Vangimalla R. Reddy

Carbon dioxide diffusion across stomata and mesophyll and photo-biochemical processes as affected by growth CO2 and phosphorus nutrition in cotton.

Nutrients such as phosphorus may exert a major control over plant response to rising atmospheric carbon dioxide concentration (CO2), which is projected to double by the end of the 21st century. Elevated CO2 may overcome the diffusional limitations to photosynthesis posed by stomata and mesophyll and alter the photo-biochemical limitations resulting from phosphorus deficiency. To evaluate these ideas, cotton (Gossypium hirsutum) was grown in controlled environment growth chambers with three levels of phosphate (Pi) supply (0.2, 0.05 and 0.01mM) and two levels of CO2 concentration (ambient 400 and elevated 800μmolmol(-1)) under optimum temperature and irrigation. Phosphate deficiency drastically inhibited photosynthetic characteristics and decreased cotton growth for both CO2 treatments. Under Pi stress, an apparent limitation to the photosynthetic potential was evident by CO2 diffusion through stomata and mesophyll, impairment of photosystem functioning and inhibition of biochemical process including the carboxylation efficiency of ribulose-1,5-bisphosphate carboxylase/oxyganase and the rate of ribulose-1,5-bisphosphate regeneration. The diffusional limitation posed by mesophyll was up to 58% greater than the limitation due to stomatal conductance (gs) under Pi stress. As expected, elevated CO2 reduced these diffusional limitations to photosynthesis across Pi levels; however, it failed to reduce the photo-biochemical limitations to photosynthesis in phosphorus deficient plants. Acclimation/down regulation of photosynthetic capacity was evident under elevated CO2 across Pi treatments. Despite a decrease in phosphorus, nitrogen and chlorophyll concentrations in leaf tissue and reduced stomatal conductance at elevated CO2, the rate of photosynthesis per unit leaf area when measured at the growth CO2 concentration tended to be higher for all except the lowest Pi treatment. Nevertheless, plant biomass increased at elevated CO2 across Pi nutrition with taller plants, increased leaf number and larger leaf area.

Soil water dynamics in row and interrow positions in soybean (Glycine max L.)

Quantitative knowledge of infiltration processes and the mechanisms that control water movement in soil is necessary to properly manage water and chemical use in agricultural fields. The objective of this study was to compare the soil water content dynamics in row and interrow positions in a soybean crop (Glycine max L.) under conventional (plow) tillage. Two field plots (Beltsville silt loam soil, Fine-loamy mixed mesic Typic Fragiudult) were instrumented with Time Domain Reflectometry (TDR) probes at 0–10 cm, 0–25 cm and 0–40 cm depths. TDR probes were installed in the row and interrow positions. Soil water content was continuously monitored at 1 hour intervals. The distribution of infiltrated water and evapotranspiration showed strong row-interrow patterns. The row positions received significantly more water during precipitation than the interrow positions. Water loss, due to evapotranspiration, was also significantly greater in the row position than in the interrow position. Both plant and soil characteristics appeared to be important factors for infiltration and redistribution. The results of this study suggested that the presence of the crop canopy altered the surface boundary conditions of the soil and, hence, the volume of infiltrating water. Results of this study suggest that in order to model water movement in row crops, the ability to simulate canopy architecture and flow processes in two dimensions is necessary.

Predicting crop yields under climate change conditions from monthly GCM weather projections

Estimation of changes in crop yields is currently based on projections of atmospheric General Circulation Models (GCM) and the use of crop simulators. Crop simulators require daily input of environmental variables. GCMs produce monthly projections of climatic variables. Our objective was to explore the possibility of using monthly weather projections in yield estimates. We considered atmospheric CO2 level, total solar radiation, average maximum and minimum temperature, and rainfall for five months of the growing season. The group method of data handling (GMDH) was applied to relate crop yields to these variables. Projections of GCMs were downscaled to provide daily weather variables for the Mississippi Delta, and weather patterns were obtained in 50 replications for each GCM. The soybean crop simulator GLYCIM was used to generate crop yields on sandy loam, loam and silt loam soils. The equations built with GMDH explained 81‐85% of yield variability, and included solar radiation in July and August, CO2 level, minimum temperature in June and August, and rainfall in August. Published by Elsevier Science Ltd.

