scholarly journals Sensitivity of leaflet growth rate to drought predicts yield in common bean (Phaseolus vulgaris)

2020 ◽  
Vol 47 (9) ◽  
pp. 792
Author(s):  
Amber N. Hageman ◽  
Milan O. Urban ◽  
Elizabeth Van Volkenburgh
Keyword(s):  
Growth Rate ◽  
Phaseolus Vulgaris ◽  
Growth Rates ◽  
Resource Partitioning ◽  
Biomass Accumulation ◽  
Growth Strategy ◽  
Yield Reduction ◽  
Sink Strength ◽  
Common Beans ◽  
Pod Growth

Although drought limits yield by decreasing photosynthesis and therefore biomass accumulation, biomass is not the strongest predictor of yield under drought in common beans (Phaseolus vulgaris L.). Instead, resource partitioning from pod walls into seeds is a stronger correlate. Our aim was to determine whether growth rates of developing leaflets and pods, as independent indicators of sink strength, predict resource partitioning into seeds. Using 20 field-grown genotypes, we paired biomass, yield, and resource partitioning data with leaflet and pod growth rates under well-watered and droughted conditions. We hypothesised that genotypes with faster growing leaflets and pods under drought would fill seeds better. However, we found that leaflet and pod growth rates did not predict partitioning to seeds; rather, sensitivity of leaflet growth rate to drought was a good predictor of yield reduction. Further, plants with rapidly growing leaves under well-watered conditions were most vulnerable to decreases in leaflet growth rate under drought. This suggests that lines that inherited a conservative growth strategy were better able to maintain yield by allocating resources to seeds. Our findings indicate that inherent sensitivity of leaflet growth rate to drought may be used as a predictor of partitioning and yield in common beans.

scholarly journals Drought sensitivity of leaflet growth, biomass accumulation, and resource partitioning predicts yield in common bean

2019 ◽  
Author(s):  
Amber Hageman ◽  
Milan O. Urban ◽  
Elizabeth Van Volkenburgh
Keyword(s):  
Phaseolus Vulgaris ◽  
Common Bean ◽  
Biomass Production ◽  
Seed Yield ◽  
Growth Rates ◽  
Resource Partitioning ◽  
Harvest Index ◽  
Biomass Accumulation ◽  
Pod Growth ◽  
Pod Harvest Index

ABSTRACTWhile drought limits yield largely by its impact on photosynthesis and therefore biomass accumulation, biomass is not the strongest predictor of yield under drought. Instead, resource partitioning efficiency, measured by how much total pod weight is contained in seeds at maturity (Pod Harvest Index), is the stronger correlate in Phaseolus vulgaris. Using 20 field-grown genotypes, we expanded on this finding by pairing yield and resource partitioning data with growth rates of leaflets and pods. We hypothesized that genotypes which decreased partitioning and yield most under drought would also have strongest decreases in growth rates. We found that while neither leaflet nor pod growth rates correlated with seed yield or partitioning, impacts to leaflet growth rates under drought correlate with impacts to yield and partitioning. As expected, biomass production correlated with yield, yet correlations between the decreases to these two traits under drought were even stronger. This suggests that while biomass contributes to yield, biomass sensitivity to drought is a stronger predictor. Lastly, under drought, genotypes may achieve similar canopy biomass yet different yields, which can be explained by higher or lower partitioning efficiencies. Our findings suggest that inherent sensitivity to drought may be used as a predictor of yield.HIGHLIGHTIn common bean, higher biomass accumulation under drought alone does not guarantee higher yield, as maintenance of higher growth rates and partitioning processes act as an additional requirement.

