter crop in the southeastern United States to diversify crop rotations and provide biofuel production and livestock feed. The objective was to evaluate the effects of row spacing and seeding rate on carinata yield and oil composition. Field experiments were conducted in Jay and Quincy, FL, from 2013 to 2016 evaluating carinata growth, seed and oil yield, and oil composition grown in a factorial arrangement of four seeding rates (3, 6, 9, and 12 kg ha−1) and four row spacings (18, 36, 53, and 89 cm). No interactions between seeding rate and row spacing were detected. Seeding rate did not influence any of the variables studied. In contrast, row spacing affected seed and oil yield, branch production, and pods per plant. Seed yield (ranked from highest to lowest) was 2761, 2286, 1851, and 1572 kg ha−1for rows spaced at 36, 18, 53, and 89 cm, respectively. Branching and pods per plant increased with row spacing. Neither seeding rate nor row spacing affected oil concentration and quality. Oil concentration averaged 40%, of which more than a third was erucic acid (C22:1). Protein concentration was 31%, and glucosinolate concentration was 93 μmol g−1. The results of the present study demonstrated that carinata can be successfully grown in the southeastern United States, reaching yields and oil quality similar to those reported at other latitudes, and can be a source of biofuel, protein for animal feed, and cropping system diversification for growers.

Published
2019
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39. Genotype, nitrogen and harvest management effects on switchgrass production

Author

Seepaul, Ramdeo and Seepaul, Ramdeo

Abstract

Use of switchgrass (Panicum virgatum L.) as a forage and feedstock species requires knowledge of fertilizer application rates and harvest timing to optimize yield and quality. Three experiments were conducted at the Brown Loam Branch Experiment Station, Raymond, MS to quantify nitrogen rates, harvest timing, and genotype effects on biomass, nutrient removal, chemical composition and ethanol yield. Dry matter yield varied with N rate, genotype, harvest frequency and timing. Yields among genotypes were: NF/GA992 = NF/GA001 (13.7 Mg ha⁻¹)> Alamo (11.6 Mg ha⁻¹)> Cave-in-Rock (6.1 Mg ha⁻¹). A single (9.5 Mg ha⁻¹) or two harvests annually (10.3 Mg ha⁻¹) produced the greatest dry matter yield. As harvest frequency increased from three (7.3Mg ha⁻¹) to six (5.9 Mg ha⁻¹) harvests annually, yield decreased. There was an effect of N application on yield, but not at application rates greater than 80 kg ha⁻¹. Nitrogen did not consistently affect tissue nutrient concentrations but more frequent harvests led to increased nutrient concentration. Nutrient removal responses to N application were mostly similar to the yield responses. Nitrogen use efficiency and recovery declined as N rate increased. Estimated ethanol yield averaged 162 L Mg⁻¹ for Alamo, NF/GA001 and NF/GA992 . A single (2.4 kL ha⁻¹) or 2 harvests annually (2.3 kL ha⁻¹) produced the greatest ethanol production and was correlated with by biomass yield. Nutrient removal, N use efficiency, N recovery and ethanol production were related to biomass yields rather than chemical composition differences. The findings in this dissertation will enable a database on management effects on ethanol yield and composition, enhance current biomass models, facilitate improved management of feedstock production inputs and improve feasibility of alternative fuel development.

Published
2014

40. Carinata Production in Florida

Author

Bliss, C. M., primary, Seepaul, Ramdeo, additional, Wright, David L., additional, Marois, James J., additional, Leon, Ramon, additional, Dufault, Nicholas, additional, George, Sheeja, additional, and Olson, Stephen M., additional

Published
2014
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41. Application of Hydrothermal Time Models to Predict Sclerotial Germination of Athelia rolfsii.

Author

Sanjel, Santosh, Guerra, Victor, Seepaul, Ramdeo, Mackowiak, Cheryl, Punja, Zamir K., Dufault, Nicholas, Tillman, Barry, Bradford, Kent J., and Small, Ian M.