Drought Responses of Foliar Metabolites in Three Maize Hybrids Differing in Water Stress Tolerance

Maize (Zea mays L.) hybrids varying in drought tolerance were treated with water stress in controlled environments. Experiments were performed during vegetative growth and water was withheld for 19 days beginning 17 days after sowing. Genotypic comparisons used measured changes of leaf water potential or results were expressed by time of treatment. Total dry matter of the drought tolerant hybrid on the final harvest was 53% less than that of the intermediate and susceptible maize hybrids when plants were water sufficient. This showed that maize hybrids selected for extreme drought tolerance possessed a dwarf phenotype that affected soil water contents and leaf water potentials. Changes of shoot and root growth, leaf water potential, net photosynthesis and stomatal conductance in response to the time of water stress treatment were diminished when comparing the drought tolerant to the intermediate or susceptible maize hybrids. Genotypic differences were observed in 26 of 40 total foliar metabolites during water stress treatments. Hierarchical clustering revealed that the tolerant maize hybrid initiated the accumulation of stress related metabolites at higher leaf water potentials than either the susceptible or intermediate hybrids. Opposite results occurred when changes of metabolites in maize leaves were expressed temporally. The above results demonstrated that genotypic differences were readily observed by comparing maize hybrids differing in drought tolerance based on either time of treatment or measured leaf water potential. Current findings provided new and potentially important insights into the mechanisms of drought tolerance in maize.

EFFECTS OF CARBON DIOXIDE AND PHOSPHORUS SUPPLY ON POTATO DRY MATTER ALLOCATION AND CANOPY MORPHOLOGY

□ Data on combined effects of elevated carbon dioxide concentration (CO2) and phosphorus fertilization (P) on potato are scarce. Growth chamber studies (E1 and E2) that used three P and two CO2 levels were conducted. Leaf, stem, tuber, and stolon dry matter increased with P. Lateral-stem production was sensitive to P with a minimum 2.5-fold increase in mass. Leaf length increased an average 20.2% in E1 and 38.2% in E2 and leaf area increased an average 336% in E1 and 470% in E2 across CO2 levels. Tuber dry mass increased 22% in E1 and 38.2% in E2 in response to elevated CO2 and total dry mass by 14.1 and 15.4%. Tissue P contents increased with P but were unaffected by CO2. Effects of P on canopy branching were associated with plant N status. The studies suggest elevated CO2 levels are unlikely to alter potato P requirements on a unit mass basis.

Growth and photosynthetic responses of soybean to short-term cold temperature

Abstract Soybean seedlings often experience short-term cold temperature during the growing season that may affect subsequent growth and production. The main objective of this study was to evaluate the effects of short-term cold temperature on soybean ( Glycine max [L.] Merr. ‘Hutcheson’) growth and development, biomass partitioning, photosynthesis, and carbohydrate metabolism. The research project tested the hypothesis that short-term cold temperature delays reproductive stages, by reducing photosynthesis and altering biomass allocation. Soybean plants were grown in controlled environmental conditions at a range of day/night temperatures (23/18°C, and 33/28°C) and exposed to a cold treatment of 8°C for 24h at the V5 and R1 stages. The cold treatments delayed R1 for plants grown at 28/23°C, delayed R2 for plants grown at all three temperatures by up to 7 d, and prolonged the time periods between R1 and R2 stages. Leaf photosynthesis in the treated plants was 81%, 75%, and 79% of controls 5 h after the treatment for plants grown at 23/18°C, 28/23°C, and 33/28°C, respectively. A greater reduction in photosynthesis was obtained after the second cold treatment was applied at R1. Total soluble carbohydrate in leaves was reduced by the short-term cold temperature 5 h after the cold treatment. Two cycles of cold temperatures also increased the partitioning of total biomass to vegetative shoots, but decreased the partitioning to flowers and pods for all three temperatures. Our results indicate that cold temperature injury delayed soybean reproductive stages and that the delays, at least in part, resulted from decreased leaf photosynthesis, reduced photosynthate availability, and altered biomass partitioning favoring vegetative over reproductive growth. The magnitude and sensitivity of soybean to short-term cold temperatures varied and was dependent on growth temperature and developmental stage.

Random Forests for Global and Regional Crop Yield Predictions

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

Methods of mesophyll conductance estimation: its impact on key biochemical parameters and photosynthetic limitations in phosphorus-stressed soybean across CO2.