The responses of photosynthesis and translocation rates to changes in the ζ ratio of light

1982 ◽  
Vol 60 (8) ◽  
pp. 1285-1291 ◽  
Author(s):  
John Hoddinott ◽  
Linda M. Hall
Keyword(s):  
Growth Rate ◽  
Steady State ◽  
Growth Rates ◽  
Light Quality ◽  
Wide Spectrum ◽  
Red Light ◽  
Sink Strength ◽  
Quality Change ◽  
Sun And Shade ◽  
Changing Light

The influence of wide spectrum illumination conditions, with red and far-red light mixed to simulate sun and shade conditions, upon rates of photosynthesis and translocation was observed. A steady-state 14CO2 labeling apparatus was used to measure the two processes simultaneously during a light quality change. Sun conditions supported lower rates of photosynthesis and translocation to illuminated sink leaves than shade conditions, but the rate of translocation was lower than expected on the basis of the decline in photosynthesis. Translocation rates to darkened sinks remained constant as the photosynthetic rates were altered by changing light quality. Sink leaflet growth rates were lower in sun than shade light. We conclude that this decline in growth rate, which is also a decline in sink strength, results in light quality exerting a smaller effect on translocation than on photosynthesis.

scholarly journals Variation in and Relationship of Biomass, Growth Rate, Harvest Index, and Phenology to Yield of Common Bean

1990 ◽  
Vol 115 (2) ◽  
pp. 218-225 ◽  
Author(s):  
B.T. Scully ◽  
D.H. Wallace
Keyword(s):  
New York ◽  
Growth Rate ◽  
Common Bean ◽  
Growth Rates ◽  
Harvest Index ◽  
Quadratic Function ◽  
Curvilinear Relationship ◽  
Sink Strength ◽  
Biomass Growth ◽  
Days To Maturity

A diverse set of 112 common bean (Paseolus vulgaris L.) accessions were evaluated for variation in eight traits related to yield over a 2-year period. Days to flower, days of pod fill, and days to maturity ranged from 25 to 66, 44 to 83, and 70 to 133, respectively, in upstate New York: Yield and biomass ranged from 81 to 387 and 270 to 1087 g•m-2, respectively. Harvest index ranged from 12% to 65%. The biomass (biomass/days to maturity) and seed (yield/days of pod fill) growth rates ranged from 3.2 to 9.3 and 1.2 to 9.5 g•m-2 -day-1, respectively. The economic growth rate (yield/days to maturity) extended from 0.6 to 5.7 g•m-2 -day-1. The growth rates, biomass, and days of pod fill were linearly and positively related to yield. Biomass and the growth rates explained a large amount of the variation in yield, with r2 values between 0.71 and 0.84; days of pod fill explained the least, with r2 = 0.09. Yield followed a curvilinear relationship with days to flower and days to maturity; yield was maximized at 48.5 days to flower and 112.2 days to maturity. Yield was a quadratic function of harvest index and maximized at 57.2%. Among these three curvilinear traits, days to flower explained 80% of the variation in yield, while days to maturity and harvest index accounted for 25% and 12.5%, respectively. The “ideal” genotype for New York was defined at these maximum values for harvest index, days to maturity, days to flower, and at 63.7 days of pod fill. Additionally, a simple equation is proposed to aid breeders in the selection of common bean accessions with strong sink strength. It is defined as “relative sink strength”: RSS = seed growth rate/biomass growth rate. Values > 1.0 implied strong sink capacity in common beans.

scholarly journals Evaluación de pentacloronitrobenceno (PCNB) en el control de la pudrición radicular cusada por Rhizoctonia solani Kuhn en frijol común (Phaseolus vulgaris L.)

2016 ◽  
Vol 1 ◽  
pp. 55
Author(s):  
Sergio Pichardo Guido
Keyword(s):  
Phaseolus Vulgaris ◽  
Grain Yield ◽  
Rhizoctonia Solani ◽  
Common Bean ◽  
Yield Reduction ◽  
Common Beans ◽  
Phaseolus Vulgaris L ◽  
Bean Variety

This experiment was conducted at “La Compañía”, Estación Experimental del Instituto Superior de Ciencias Agropecuarias (ISCA), which is located in the department of Carazo, Nicaragua. The trial was conducted during the months of June through September, 1987 with the following objectives: 1) To determine the appropiate rate of pentachloronitrobenzene (PCNB) for control of Rhizoctonia solani in common beans, 2) To evaluate the effect of mixing PCNB and “ Metalaxyl” on grain yield of common beans, 3) To determine yield reduction percentages caused by R. solani in common beans and 4) To select the best common bean variety in this experiment relative to the defined treatments. The results demonstrated that PCNB applied at a rate of 6.81 kg/ha was 3 % higher than the check and 12% higher than the highest rate of PCNB (11.36 kg/ha). The variety “Revolución 84” provided the highest yields compared to other entries.

