4.7 Review

Physiological drivers of responses of grains per m2 to environmental and genetic factors in wheat

Journal

FIELD CROPS RESEARCH
Volume 285, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.fcr.2022.108593

Keywords

Number of grains; Number of spikes; Fruiting efficiency; Spike dry weight; Yield components; Triticum aestivum

Categories

Funding

  1. International Wheat Yield Partnership [IWYP25FP]
  2. Spanish State Agency for Research [RTI2018-096213-B-100]
  3. Argentine Fund for Scientific and Technological Research [PICT RAICES 2019-04333]

Ask authors/readers for more resources

Research suggests that to increase wheat yield, it is crucial to increase the number of grains per unit area. This study analyzed the main determinants of grain number per unit area in response to genetic and environmental factors, revealing trade-offs between numerical and physiological components.
Most of the required increases in food production over the next decades are expected to be achieved through increases in crop yield. As wheat is essential for food security it is worrying that its yield gains over the last two decades were small. To achieve further yield increases it is critical to continue increasing number of grains per unit area (GN m(-2)), the trait best related to yield. In this context, it is relevant to identify the main determinants of GN m(-2) in response to genetic and environmental factors as well as the trade-offs between them. In the present study we compiled a large database across the literature to analyse the relative importance of components when affected by genetic or environmental factors, producing small or large changes in GN m(-2) and its components, either numerical (the number of spikes per m(2), SN m(-2); and the number of grains per spike, GN spike(-1)) or physiological (spike dry weight at anthesis, SDWa; and fruiting efficiency, FE) determinants. The database included 367 papers published in: (i) Field Crop Research (FCR), (ii) European Journal of Agronomy (EJA), (iii) Crop Science (CS) and (iv) Crop and Pasture Science (CPS, formerly Australian Journal of Agricultural Research) between 1990 and 2020. The complete dataset was split into classes, depending on the source of experimental variation, environment or genotype and was normalised to remove the differences between experiments and determine the environmental and genotypic effects within each experiment. Normalised data showed that the responsiveness of GN m(-2)was similarly explained by changes in both SN m(-2) and GN spike(-1), but in terms of physiological components SDWa was more relevant than FE for explaining the variations in GN m(-2). Considering the numerical components of GN m(-2) genotypic and environmental factors modified more GN spike(-1) than in SN m(-2). On the other hand, physiological components were differently modified by genotype and environment: for genotypic effects FE was more critical than SDWa and the other way around for environmental factors. A tradeoff between numerical and physiological components was observed although was greater between physiological than between numerical components.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available