Despite the development of various methods, the rapid estimation of mesophyll conductance (gm ) for a large number of samples is still a daunting challenge. Although the accurate estimation of gm is critical to partition photosynthetic limitations by stomatal (Ls ) and mesophyll (Lm ) conductance and by photo-biochemical (Lb ) processes, the impact of various gm estimation methods on this is ambiguous. As phosphorus (P) starvation and elevated CO2 (eCO2 ) strongly affect photosynthetic processes, their combined effect on the proportional changes in these limitations are not well understood. To investigate this, while also evaluating distinct recent methods of gm estimation sharing few common theories and assumptions, soybean was grown under a range of P nutrition at ambient and eCO2 . Methods significantly affected gm and carboxylation efficiency (VCmax ) but not other photosynthetic parameters. In all the methods, all photosynthetic parameters responded similarly to treatments. However, the percentage difference between VCmax assuming finite and infinite gm was highly inconsistent among methods. The primary mechanism responsible for P limitation to soybean photosynthesis was not CO2 diffusion limitations but Lb comprised of reduced chlorophyll, photochemistry and biochemical processes. The eCO2 decreased Lb but increased Lm without affecting Ls across leaf P concentration. Although each method explored advances of our understanding about gm variability, they all require assumptions of varying degrees, which lead to the discrepancy in the gm values. Among the methods, the oxygen sensitivity-based gm estimation appeared to be suitable for the quick assessment of a large number of samples or genotypes. Digital tools are provided for the easy estimation of gm for some methods.

Growth, nutrient dynamics, and efficiency responses to carbon dioxide and phosphorus nutrition in soybean

Plant mineral nutrients such as phosphorus may exert major control on crop responses to the rising atmospheric carbon dioxide (CO2) concentrations. To evaluate the growth, nutrient dynamics, and efficiency responses to CO2 and phosphorus nutrition, soybean (Glycine max (L.) Merr.) was grown in controlled environment growth chambers with sufficient (0.50 mM) and deficient (0.10 and 0.01 mM) phosphate (Pi) supply under ambient and elevated CO2 (aCO2, 400 and eCO2, 800 µmol mol−1, respectively). The CO2 × Pi interaction was detected for leaf area, leaf and stem dry weight, and total plant biomass. The severe decrease in plant biomass in Pi-deficient plants (10–76%) was associated with reduced leaf area and photosynthesis (Pnet). The degree of growth stimulation (0–55% total biomass) by eCO2 was dependent upon the severity of Pi deficiency and was closely associated with the increased phosphorus utilization efficiency. With the exception of leaf and root biomass, Pi deficiency decreased the biomass partitioning to other plant organs with the maximum decrease observed in seed weight (8–42%) across CO2 levels. The increased tissue nitrogen (N) concentration in Pi-deficient plants was accredited to the lower biomass and increased nutrient uptake due to the larger root to shoot ratio. The tissue P and N concentration tended to be lower at eCO2 versus aCO2 and did not appear to be the main cause of the lack of CO2 response of growth and Pnet under severe Pi deficiency. The leaf N/P ratio of >16 was detrimental to soybean growth. The tissue P concentration needed to attain the maximum productivity for biomass and seed yield tended to be higher at eCO2 versus aCO2. Therefore, the eCO2 is likely to increase the leaf critical P concentration for maximum biomass productivity and yield in soybean.

Growth responses of cotton to aldicarb and temperature

Abstract Aldicarb, 2-methyl-2-(methylthio)propionaldehyde O-(methylcarbamoyl)oxime, is a systemic insecticide used extensively for early season insect control in cotton ( Gossypium hirsutum L.). The indirect effect of aldicarb on cotton due to insect control is well documented; however, much less is known regarding its direct effect on cotton growth and development. The purpose of this research was to test the hypothesis that aldicarb in the absence of insects imposes a direct effect on cotton growth and that aldicarb effectiveness on growth depends on temperature. Cotton plants (cv. Deltapine-50 and DES-119) were grown in outdoor sunlit plant growth chambers under five day/night temperatures (20/12, 25/17, 30/22, 35/27, and 40/32 °C). In one study, aldicarb at 0.56 kg ha −1 was applied to soil at sowing. In a second study, aldicarb was first applied at a rate of 0.84 kg ha −1 to soil at sowing and applied again at a rate of 2.24 kg ha −1 at the stage of flower bud initiation as a side-dressing. Aldicarb increased early season vegetative growth of cotton plants grown at 25/17, 30/22, and 35/27 °C, but not for plants grown at 20/12 and 40/32 °C. Aldicarb also promoted the early formation of cotton flower buds at the five temperature regimes and increased the number of flowers at 30/22 °C. The treated plants had more growing roots, greater root length densities in the 61–80 cm soil depth, and higher root/shoot ratios than control plants at all temperatures. Our results showed that aldicarb promoted cotton earliness by enhancing growth rates and promoting the roots to grow deeper into soil. The responses of cotton to aldicarb depended on temperature, with a greater effect occurring at near optimum temperatures for cotton growth.