6.1 Overview of the thesis
Nitrogen (N) is one of the key determinants of crop growth and yield, with N deficiencies often resulting in retarded growth and reductions in harvestable yields and quality. Crop varieties produced by the ‘Green Revolution’ (Khush, 1999, Lassaletta et al., 2014) have helped alleviate hunger and poverty throughout the world. Yet, yields of such crops are heavily dependent on N inputs (Mueller et al., 2012), with their N uptake efficiency being relatively low (Glass, 2003). This encourages farmers to apply excessive amounts of N fertilizer to soil which in turn create environmental issues (e.g. eutrophication, soil acidification and greenhouse gas emissions) and economic losses. On the other hand, crop production needs to be increased [including rice yields by 60- 70% (Takai et al., 2013)] to feed the rising human population which is predicted to reach 9.7 billion by 2050 (UN, 2015); achieving higher yields would potentially increase N fertilizer use [240 MMt by the year 2050 (Tilman, 1999)] around the world. Thus, future crop production needs to be accomplished in a sustainable manner with minimum N inputs while introducing genotypes that are efficient in N use. Nitrogen productivity (NP) can be considered as a useful indicator of the efficiency of N use for biomass production during vegetative growth, which has the potential to lead to a better N use efficiency (NUE) at reproductive stage. NP is well characterized in the field of plant eco-physiology; by contrast, less is known about how NP varies among crop genotypes. Therefore, in my thesis, I adopted an eco-physiological based approach to evaluate genotypic variation in growth and NP of rice during early vegetative growth.
To explore how whole-plant growth of rice and its underlying components respond when exposed to a logarithmic series of available N, I first established what N concentrations are needed to create N-deficient phenotypes of a single genotype; this study is one of the few attempts to understand components underpinning rice growth based on a detailed dose-response
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experiment (Chapter 2). N-deficient phenotypes were observed over the 0.06- 0.12 mM N range, while relative growth rate (RGR) was optimum at moderate (0.5-2 mM) levels of N supply. Increased NP under severe N deficiency was not sufficient to compensate for a greater decline in leaf and plant N concentrations; consequently, net assimilation rate (NAR) and RGR both declined under low N supply. The results of Chapter 2 can also be used to provide inferences for variation in N supply under field conditions. For example, high N fertility in paddy soils is important to a farmer to ensure rice yields; however, overly high N availability during early growth can result in high N toxicity symptoms. Applying the optimum amount of N fertilizer during early stages of growth would be sufficient to boost leaf and tiller number, while avoiding deleterious effects of high N supply on plant growth and reduce runoff of excess N into rivers/lakes/oceans. Subsequent increases in N supply could then be applied as plant demand increases; ensuring yields are not N limited. Therefore, manipulation of the amount as well as timing when plants experience N fertilizer could be important both in terms of preventing toxicity during early growth or deficiency later.
In Chapter 3, I assessed genotypic variation of 10 genotypes of rice for their capacity to grow under low N conditions by performing a functional growth analysis during early vegetative growth. NP varied across genotypes to a greater extent (~70%) at low N compared with high N (23%). Based on the above approach, three rice genotypes (Takanari, IR 64 and Milyang 23) were identified for relatively high RGR at low N compared with high N associated with high NAR and NP. Thus, the key components driving faster growth in rice were the efficiency of carbon (C) and N use, rather than resource allocation among organs at the whole-plant level. Given that, next I investigated what physiological mechanisms could explain the observed maintenance of growth and NP at low N conditions. In Chapter 4, I assessed the extent to which leaf- level photosynthetic N use efficiency (PNUE) could explain improved whole- plant performance of rice genotypes at low N. There was tendency for higher PNUE in the three selected genotypes at low N (as indicated by enhanced net photosynthesis on N basis and Rubisco capacity per unit N, due to maintenance of photosynthetic capacity at low N along with partitioning more N to
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photosynthesis particularly Rubisco and electron transport components); however, no statistically significant differences in PNUE were found among the 10 genotypes and N levels, either as main or interactive effects. Yet, whole plant NP at low N strongly correlated with leaf PNUE i.e. both net photosynthesis and Rubisco capacity on N basis (Fig. 4.11). Thus, there is some evidence that differences in PNUE at the leaf level might explain the observed variations in whole-plant NP at low N. Given this, I suggested that further work is needed with more replicates and multiple genotypes including Takanari, IR 64 and Milyang 23 to confirm the contribution of leaf-level PNUE to whole-plant NP at low N. Further, measurements of shoot photosynthesis along with N analysis are necessary to calculate PNUE at shoot level and to investigate its contribution to whole-plant NP. In Chapter 5, I investigated the extent to which respiration could influence above performance at low N. The above mentioned three genotypes that exhibited high whole-plant NP under low N supply did not exhibit a consistent pattern for whole-plant respiration at low N; respiration was relatively homeostatic across different levels of N supply, which contrasts with the inhibitory effect of low N supply on rates of photosynthesis. Further, no correlation was found between leaf respiration in the dark (N basis) and whole plant NP at low N. In addition to the above findings, my thesis provided some important insights on respiratory fluxes of rice in relation to N supply at tissue, organ and whole-plant levels in the dark (RD) and also in the light (RL); this study helps address a knowledge gap in our understanding of variation in rates of respiration in rice compared to the abundance of studies on photosynthesis. The results highlight the importance of incorporating biomass allocation data with measurements of tissue-specific respiratory rates when modelling C fluxes at whole-plant level. Respiration in the shoot contributed 70% to daily whole plant respiration compared with the root, with this proportional contribution not changing in response to N supply. This was further confirmed by a near common slope observed for R-N scaling relationships of leaves and roots during the steady state of N supply, with the results being in agreement with Reich et al. (2008). The higher respiratory fluxes per unit N in roots, high susceptibility of root respiration to low N, and alteration of R-N scaling relationship of roots following N cessation, all reflected high energy costs associated with roots (e.g.
