Experimental and modeling evidence of carbon limitation of leaf appearance rate for spring and winter wheat

Baumont, Maeva; Parent, Boris; Manceau, Loïc; Brown, Hamish E.; Driever, Steven M.; Muller, Bertrand; Martre, Pierre

doi:10.1093/jxb/erz012

Cited by 23 publications

(22 citation statements)

References 79 publications

(117 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The phyllochron describing leaf appearance rate responds nonlinearly to multienvironmental factors. When it is modeled using only temperature, residual environmental effects are often observed (Cao and Moss, 1989;Baumont et al, 2019). This can be partly removed using the photothermal time corresponding to temperatures accumulated during the light time period only (Masle et al, 1989).…”

Section: Assimilation Of Gf Observations Provides Accurate Estimates mentioning

confidence: 99%

Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform

Liu

Martre

Buis³

et al. 2019

Plant Physiol.

Self Cite

View full text Add to dashboard Cite

The extraction of desirable heritable traits for crop improvement from high-throughput phenotyping (HTP) observations remains challenging. We developed a modeling workflow named "Digital Plant Phenotyping Platform" (D3P), to access crop architectural traits from HTP observations. D3P couples the Architectural model of DEvelopment based on L-systems (ADEL) wheat (Triticum aestivum) model (ADEL-Wheat), which describes the time course of the three-dimensional architecture of wheat crops, with simulators of images acquired with HTP sensors. We demonstrated that a sequential assimilation of the green fraction derived from Red-Green-Blue images of the crop into D3P provides accurate estimates of five key parameters (phyllochron, lamina length of the first leaf, rate of elongation of leaf lamina, number of green leaves at the start of leaf senescence, and minimum number of green leaves) of the ADEL-Wheat model that drive the time course of green area index and the number of axes with more than three leaves at the end of the tillering period. However, leaf and tiller orientation and inclination characteristics were poorly estimated. D3P was also used to optimize the observational configuration. The results, obtained from in silico experiments conducted on wheat crops at several vegetative stages, showed that the accessible traits could be estimated accurately with observations made at 0°and 60°zenith view inclination with a temporal frequency of 100°Cd (degree day). This illustrates the potential of the proposed holistic approach that integrates all the available information into a consistent system for interpretation. The potential benefits and limitations of the approach are further discussed.

show abstract

Section: Assimilation Of Gf Observations Provides Accurate Estimates mentioning

confidence: 99%

Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform

Liu

Martre

Buis³

et al. 2019

Plant Physiol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, Legris et al (2016) have shown that phytochrome B is not only related to photoperiod but also to temperature sensitivity. Baumont et al (2019) relate leaf appearance rate with carbohydrate availability and claim that the photoperiod effect of leaf appearance rate could be a surrogate for carbohydrate availability. And one could think that as our knowledge of the gene network controlling phenology improves, models will improve as well; but will models accelerate the uncovering of these networks?…”

Section: Phenologymentioning

confidence: 99%

“…Defining the canopy greenness throughout the growth cycle is critical to compute transpiring (green area) and non-transpiring fractions of the canopy. Leaf development is largely a function of temperature and carbohydrates availability (Baumont et al, 2019), but leaf expansion is also controlled by water and nutrient stress.…”

Section: Canopy Developmentmentioning

confidence: 99%

Can Crop Models Identify Critical Gaps in Genetics, Environment, and Management Interactions?

Stöckle

Kemanian

2020

Front. Plant Sci.

