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Dr. MANYOWA MEKI
Texas A&M AgriLife Research, Blackland Research and Extension Center

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0 Climate Change Impacts
0 Crop modelling
0 Agricultural sustainability
0 Agricultural intensification
0 Best management practices

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Journal article
Published: 24 April 2021 in Agronomy
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The efficacy of C4 grasses as feedstocks for liquid fuel production and their climate mitigation potential remain unresolved in the tropics. To identify highly convertible C4 grasses, we measured final fuels and postprocess biomass produced in two laboratory-scale conversion pathways across 12 species and varieties within the Poaceae (grass) family. Total mass, carbon, and energy in final fuels and postprocess biomass were assessed based on field mass and area-based production. Two lignocellulosic processes were investigated: (1) anaerobic digestion (AD) to methane and (2) hot water pretreatment and enzymatic hydrolysis (HWP-EH) to ethanol. We found AD converted lignocellulose to methane more efficiently in terms of carbon and energy compared to ethanol production using HWP-EH, although improvements to and the optimization of each process could change these contrasts. The resulting data provide design limitations for agricultural production and biorefinery systems that regulate these systems as net carbon sources or sinks to the atmosphere. Median carbon recovery in final fuels and postprocess biomass from the studied C4 grasses were ~5 Mg C ha−1 year−1 for both methane and ethanol, while median energy recovery was ~200 MJ ha−1 year−1 for ethanol and ~275 MJ ha−1 year−1 for methane. The highest carbon and energy recovery from lignocellulose was achieved during methane production from a sugarcane hybrid called energycane, with ~10 Mg C ha−1 year−1 and ~450 MJ ha−1 year−1 of carbon and energy recovered, respectively, from fuels and post-process biomass combined. Carbon and energy recovery during ethanol production was also highest for energycane, with ~9 Mg C ha−1 year−1 and ~350 MJ ha−1 year−1 of carbon and energy recovered in fuels and postprocess biomass combined. Although several process streams remain unresolved, agricultural production and conversion of C4 grasses must operate within these carbon and energy limitations for biofuel and bioenergy production to be an atmospheric carbon sink.

ACS Style

Jon Wells; Susan Crow; Samir Khanal; Scott Turn; Andrew Hashimoto; Jim Kiniry; Norman Meki. Anaerobic Digestion and Hot Water Pretreatment of Tropically Grown C4 Energy Grasses: Mass, Carbon, and Energy Conversions from Field Biomass to Fuels. Agronomy 2021, 11, 838 .

AMA Style

Jon Wells, Susan Crow, Samir Khanal, Scott Turn, Andrew Hashimoto, Jim Kiniry, Norman Meki. Anaerobic Digestion and Hot Water Pretreatment of Tropically Grown C4 Energy Grasses: Mass, Carbon, and Energy Conversions from Field Biomass to Fuels. Agronomy. 2021; 11 (5):838.

Chicago/Turabian Style

Jon Wells; Susan Crow; Samir Khanal; Scott Turn; Andrew Hashimoto; Jim Kiniry; Norman Meki. 2021. "Anaerobic Digestion and Hot Water Pretreatment of Tropically Grown C4 Energy Grasses: Mass, Carbon, and Energy Conversions from Field Biomass to Fuels." Agronomy 11, no. 5: 838.

Journal article
Published: 30 October 2020 in Agronomy
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To identify eco-efficient bean cultivars that can be planted at high densities for sustainable bean production under climate change, this study analyzed the performance of ten dry bean (Phaseolus vulgaris L.) cultivars grown at 90,000, 145,000 and 260,000 plants ha−1 under rainfed semi-arid conditions in Mexico. The study compared the yield and yield components (leaf area index (LAI), pods per plant, and hundred seed weight) of the cultivars. We also analyzed the dry matter distribution (DMD), growth rate (GR), radiation use efficiency (RUE), and harvest index (HI) of the best performing cultivars to determine how they respond to higher densities. The cultivars were established under similar planting and management conditions during two growing seasons. The precipitation for the first and second seasons were 175 and 492 mm, respectively, representing 57% and 160% of the mean precipitation in the area during the July–October growing period. Pinto Saltillo, a drought-tolerant indeterminate semi-prostrate cultivar, and Azufrado 2, a determinate shrub cultivar, performed best at high densities under low-precipitation conditions (175 mm). Both cultivars responded to the highest density (260,000 plants ha−1) with increases of 54% to 69% (0.7 to 1.1) in LAI and 21% to 86% (0.32–0.81 Mg ha−1) in yield. The two cultivars responded to increasing plant density with a modification in their fraction of DMD over plant parts and a change in their GR from 0.23–0.25 at low density to 0.96–1.74 gr m−2 day−1 at high density. The two cultivars had an RUE of 3.8 to 4.4 g MJ−1 and HI of 0.31 to 0.36 at high planting density. Farmers’ use of these commercially available cultivars proven to have high yields and the ability to respond favorably to high densities under rainfed conditions can be a viable short-term strategy to increase dry bean production for sustainable agriculture in semi-arid temperate regions.

