Carbon Isotope Discrimination is not Correlated with Transpiration Efficiency in Three Cool‐Season Grain Legumes (Pulses)

Abstract

The carbon isotope discrimination (δ13C) of leaves has been shown to be correlated with the transpiration efficiency of leaves in a wide range of species. This has led to δ13C being used in breeding programs to select for improved transpiration efficiency. The correlation between δ13C and transpiration efficiency was determined under well‐watered conditions during the vegetative phase in six genotypes of lentil (Lens culinaris Medikus), six genotypes of chickpea (Cicer arietinum L.) and 10 cultivars of narrow‐leafed lupin (Lupinus angustifolius L.). Biomass (dry matter) accumulation and water use (transpiration) varied among the genotypes in all three species and transpiration efficiency was 40% to 75% higher in the most efficient compared with the least efficient genotypes. However, δ13C and transpiration efficiency were not significantly correlated in any of the species. This suggests that the δ13C technique cannot be used in selection for transpiration efficiency in the three grain legumes (pulses) studied.

Transpiration efficiency versus growth: Exploring the banana biodiversity for drought tolerance

“…The 13 C levels are only determined by the possibility of CO 2 exchange with the atmosphere and thus opening and closing of stomata while TE takes into account the real dry matter accumulation and thereby growth. Another possible explanation for the lack of correlation between TE and ␦ 13 C as suggested by Turner et al (2007b). It can be explained by the difference in dry matter allocation between leaves and corm.…”

“…It can be explained by the difference in dry matter allocation between leaves and corm. Since TE was determined by the dry matter accumulated in the aboveground parts of the plant and ␦ 13 C was only measured at leaf level, differences in dry matter allocation could influence the correlation between both variables (Turner et al, 2007b). Furthermore, dry matter allocation is known to be a strategy for coping with drought and can differ among cultivars.…”

Genetic Analysis of Carbon Isotope Discrimination and its Relation to Yield in a Wheat Doubled Haploid Population

“…The positive correlation between Δ 13 C and grain yield in both the DS and WW environments in the present work might be associated with the moderate drought stress (rain‐fed condition) applied. Additionally, in relatively few cases, Δ 13 C is reported to be not correlated with grain yield, e.g., Δ 13 C is shown to be not correlated with transpiration efficiency and grain yield in the three grain legumes studied (Turner et al 2007). Therefore, the application of carbon isotope discrimination measurement for high yield potential is valid only under specific conditions.…”

Variation in carbon isotope discrimination and its relationship with harvest index in the reference collection of chickpea germplasm

“…In several legumes such as bean (White, 1993;Wright and Redden, 1995), cowpea (Ismail and Hall, 1992;Ismail et al, 1994), groundnut (Hubick et al, 1986;Wright et at., 1994), lentil (Matus et al, 1995), soybean (White et al, 1995;Uday Kumar et al, 1996;Tobita et al, 2007), and in chickpea (Kashiwagi et al 2006b) Δ 13 C was found to be correlated with TE. But the lack of such relationship between Δ 13 C and TE was also shown, in groundnut transgenic events (Devi et al, 2011) or in three legume species grown well-watered (Turner et al 2007), or a weak relationship was found in recombinant inbred lines of groundnut (Krishnamurthy et al, 2007), indicating that there are specific weather and soil moisture conditions where the contribution of Δ 13 C becomes apparent. There were also indications from these works that there can be direct as well indirect effects of the isotope discrimination on yield performance and special attention is required to understand such effects (Mohankumar et al 2011;Khazaie et al 2011) A reference collection of chickpea germplasm based on molecular diversity data of global composite collection (3000 accessions at 50 microsatellite loci) (Upadhyaya et al 2006) has been developed at ICRISAT ).…”