- Email: [email protected]
Crop productivity as related to single-plant traits at key phenological stages in durum wheat
Field Crops Research 138 (2012) 42–51
Contents lists available at SciVerse ScienceDirect
Field Crops Research journal homepage: www.elsevier.com/locate/fcr
Crop productivity as related to single-plant traits at key phenological stages in durum wheat Anna Pedró a , Roxana Savin a , Gustavo A. Slafer a,b,∗ a b
Department of Crop and Forest Sciences and AGROTECNIO (Centre for Research in Agrotechnology), University of Lleida, Av. Rovira Roure 191, 25198 Lleida, Spain ICREA (Catalonian Institution for Research and Advanced Studies), Barcelona, Spain
a r t i c l e
i n f o
Article history: Received 2 April 2012 Received in revised form 16 August 2012 Accepted 19 September 2012 Keywords: Grain yield Grain yield components Morpho-physiological traits Selection criteria Isolated plants, Triticum durum
a b s t r a c t Selection based on single plants is a necessary step during early generations in breeding programs, where populations are still heterogeneous. A major problem is that individual plant performance is rather independent of crop performance, and there are few studies indicating physiological traits in individual plants that are reliable to select for to increase crop yield. In this context we aimed to find out whether it is possible to identify morpho-physiological traits in single spaced plants that might be trustworthily used for selecting in early generations for improving crop performance in durum wheat. We have grown during two seasons both isolated plants and dense populations of the same durum wheat genotypes. Isolated plants were sown at <20 plants m−2 while crop populations were grown at 200 plants m−2 during the first experiment and 400 plants m−2 during the second one. Several traits (57 and 114 in the first and second experiments, respectively) were measured or estimated at different steps during the crop cycle in both conditions. Both, crop and individual plant yields were better explained by the number of grains than by the average weight of the grains. As expected, there was no relationship between crop yield and yield of the individual plants. Yield components and other traits measured in individual plants at maturity did not relate well with crop yield. However, specific leaf weight and spike partitioning of isolated plants determined at anthesis exhibited clear trends to be positively related to crop yield. Both traits are dense independent and may be potentially useful selection criteria, if surrogates to determine them more easily or molecular markers become available. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Breeding of grain crops has been very successful during the second half of the 20th century, essentially based on an empirical approach of selecting for yield per se (Slafer and Andrade, 1991). But we now face a worrisome slowdown in the rate of genetic gains (Reynolds et al., 2009a; Fischer and Edmeades, 2010). It has been speculated several times that achieving a better understanding of yield physiology would be instrumental to regain healthier rates of genetic gains in yield (Calderini and Slafer, 1999; Slafer, 2003; Fischer, 2007, 2011; Araus et al., 2008; Reynolds et al., 2009a,b, 2012; Foulkes et al., 2011). However, most of the knowledge we have gained on yield physiology in the last decades derives from studies analysing crop yield together with other crop physiological attributes. Focusing on attributes of the crop canopy would be useful in selection of late generations in which breeders select on
∗ Corresponding author at: Department of Crop and Forest Sciences and AGROTECNIO (Centre for Research in Agrotechnology), University of Lleida, Av. Rovira Roure 191, 25198 Lleida, Spain. Tel.: +34 973 003659. E-mail address: [email protected] (G.A. Slafer). 0378-4290/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fcr.2012.09.016
actual near-homogeneous populations in a crop dense stand. However, the problem remains that the strongest selection pressure is applied in early generations when selection is based on single plant performance and individual plant productivity may be rather independent of that of the crop, as lucidly evidenced by Donald some half-century ago when introducing the concept of ideotype (Donald, 1968; Donald and Hamblin, 1976). Even though there have been many attempts to offer ideotypes in the literature, it is noticeably small the body of evidences in which morpho-physiological traits of isolated individuals of a particular genotype are actually compared with the performance of the crop of that genotype in dense stands. This sort of comparison might provide breeders with selection criteria to be used on isolated plants in early generations to increase the likelihood of producing high-yielding cultivars few generations later. If such attributes in isolated plants were known, their use as selection criteria in early generations can improve the likelihood of success. Examples of good correlations between isolated plant traits and crop performance were the basis for ideotype selection. For instance, Hamblin and Donald (1974) found a significant inverse relationship between yield of F5 lines grown in plots and plant
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
height in single plants from F3 lines. Shorter plants with shorter leaves in the F3 tended to produce lines of similar habit in the F5 , and these characters were associated with lower F3 plant yield but higher F5 crop yield. Fischer and Kertesz (1976) and Syme (1972) examined the correlation between some single plant characters and crop yield and suggested that harvest index of spaced plants might be a useful predictor of crop yielding ability. This was in line with the suggestion by Hamblin and Donald (1974), as harvest index is inversely related to plant height (Siddique et al., 1989; Slafer and Andrade, 1993; Calderini et al., 1995; Acreche and Slafer, 2006). Importantly, the differences among genotypes in these traits seem to be dense-independent (differences in single isolated plants are maintained in dense crops; Fowler and Rasmusson, 1969), and as these traits were related to crop yield they became classical examples of wheat and barley ideotypes. In fact, it is well known that past increases in potential and actual yields have been largely associated with changes in harvest index, whereas increases in biomass have been small or negligible in bread