ACS Style

Alma Delia Baez-Gonzalez; Ricardo Fajardo-Diaz; Jose Saul Padilla-Ramirez; Esteban Salvador Osuna-Ceja; James R. Kiniry; Manyowa N. Meki; Efraín Acosta-Díaz. Yield Performance and Response to High Plant Densities of Dry Bean (Phaseolus vulgaris L.) Cultivars under Semi-Arid Conditions. Agronomy 2020, 10, 1684 .

AMA Style

Alma Delia Baez-Gonzalez, Ricardo Fajardo-Diaz, Jose Saul Padilla-Ramirez, Esteban Salvador Osuna-Ceja, James R. Kiniry, Manyowa N. Meki, Efraín Acosta-Díaz. Yield Performance and Response to High Plant Densities of Dry Bean (Phaseolus vulgaris L.) Cultivars under Semi-Arid Conditions. Agronomy. 2020; 10 (11):1684.

Chicago/Turabian Style

Alma Delia Baez-Gonzalez; Ricardo Fajardo-Diaz; Jose Saul Padilla-Ramirez; Esteban Salvador Osuna-Ceja; James R. Kiniry; Manyowa N. Meki; Efraín Acosta-Díaz. 2020. "Yield Performance and Response to High Plant Densities of Dry Bean (Phaseolus vulgaris L.) Cultivars under Semi-Arid Conditions." Agronomy 10, no. 11: 1684.

Journal article
Published: 07 October 2020 in Agronomy
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Given a rising demand for quality assurance, rather than solely yield, supplemental irrigation plays an important role to ensure the viability and profitability of vegetable crops from unpredictable changes in weather. However, under drought conditions, agricultural irrigation is often given low priority for water allocation. This reduced water availability for agriculture calls for techniques with greater irrigation efficiency, that do not compromise crop quality and yield, and that provide economic benefit for producers. This study developed vegetable growing models for eight different vegetable crops (bush bean, green bean, cabbage, peppermint, spearmint, yellow straight neck squash, zucchini, and bell pepper) based on data from several years of field research. The ALMANAC model accurately simulated yields and water use efficiency (WUE) of all eight vegetables. The developed vegetable models were used to evaluate the effects of various irrigation regimes on vegetable growth and production in several locations in the Winter Garden Region of Texas, under variable weather conditions. Based on our simulation results from 960 scenarios, optimal irrigation amounts that produce high yield as well as reasonable economic profit to producers were determined for each vegetable crop. Overall, yields for all vegetables increased as irrigation amounts increased. However, irrigation amounts did not have a sustainable impact on vegetable yield at high irrigation treatments, and the WUEs of most vegetables were not significantly different among various irrigation regimes. When vegetable yields were compared with water cost, the rate decreased as irrigation amounts increased. Thus, producers will not receive economic benefits when vegetable irrigation water demand is too high.

ACS Style

Sumin Kim; Manyowa N. Meki; Sojung Kim; James R. Kiniry. Crop Modeling Application to Improve Irrigation Efficiency in Year-Round Vegetable Production in the Texas Winter Garden Region. Agronomy 2020, 10, 1525 .

AMA Style

Sumin Kim, Manyowa N. Meki, Sojung Kim, James R. Kiniry. Crop Modeling Application to Improve Irrigation Efficiency in Year-Round Vegetable Production in the Texas Winter Garden Region. Agronomy. 2020; 10 (10):1525.