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N uptake and assimilation) compared with leaves. Thus, attention needs to be given to roots when modelling C fluxes of rice at low N conditions.
Leaf RD varied by two fold across genotypes within a given N level and low-N grown plants exhibited greater respiratory N use efficiency than their high-N grown counterparts. To my knowledge, this is the only study that has attempted to examine RL and light inhibition of leaf R in rice, particularly with respect to N supply. Light inhibited leaf R and leaf RL was reduced by low N. Yet, neither RL nor light inhibition of leaf R correlated with leaf N content. Genotypic differences were found for RL and light inhibition of leaf R. Variation in light inhibition of leaf R was largely accounted by leaf RL which was in turn dependent on the activity of Rubisco (either carboxylation or oxygenation) in the light. There was no impact of N supply on the fraction of daily fixed CO2 released by R at the whole-plant level during early growth, but increased at the whole-plant level during later growth as a consequence of reduced whole-plant A at low N. Respiration : photosynthesis ratios at leaf level were slightly lower in the light compared to dark, but both remained constant across N supply.
Thus, the overall objective together with all four specific objectives outlined earlier in my thesis was addressed in Chapters 2, 3, 4 and 5, respectively.
6.2 Agronomic considerations
Having established that there was genotypic variation for NP in rice at each N supply, and that Takanari, IR 64 and Milyang 23 performed well at low N relative to high N conditions, I now explore to what extent the results of present study (in a hydroponic system under glasshouse conditions) could be related to the performance (Table 6.1) in the field. Unlike in a glasshouse, the performance of genotypes under field conditions could differ depending on climatic (incident radiation, temperature and day length) (Evans, 1976), soil and other factors at each field location. For instance, Mae (2011) and Takai et al. (2006) reported field-based NUE of 38.3 and 44.6 respectively for the rice variety Nipponbare. While this sort of comparison is not definitive, my thesis research suggests the genotypes that were efficient in N use in the field are also the ones that
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maintained high RGR and NP during vegetative stage, as a majority of genotypes maintained their rankings (except IR 64, Akihikari and Azucena) for RGR and NP during vegetative growth in relation to the NUE in the field. There was 47% variation among and the highest (Takanari) and the lowest (Nipponbare) for NUE (excluding IR 64, Akihikari and Azucena). Sink capacity (i.e. the product of 1000 grain mass in g and total number of spikelets per unit land area of m2) per unit plant N was 1.6 times greater in Takanari than in Nipponbare; thus, Takanari could achieve a higher yield per unit plant N than Nipponbare (Mae, 2011). Further, Takanari, Milyang 23 and Nipponbare exhibited a crop growth rate of 26.0, 23.2 and 19.9 g m-2 d-1, respectively, during tillering to primordia initiation stage (Takai et al., 2006); this is consistent with rankings obtained for RGR of the present study. Genotype rankings for RGR and NP from my glasshouse study were similar to that of field data results (from literature) for CGR and NUE, suggesting the findings of my study may have wider relevance for field-grown rice.
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Genotypes were arranged following the order for RGR of present study from highest to the lowest. References were given only for grain yield, applied N fertilizer and NUE. NUE (kg of grain yield/ kg of applied N fertilizer) was calculated by dividing the amount of grain yield (kg/ha) by the amount of applied N fertilizer (kg/ha). Genotypic variation for NP was calculated as [(maximum NP– minimum NP)/ minimum NP]*100. Genotypic variation for NUE was calculated as [(maximum NUE– minimum NUE)/ minimum NUE]*100.
Table 6.1 Background of the genotypes used in the present study
Genotype Type Parents Country of origin Year of release Duration Vegetative growth or days to full heading 1000 grain mass (g) Grain yield (t/ ha) Applied N fertilizer (kg/ ha) NUE i.e. grain yield (kg)/ Fertilizer N (kg) References Takanari indica x japonica
Cross-bred from Milyang 25 and Milyang 42 where both carrying the semi- dwarf gene sd-1
Japan 1990 116 78 23.5 9.83 150 65.53 Takai et al. (2006)
IR 64 indica IR5657-33-2-1 and IR2061-465-1-5-5
Philippines 1985 118 57 25.6 3.8 75 50.67 Haefele et al. (2008) Milyang 23 indica x
japonica
Milyang 23 was bred using semi-dwarf variety IR 24
Korean Republic
1976 116 77 25.6 9.09 150 60.60 Takai et al. (2006)
Opus japonica Australia 143 22.5 8.90 150 59.33 Troldahl (2014)
Dular Indica landrace
- India - 105 45 3.28 60 54.67 Pande and Singh (1970)
Bg 34-8 indica Sri Lanka 119 8.20 150 54.66 Singh et al. (1998)
Koshihikari japonica Cross-bred from Norin 22 and Norin 1
Japan 1956 143 21.9 7.30 150 48.66 Troldahl (2014) Akihikari japonica Cross-bred from
Toyonishiki and Remei
Japan 1976 21.6 10.11 130 77.76 Mae (2011)
Azucena Japonica landrace
- Philippines - 90 2.29 90 25.44 Atlin et al. (2006)