wheat (Austin et al., 1989; Slafer and Andrade, 1993; Calderini and Slafer, 1998), barley (Abeledo et al., 2003) and durum wheat (Royo et al., 2007; Alvaro et al., 2008). As modern cereal cultivars have already reached optimum plant height for maximising yield (c. 0.75–0.95 m; Richards, 1992; Miralles and Slafer, 1995) and it would be limited opportunities to further rise harvest index (Foulkes et al., 2011). In this context, it would be important to identify alternative individual plant traits exhibiting some ability to predict crop yield (e.g. Pedro et al., 2012). Past attempts to identify traits in individual plants that may be useful to improve crop yield where mostly based on traits determined at maturity (Hsu and Walton, 1970; Syme, 1972; Fischer and Kertesz, 1976; Park et al., 1977). We now know that yield of wheat at maturity is largely determined at anthesis, as (i) yield is far more related to grain number than to average grain weight (Slafer, 2003, and references quoted therein), and (ii) grain number is largely determined by spike dry weight at anthesis (Fischer, 1985, 2007) as floret survival is related to pre-anthesis spike growth in wheat (González et al., 2011a). As spike growth does only occur during the stem elongation phase from terminal spikelet to anthesis (Kirby, 1988; González et al., 2003, 2005), traits in isolated plants at these two stages may be relevant for determining crop yield. Thus, it might be instrumental to test whether traits in individual isolated plants at critical stages (i.e. the period between the onset of stem elongation and anthesis; Miralles and Slafer, 2007; Fischer, 2011) may be responsible for crop productivity. The main objective of the present study was to test whether morpho-physiological traits at key developmental stages in single spaced plants would be associated with crop yield. If such traits could be identified, they might then be trustworthily used to select for in early generations aiming to improve crop performance in durum wheat.
2. Materials and methods 2.1. General Two field experiments were conducted during 2006/07 and 2008/09 growing seasons in Catalonia, NE Spain. Experiment I (2006/07) was located in a farmer field at Mafet (lat. 41◦ 48 42 N, long. 1◦ 5 43 E; altitude 340 m). Experiment II (2008/2009) was located in another farmer field at Agramunt (lat. 41◦ 47 17 N, long. 1◦ 5 59 E; altitude 337 m) in both neighbouring sites the soil type was classified as fluvisol calcari, following the soil classification of FAO (1990). Details of each experiment including soil nitrogen (N) and water contents at the beginning of the experiments, the amounts of N
43
fertilised as well as overall climatic conditions from sowing to the onset of stem elongation, from then to anthesis, and from then to maturity are shown in Table 1. Sowing date in the first experiment was too late for the region, due to delays in receiving the seeds of Cham 1. Due to this reason the seedlings did not need to go through the winter survival process and therefore the sowing density was relatively lower than in the second season in which we sowed the experiment in the optimal sowing period in the region and therefore used a much higher density to compensate for likely failures in winter survival (Table 1). In any case, crop canopies were well established in both cases with canopy fully intercepting incoming radiation well before anthesis. Weeds, insects and diseases were controlled or prevented using conventional commercial pesticides applied following the recommendations from their manufacturers.
2.2. Treatments and design Treatments in each of the experiments consisted of the factorial combination of (i) a number of genotypes, all high-yielding modern cultivars or lines, and (ii) a qualitative difference in the magnitude of interplant competition (isolated plants or dense canopy). The choice of genotypes restricting the variability to those that may be considered elite material in any realistic breeding programme reduces dramatically the likelihood of finding positive results (traits in isolated plants clearly related to crop yield) though the results that might be found would be readily applicable. The qualitative difference was sought to represent the most likely scenario of plant growth condition in early generations (mainly rather isolated plants with virtually inexistent interplant competition) and in actual crops grown to maximise yield per unit land area (dense crops with a strong interplant competition through most of the growing season). Experiment I was a first exploratory approach with only four genotypes: three durum wheat cultivars very well adapted to different regions of Spain (Simeto, Claudio, and Vitron; the three of them have been used as checks in the Spanish network of cultivar yield comparison) and a durum cultivar from ICARDA (Cham 1) known for combining high yield potential (Nachit et al., 2001) and some drought tolerance (Rekika et al., 1998); which previously exhibited high-yielding capacity in the experimental sites (Pedro et al., 2011). Experiment II was more comprehensive as it included 13 genotypes; seven of them were chosen because they were all well adapted to the Spanish Mediterranean conditions (the three cultivars used in experiment I plus Avispa, Arcoduro, Molino and Donduro), while the other six genotypes were four RILs derived from a cross of Cham 1 with Lahn (2004, 2410, 2408 and 2517), and both parental lines of the population, all proven to have good agronomic performance in the region in a previous independent study (Pedro et al., 2011). The treatments establishing the qualitative difference in interplant competition (isolated plants or dense canopy) were identical in both years. Isolated plants were sown in rows, 0.20 m apart, with a 0.30 m inter-row distance between plants (<20 plants m−2 ). In all the cases, each plot had one row per cultivar with 20 seeds per row, and plants in adjacent rows were planted in a zig–zag pattern, to minimise any interaction even at the very low density used. Dense canopies were achieved by installing conventional field plots sown at a density of 200 plants m−2 during the first growing season and 400 plants m−2 during the second one. The dense canopy treatment plots consisted of 6 rows, 18 cm apart (experiment I) or 20 cm apart (experiment II), and 6 m long. Treatments (genotypes by canopy structure, isolated plants or dense canopy) were arranged in a completed randomised design with three replicates.