Chicago/Turabian Style

Sumin Kim; Manyowa N. Meki; Sojung Kim; James R. Kiniry. 2020. "Crop Modeling Application to Improve Irrigation Efficiency in Year-Round Vegetable Production in the Texas Winter Garden Region." Agronomy 10, no. 10: 1525.

Journal article
Published: 04 July 2020 in Agronomy
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Sorghum is the world’s fifth major cereal in terms of production and acreage. It is expected that its growth will be affected by the increase in air temperature, an important component of global climate change. Our objective was to use the Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) model to (a) evaluate the impact of climate warming on forage and grain sorghum production in Argentina and (b) to analyze to what extent yield changes were associated with changes in water or nitrogen stress days. For model calibration, we used previous information related to the morpho-physiological characteristics of both sorghum types and several soil parameters. We then used multiyear field data of sorghum yields for model validation. Yield simulations were conducted under three possible climate change scenarios: 1, 2, and 4 °C increase in mean annual temperature. ALMANAC successfully simulated mean yields of forage and grain sorghum: root mean square error (RMSE): 2.6 and 1.0 Mg ha−1, respectively. Forage yield increased 0.53 Mg ha−1, and grain yield decreased 0.27 Mg ha−1 for each degree of increase in mean annual temperature. Yields of forage sorghum tended to be negatively associated with nitrogen stress (r = −0.94), while grain sorghum yield was negatively associated with water stress (r = −0.99). The information generated allows anticipating future changes in crop management and genetic improvement programs in order to reduce the yield vulnerability.

ACS Style

Magdalena Druille; Amber Williams; Marcelo Torrecillas; Sumin Kim; Norman Meki; James R. Kiniry. Modeling Climate Warming Impacts on Grain and Forage Sorghum Yields in Argentina. Agronomy 2020, 10, 964 .

AMA Style

Magdalena Druille, Amber Williams, Marcelo Torrecillas, Sumin Kim, Norman Meki, James R. Kiniry. Modeling Climate Warming Impacts on Grain and Forage Sorghum Yields in Argentina. Agronomy. 2020; 10 (7):964.

Chicago/Turabian Style

Magdalena Druille; Amber Williams; Marcelo Torrecillas; Sumin Kim; Norman Meki; James R. Kiniry. 2020. "Modeling Climate Warming Impacts on Grain and Forage Sorghum Yields in Argentina." Agronomy 10, no. 7: 964.

Article
Published: 03 April 2020 in Agronomy Journal
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Vetivergrass [Chrysopogon zizanioides (L.) Roberty] is a multi‐purpose crop that has an untapped potential for biofuel production. We conducted a field study at Temple, Texas to determine plant growth characteristics that make vetivergrass an ideal candidate bioenergy feedstock crop. Overall, the high biomass yield (avg.18.4±0.7 Mg ha–1) can be attributed to the high leaf area index (LAI, avg. 12.7±2.5) and crop growth rates that ranged from 2.7±0.1 to 15.7±0.1 g m−2 d−1. Plant tissue N and P concentrations ranged from 0.59% to 1.66% and 0.06% to 0.15%, respectively. Surprisingly, the radiation use efficiency (RUE, avg. 2.2±0.1 g MJ–1) was not high relative to other highly productive grasses. Biomass yield was highly correlated to plant height (avg. 2.1±0.1 m) and LAI (Pearson, r = 0.96 and 0.77, respectively). Data from the field experiment provided plant coefficients that were used to develop an Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) vetivergrass model to assess dryland and irrigated interannual and spatial biomass yields across TX. ALMANAC simulated dryland and irrigated yields ranged from 0.8 to 39.3 (Avg., 17.2) Mg ha−1 and 9.1 to 47.0 (Avg., 25.4) Mg ha−1, respectively. There was huge spatial variation in dryland and irrigated yields, with CV percent values of 20% and 15%, respectively. Similarly, dryland and irrigated inter‐annual yields respectively had CV percent values of 25% and 17%. State‐wide simulation model assessments complement field studies, and furthermore allow bioenergy companies and investors to better estimate biofuel feedstock potential for new crops such as vetivergrass. This article is protected by copyright. All rights reserved

ACS Style

Manyowa N. Meki; James R. Kiniry; Abeyou W. Worqlul; Sumin Kim; Amber Williams; Javier M. Osorio; John Reilley. Field and simulation‐based assessment of vetivergrass bioenergy feedstock production potential in Texas. Agronomy Journal 2020, 112, 2692 -2707.