Comparison of copper sulphate pentahydrate growth rates determined by different methods

1990 ◽  
Vol 55 (7) ◽  
pp. 1691-1707 ◽  
Author(s):  
Miloslav Karel ◽  
Jiří Hostomský ◽  
Jaroslav Nývlt ◽  
Axel König
Keyword(s):  
Growth Rate ◽  
Crystal Growth ◽  
Fluidized Bed ◽  
Growth Rates ◽  
Copper Sulphate ◽  
Crystal Growth Rate ◽  
Effect Of Temperature ◽  
Rotating Disc ◽  
Shape Factors ◽  
Data Treatment

Crystal growth rates of copper sulphate pentahydrate (CuSO4.5 H2O) determined by different authors and methods are compared. The methods included in this comparison are: (i) Measurement on a fixed crystal suspended in a streaming solution, (ii) measurement on a rotating disc, (iii) measurement in a fluidized bed, (iv) measurement in an agitated suspension. The comparison involves critical estimation of the supersaturation used in measurements, of shape factors used for data treatment and a correction for the effect of temperature. Conclusions are drawn for the choice of values to be specified when data of crystal growth rate measurements are published.

Measurement of growth rates for single crystals and pressed tablets of CuSO4.5 H2O on a rotating disc

1989 ◽  
Vol 54 (11) ◽  
pp. 2951-2961 ◽  
Author(s):  
Miloslav Karel ◽  
Jaroslav Nývlt
Keyword(s):  
Growth Rate ◽  
Single Crystal ◽  
Single Crystals ◽  
Growth Rates ◽  
Diffusion Coefficients ◽  
Preferred Orientation ◽  
Rotating Disc ◽  
Dissolution Rates ◽  
Rates Of Growth ◽  
Good Agreement

Measured growth and dissolution rates of single crystals and tablets were used to calculate the overall linear rates of growth and dissolution of CuSO4.5 H2O crystals. The growth rate for the tablet is by 20% higher than that calculated for the single crystal. It has been concluded that this difference is due to a preferred orientation of crystal faces on the tablet surface. Calculated diffusion coefficients and thicknesses of the diffusion and hydrodynamic layers in the vicinity of the growing or dissolving crystal are in good agreement with published values.

scholarly journals Accuracy of State-Level Surveillance during Emerging Outbreaks of Respiratory Viruses: A Model-Based Assessment

2021 ◽  
pp. 0272989X2110222
Author(s):  
Yuwen Gu ◽  
Elise DeDoncker ◽  
Richard VanEnk ◽  
Rajib Paul ◽  
Susan Peters ◽  
...  
Keyword(s):  
Growth Rate ◽  
Data Collection ◽  
Disease Progression ◽  
Health Care Providers ◽  
Growth Rates ◽  
State Level ◽  
Future Research ◽  
Care Providers ◽  
State Surveillance ◽  
First Come First Serve