View full text Add to dashboard Cite

Increasing food demand under climate change constraints may challenge and strain agricultural systems. The use of crop models to assess genotypes performance across diverse target environments and management practices, i.e., the genetic × environment × management interaction (GEMI), can help understand suitability of genotype and agronomic practices, and possibly accelerate turnaround in plant breeding programs. However, the readiness of models to support these tasks can be debated. In this article, we point out modeling and data limitations and argue the need for evaluation and improvement of relevant process algorithms as well as model convergence. Under conditions suitable for plant growth, without meteorological extremes or soil limitation to root exploration, models can simulate resource capture, growth, and yield with relative ease. As stresses accumulate, the plant species-and genotype-specific attributes and their interactions with the soil and atmospheric environment generate a large range of responses, including conditions where resources become so limiting as to make yields very low. The space in between high and low yields is where most rainfed production occurs, and where the current model and user skill at representing GEMI varies. We also review studies comparing the performance of a large number of crop models and the lessons learned. The overall message is that improvement of models appears as a necessary condition for progress, and perhaps relevancy. Model ensembles help mitigate data input, model, and user-driven uncertainty for some but not all applications, sometimes at a very high cost. Successful model-based assessment of GEMI not only requires better crop models and knowledgeable users, but also a realistic representation of the environmental conditions of the landscape where crops are grown, which is not trivial given the 3D nature of water and nutrient transport. Models remain the best quantitative repository of our knowledge on crop functioning; they contain a narrative of plant, soil, and atmospheric functioning in computer language and train the mind to couple processes. But in our quest to tame GEMI, will they lead the way or just ride along history?

show abstract

“…In rice, Islam and Morison (1992) introduced the photothermal quotient (PQ) -as the ratio between cumulated radiation and cumulated thermal time (MJ.m -2 .°C -1 ) -during the 30 days-day period before harvest in order to predict yield. Recently, Baumont et al (2019) indicated in wheat the joint role of temperature and carbon availability on plant development rate and concluded that the use of photothermal quotient (PQ) is relevant to better model cycle durations in different light and temperature environments. In order to compare phyllochron between environments, it is suggested here that thermal time is appropriate when environments differ mainly by their temperature conditions, while PQ is when facing contrasted environments, differing by incident radiation, temperature and VPD, as it was the case in our study.…”

Section: Phenotyping For Tolerance To Mild Water Deficit At Reproductmentioning

confidence: 99%

Genotypic response to water deficit applied at reproductive stage in rice: is the response unique across two contrasted climates?

Lima

Lafarge

Castro

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Rice crop is known as very sensitive to water deficit, especially during the reproductive phase when growth of vegetative organs and formation of spikelets are concomitant. The present study questioned whether the maintenance of vegetative organ expansion during a water deficit at the reproductive phase affects the reproductive structure organogenesis, and if relevant traits for adaptation can be identified. To answer these queries, the response to a same reproductive water deficit of six contrasted japonica genotypes has been analyzed under two contrasted climates differing in incident radiation, air hygrometry and temperature (greenhouse in Brazil, Sitis, and growth chamber in France, GC).Results: Under irrigation, plant growth rate was reduced in GC while crop duration was extended: the trade-offs resulted in similar plant height and biomass. From a method able to determine a posteriori the date of panicle initiation (PI), elementary processes were positioned in time, allowing to evaluate how much each process was affected, despite the diversity in phenology across genotypes. Elongation rate decreased with water deficit and was highly associated with an increase in soluble sugars in stem and flag leaf in both experiments, while starch was reduced in Sitis and negligible in GC. This unique response, however, induced a different effect across experiments on branch and spikelet formation. In short, in both experiments, maintenance of spikelet number was highly associated with maintenance of flag leaf and internode width. All variables, including branch and spikelet number, were highly affected with IAC 25 in both experiments, while variations were non-significant with Cirad 409. In addition, some other genotypes expressed a differential response between Sitis and GC, conveying a specific sensitivity to low radiation or to high air temperature. Conclusions: This study highlighted the importance of finely mapping in time elementary growth processes, thanks to PI date determination, in order to detect key traits of adaptation to abiotic stress through phenotyping across genotypes of diverse phenology. The maintenance of flag leaf width or internode diameter under a mild water deficit was highlighted here as a trait associated with the maintenance of yield components.

show abstract

Experimental and modeling evidence of carbon limitation of leaf appearance rate for spring and winter wheat

Abstract: Carbon availability can account for environmental effects on leaf appearance rate (LAR) and a new ecophysiological model is developed that gives good predictions for LAR in contrasting field environments.

Cited by 23 publications

References 79 publications

Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform

Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform

Can Crop Models Identify Critical Gaps in Genetics, Environment, and Management Interactions?

Genotypic response to water deficit applied at reproductive stage in rice: is the response unique across two contrasted climates?

Contact Info

Product

Resources

About