AMA Style

Manyowa N. Meki, James R. Kiniry, Abeyou W. Worqlul, Sumin Kim, Amber Williams, Javier M. Osorio, John Reilley. Field and simulation‐based assessment of vetivergrass bioenergy feedstock production potential in Texas. Agronomy Journal. 2020; 112 (4):2692-2707.

Chicago/Turabian Style

Manyowa N. Meki; James R. Kiniry; Abeyou W. Worqlul; Sumin Kim; Amber Williams; Javier M. Osorio; John Reilley. 2020. "Field and simulation‐based assessment of vetivergrass bioenergy feedstock production potential in Texas." Agronomy Journal 112, no. 4: 2692-2707.

Journal article
Published: 23 March 2020 in Agronomy
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Mexico holds the largest single bean production area in the world that is vulnerable to drought. Using field data and two future climate scenarios (RCP4.5 and RCP8.5) for the period 2020–2039, this study evaluated three common bean (Phaseolus vulgaris L.) cultivars planted under rainfed conditions at different densities in two locations in the north-central Mexican semi-arid temperate highlands. The sowing densities were 90,000, 145,000, and 260,000 plants ha−1 established in single rows (SR), three rows (3R), and six rows (6R), respectively. The climate change scenarios were derived from an assembly model integrating 11 general circulation models (GCM) selected for Mexico with a 30” arc resolution. The baseline climate was for the period 1961–2010. The ALMANACMEX model (USDA-ARS-INIFAP, Temple, USA) was parameterized and evaluated and then re-run using the climate scenarios. Beans planted at 6R showed the highest increase in seed yield in both climate scenarios, although the response varied by cultivar and time periods. For the growth habit III cultivars, Flor de Mayo Bajio showed no difference in yield, while Pinto Saltillo, a drought-resistant cultivar, showed increases of 13% to 16% at 6R only until 2033. Growth habit I cultivar Azufrado 2 showed more than 60% increases at 6R in both climate scenarios for the full period 2020–2039. These results suggest that considering the projected climate conditions, high sowing densities may be a viable agronomic option for common bean production under rainfed conditions in semi-arid temperate regions, such as the highlands of Mexico, in the near future; however, the selection of the cultivar is a key element to consider in this regard.

ACS Style

Alma Delia Baez-Gonzalez; Ricardo Fajardo-Díaz; Giovanni Garcia-Romero; Esteban Osuna-Ceja; James R. Kiniry; Manyowa N. Meki. High Sowing Densities in Rainfed Common Beans (Phaseolus vulgaris L.) in Mexican Semi-Arid Highlands under Future Climate Change. Agronomy 2020, 10, 442 .

AMA Style

Alma Delia Baez-Gonzalez, Ricardo Fajardo-Díaz, Giovanni Garcia-Romero, Esteban Osuna-Ceja, James R. Kiniry, Manyowa N. Meki. High Sowing Densities in Rainfed Common Beans (Phaseolus vulgaris L.) in Mexican Semi-Arid Highlands under Future Climate Change. Agronomy. 2020; 10 (3):442.

Chicago/Turabian Style

Alma Delia Baez-Gonzalez; Ricardo Fajardo-Díaz; Giovanni Garcia-Romero; Esteban Osuna-Ceja; James R. Kiniry; Manyowa N. Meki. 2020. "High Sowing Densities in Rainfed Common Beans (Phaseolus vulgaris L.) in Mexican Semi-Arid Highlands under Future Climate Change." Agronomy 10, no. 3: 442.

Journal article
Published: 27 September 2019 in Agronomy
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Cultivation of highly salt-tolerant plants (i.e., halophytes), may provide a viable alternative to increase productivity compared to conventional salt-sensitive crops, increasing the economic potential of salt-affected lands that comprise ~20% of irrigated lands worldwide. In this study the Agricultural Policy/Environmental eXtender (APEX) model was adapted to simulate growth of the halophyte quinoa, along with salt dynamics in the plant-soil-water system. Model modifications included salt uptake and salt stress functions formulated using greenhouse data. Data from a field site were used to further parameterize and calibrate the model. Initial simulation results were promising, but differences between simulated and observed soil salinity and plant salt values during the growing season in the calibration suggest that additional improvements to salt uptake and soil salinity algorithms are needed. To demonstrate utility of the modified APEX model, six scenarios were run to estimate quinoa biomass production and soil salinity with different irrigation managements and salinities. Simulated annual biomass was sensitive to soil moisture, and root zone salinity increased in all scenarios. Further experiments are needed to improve understanding of crop salt uptake dynamics and stress sensitivities so that future model updates and simulations better represent salt dynamics in plants and soils in agricultural settings.