It is long perceived that the more data collection, the more knowledge emerges about the real disease progression. During emergencies like the H1N1 and the severe acute respiratory syndrome coronavirus 2 pandemics, public health surveillance requested increased testing to address the exacerbated demand. However, it is currently unknown how accurately surveillance portrays disease progression through incidence and confirmed case trends. State surveillance, unlike commercial testing, can process specimens based on the upcoming demand (e.g., with testing restrictions). Hence, proper assessment of accuracy may lead to improvements for a robust infrastructure. Using the H1N1 pandemic experience, we developed a simulation that models the true unobserved influenza incidence trend in the State of Michigan, as well as trends observed at different data collection points of the surveillance system. We calculated the growth rate, or speed at which each trend increases during the pandemic growth phase, and we performed statistical experiments to assess the biases (or differences) between growth rates of unobserved and observed trends. We highlight the following results: 1) emergency-driven high-risk perception increases reporting, which leads to reduction of biases in the growth rates; 2) the best predicted growth rates are those estimated from the trend of specimens submitted to the surveillance point that receives reports from a variety of health care providers; and 3) under several criteria to queue specimens for viral subtyping with limited capacity, the best-performing criterion was to queue first-come, first-serve restricted to specimens with higher hospitalization risk. Under this criterion, the lab released capacity to subtype specimens for each day in the trend, which reduced the growth rate bias the most compared to other queuing criteria. Future research should investigate additional restrictions to the queue.

scholarly journals StalGrowth—A Program to Estimate Speleothem Growth Rates and Seasonal Growth Variations

Geosciences ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 187
Author(s):  
Rolf Vieten ◽  
Francisco Hernandez
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Environmental Parameters ◽  
Ion Concentration ◽  
Radiometric Dating ◽  
Seasonal Growth ◽  
Climate Signal ◽  
Show Evidence ◽  
Cave Monitoring ◽  
Calcium Ion Concentration

Speleothems are one of the few archives which allow us to reconstruct the terrestrial paleoclimate and help us to understand the important climate dynamics in inhabited regions of our planet. Their time of growth can be precisely dated by radiometric techniques, but unfortunately seasonal radiometric dating resolution is so far not feasible. Numerous cave environmental monitoring studies show evidence for significant seasonal variations in parameters influencing carbonate deposition (calcium-ion concentration, cave air pCO2, drip rate and temperature). Variations in speleothem deposition rates need to be known in order to correctly decipher the climate signal stored in the speleothem archive. StalGrowth is the first software to quantify growth rates based on cave monitoring results, detect growth seasonality and estimate the seasonal growth bias. It quickly plots the predicted speleothem growth rate together with the influencing cave environmental parameters to identify which parameter(s) cause changes in speleothem growth rate, and it can also identify periods of no growth. This new program has been applied to multiannual cave monitoring studies in Austria, Gibraltar, Puerto Rico and Texas, and it has identified two cases of seasonal varying speleothem growth.

scholarly journals Effect of Light Intensity and Quality on Growth Rate and Composition of Chlorella vulgaris

Plants ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 31 ◽  
Author(s):  
Maria N. Metsoviti ◽  
George Papapolymerou ◽  
Ioannis T. Karapanagiotidis ◽  
Nikolaos Katsoulas
Keyword(s):  
Growth Rate ◽  
Light Intensity ◽  
Chlorella Vulgaris ◽  
Lipid Content ◽  
Growth Rates ◽  
Solar Irradiance ◽  
White Led ◽  
Microalgal Biomass ◽  
Nm Range ◽  
Effect Of Light

In this research, the effect of solar irradiance on Chlorella vulgaris cultivated in open bioreactors under greenhouse conditions was investigated, as well as of ratio of light intensity in the 420–520 nm range to light in the 580–680 nm range (I420–520/I580–680) and of artificial irradiation provided by red and white LED lamps in a closed flat plate laboratory bioreactor on the growth rate and composition. The increase in solar irradiance led to faster growth rates (μexp) of C. vulgaris under both environmental conditions studied in the greenhouse (in June up to 0.33 d−1 and in September up to 0.29 d−1) and higher lipid content in microalgal biomass (in June up to 25.6% and in September up to 24.7%). In the experiments conducted in the closed bioreactor, as the ratio I420–520/I580–680 increased, the specific growth rate and the biomass, protein and lipid productivities increased as well. Additionally, the increase in light intensity with red and white LED lamps resulted in faster growth rates (the μexp increased up to 0.36 d−1) and higher lipid content (up to 22.2%), while the protein, fiber, ash and moisture content remained relatively constant. Overall, the trend in biomass, lipid, and protein productivities as a function of light intensity was similar in the two systems (greenhouse and bioreactor).

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