Subjects
*GERMINATION, *FACTORIAL experiment designs, *SOIL classification, *SOIL temperature, *SOIL moisture, *SCLEROTIUM (Mycelium)
Abstract

Athelia rolfsii, causal agent of "southern blight" disease, is a soilbome fungal pathogen with a wide host range of more than 500 species. This study's objectives were to (i) quantify the effects of two environmental factors, temperature and soil moisture, on germination of A. rolfsii inoculum (sclerotia), which is a critical event for the onset of disease epidemics and (ii) predict the timing of sclerotial germination by applying populationbased threshold-type hydrothermal time (HTT) models. We conducted in vitro germination experiments with three isolates of A. rolfsii isolated from peanuts, which were tested at five temperatures (7), ranging from 17 to 40°C, four matric potentials (W) between -0.12 and -1.57 MPa, and two soil types (fine sand and loamy fine sand), using a factorial design. When Mm was maintained between -0.12 and -0.53 MPa, T from 22 to 34°C was found to be conducive to sclerotial germination (>50%). The HTT models were fitted for a range of T (22 to 34°C) and Mm (-0.12 to -1.57 MPa) that accounted for 84% or more of variation in the timing of sclerotial germination. The estimated base T ranged between 0 and 4.5°C and the estimated base Mm between -2.96 and -1.52 MPa. The results suggest that the HTT modeling approach is a suitable means of predicting the timing of A. rolfsii sclerotial germination. This HTT methodology can potentially be tested to fine-tune fungicide application timing and in-season A. rolfsii management strategies. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Switchgrass (Panicum virgatum L.) intraspecific variation and temperature tolerance classification using in vitro seed germination assay

Author

Seepaul, Ramdeo and Seepaul, Ramdeo

Subjects
Switchgrass., Switchgrass Seeds., Switchgrass Effect of temperature on., Germination., Panic raide., Panic raide Semences., Panic raide Effets de la température sur., Germination., Germination, Switchgrass
Abstract

An experiment was conducted to determine temperature effects on switchgrass seed germination, a native species with feedstock potential for the biofuel industry. Stratified seeds were germinated at constant temperatures, 15 to 45°C with 5°C interval. Maximum seed germination (MSG) and germination rate (GR), estimated by fitting sigmoid function to germination-time series data, varied among genotypes. Quadratic and bilinear models best described the MSG and GR responses to temperature, respectively. The mean cardinal temperatures, minimum, optimum and maximum, were 8.1, 26.6 and 45.1°C for MSG and 11.1, 33.1 and 46.0°C for GR, respectively, varied among genotypes. Genotypes were classified for temperature tolerance based on cumulative temperature response index: 'Summer' and 'Expresso' were identified as the most heat- and cold-tolerant genotypes, respectively. The functional algorithms and identified tolerant genotypes may be used to improve switchgrass models for field applications and breeding programs to develop new genotypes with enhanced tolerance for niche environments.

Published
2010

45. Environmental Factors Influencing Stem Rot Development in Peanut: Predictors and Action Thresholds for Disease Management.

Author

Sanjel, Santosh, Colee, James, Barocco, Rebecca L., Dufault, Nicholas S., Tillman, Barry L., Punja, Zamir K., Seepaul, Ramdeo, and Small, Ian M.

Subjects
*PEANUTS, *DISEASE management, *DECISION trees, *AKAIKE information criterion, *DECISION making, *SOLAR radiation
Abstract

Peanuts grown in tropical, subtropical, and temperate regions are susceptible to stem rot, which is a soilborne disease caused by Athelia rolfsii. Due to the lack of reliable environmental-based scheduling recommendations, stem rot control relies heavily on fungicides that are applied at predetermined intervals. We conducted inoculated field experiments for six site-years in North Florida to examine the relationship between germination of A. rolfsii sclerotia: the inoculum, stem rot symptom development in the peanut crop, and environmental factors such as soil temperature (ST), soil moisture, relative humidity (RH), precipitation, evapotranspiration, and solar radiation. Window-pane analysis with hourly and daily environmental data for 5- to 28-day periods before each disease assessment were evaluated to select model predictors using correlation analysis, regularized regression, and exhaustive feature selection. Our results indicated that within-canopy ST (at 0.05 m belowground) and RH (at 0.15 m aboveground) were the most important environmental variables that influenced the progress of mycelial activity in susceptible peanut crops. Decision tree analysis resulted in an easy-to-interpret one-variable model (adjusted R2 = 0.51, Akaike information criterion [AIC] = 324, root average square error [RASE] = 14.21) or two-variable model (adjusted R2 = 0.61, AIC = 306, RASE = 10.95) that provided an action threshold for various disease scenarios based on number of hours of canopy RH above 90% and ST between 25 and 35°C in a 14-day window. Coupling an existing preseason risk index for stem rot, such as Peanut Rx, with the environmentally based predictors identified in this study would be a logical next step to optimize stem rot management. [ABSTRACT FROM AUTHOR]

Published
2024
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