ACS Style

Nicole Goehring; Paul Verburg; Laurel Saito; Jaehak Jeong; Manyowa N. Meki. Improving Modeling of Quinoa Growth Under Saline Conditions Using the Enhanced Agricultural Policy Environmental eXtender Model. Agronomy 2019, 9, 592 .

AMA Style

Nicole Goehring, Paul Verburg, Laurel Saito, Jaehak Jeong, Manyowa N. Meki. Improving Modeling of Quinoa Growth Under Saline Conditions Using the Enhanced Agricultural Policy Environmental eXtender Model. Agronomy. 2019; 9 (10):592.

Chicago/Turabian Style

Nicole Goehring; Paul Verburg; Laurel Saito; Jaehak Jeong; Manyowa N. Meki. 2019. "Improving Modeling of Quinoa Growth Under Saline Conditions Using the Enhanced Agricultural Policy Environmental eXtender Model." Agronomy 9, no. 10: 592.

Journal article
Published: 31 July 2017 in Sustainability
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Crop models with well-tested parameters may help improve sugarcane productivity for food and biofuel generation, especially in rainfed areas where studies are scarce. This study aimed to calibrate crop parameters for the sugarcane cultivar CP 72-2086, an early-maturing cultivar widely grown in Mexico and other countries, and evaluate their adequacy in simulating sugarcane in a diverse range of rainfed conditions. For the calibration and evaluation of parameters, the ALMANAC model was used with climate, soil, management, and yield for two growing seasons from 30 farms in three regions (Northeastern Mexico, Gulf of Mexico, and Pacific Mexico). Statistical analyses were made using regression analysis and mean squared deviation and its three components, i.e., the squared bias, the lack of correlation weighted by the standard deviations, and the squared difference between standard deviations. Model simulations with a light extinction coefficient (k) of 0.69, maximum leaf area index of 7.5, leaf area index decline rate of 0.3, optimal and minimum temperature for plant growth of 32 °C and 11 °C, respectively, potential heat units of 6000 to 7400 degree days (base 11 °C), harvest index of 0.9; maximum crop height of 4.0 m, and root depth of 2.0 m showed highest accuracy and captured best the magnitude of yield fluctuations with a root mean squared deviation of 7.8 Mg ha−1. The parameters were found to be reasonable to use in simulating sugarcane in diverse regions under rainfed conditions. Using a dynamic value of k (varying during the growing season) deserves further study as it may help improve crop model precision.

ACS Style

Alma Delia Baez-Gonzalez; James R. Kiniry; Manyowa N. Meki; Jimmy Williams; Marcelino Alvarez-Cilva; Jose L. Ramos-Gonzalez; Agustin Magallanes-Estala; Gonzalo Zapata-Buenfil. Crop Parameters for Modeling Sugarcane under Rainfed Conditions in Mexico. Sustainability 2017, 9, 1337 .

AMA Style

Alma Delia Baez-Gonzalez, James R. Kiniry, Manyowa N. Meki, Jimmy Williams, Marcelino Alvarez-Cilva, Jose L. Ramos-Gonzalez, Agustin Magallanes-Estala, Gonzalo Zapata-Buenfil. Crop Parameters for Modeling Sugarcane under Rainfed Conditions in Mexico. Sustainability. 2017; 9 (8):1337.

Chicago/Turabian Style

Alma Delia Baez-Gonzalez; James R. Kiniry; Manyowa N. Meki; Jimmy Williams; Marcelino Alvarez-Cilva; Jose L. Ramos-Gonzalez; Agustin Magallanes-Estala; Gonzalo Zapata-Buenfil. 2017. "Crop Parameters for Modeling Sugarcane under Rainfed Conditions in Mexico." Sustainability 9, no. 8: 1337.