24.8 19.8 9.1 20.3 11.9 5.3 110 38
156 38
129 46 120
9
25 20 8.1 20.7 15.7 6.2 32 60
An–Mt (d) )
0 204
100 201
)
(mm)
(kg N ha
−1
3.1. Yield in isolated individual plants and in dense crops
20-November II – 2008–2009
102
22-February I – 2006–2007
150
Sowing date
(kg N ha
−1
N fertilisation
At the onset of stem elongation (jointing, DC 3.1; Zadoks et al., 1974), anthesis (DC 6.5) and physiological maturity (DC 9.5) above ground biomass samples were taken both in isolated individual plants (5 plants per plot and replication) and in plots with dense crops (c. 0.1 m2 per plot and replication). Each sample from both, crop and isolated plants, was separated into main shoot and tillers, and within each of these two categories of shoots into stems (including leaf sheaths), green and senescent leaf laminae and spikes. At maturity yield and its main components, numbers of grains and spikes per unit land area or per plant (depending on whether they were determined in dense crop or in isolated plants, respectively), number of grains per spike and the average weight of the individual grains, were also determined. Nitrogen content of the samples taken at the three mentioned stages was analysed separately, for the different organs, by micro-Kjeldahl. In addition, in the single plant treatment, from jointing onwards plant height (measured from the soil up to the base of the spike), peduncle height (measured from the last extended node to the base of the spike), number of tillers, green area, flag leaf senescence (evaluated as a percentage of the leaf laminae that has lost the green colour) and SPAD (measured with Konica Minolta SPAD502) on the uppermost expanded leaf (from booting onwards the flag leaf) were determined weekly. With the measurements from all the growing periods, we calculated rates of stem extension, of tillering (before flowering) and of leaf senescence (after flowering) as reduction in both green area of the leaves and SPAD values; and estimated leaf area and SPAD durations,1 as the integral underneath the curve describing the dynamics of these two measurements over time. These durations were estimated for the whole period from jointing to maturity or for the periods from jointing to anthesis and from then to maturity. Taking into account the number of measured or estimated traits and their timings, a total of 57 (experiment I) and 114 traits (experiment II) in isolated individual plants were considered in this analysis (Table 2). We then analysed the relationships of yield, biomass and number of grains per unit land area in the dense crops as dependant variables against each of these 57 and 114 traits in the isolated individual plants as independent variables. 3. Results
Experiment and season
Initial N and water
97
Sw–Se (mm) Se–An (d) Sw–Se (d)
Se–An (mm)
Seasonal rainfall
72
Se–An (MJ m−2 d−1 ) Sw–Se (MJ m−2 d−1 ) An–Mt (◦ C) Se–An (◦ C) Sw–Se (◦ C)
2.3. Sampling and measurements
Duration
An–Mt (mm)
Average temperature
Average daily radiation
An–Mt (MJ m−2 d−1 )
A. Pedró et al. / Field Crops Research 138 (2012) 42–51 Table 1 Sowing date, water and mineral nitrogen (N–NO3 ) contents in the soil (1 m depth) at sowing, the amount of nitrogen fertilised and irrigation applied. Average duration for phenological phases [from sowing (Sw) to the onset of stem elongation (Se), from then to anthesis (An) and from anthesis to maturity (Mt)], seasonal rainfall, average temperature and radiation averaged for the three different phases are given for each of the two experiments grown in NE Spain.
44
There was a large degree of genotypic variation (P < 0.001), particularly in experiment II in which a much wider range of genotypes were grown. The range of yields observed in experiment II was from slightly under 5 to well above 15 g plant−1 when considering the isolated individual plants, and from less than 400 to more than 800 g m−2 for the dense crops (Fig. 1). As expected, yield was better explained by the number of grains (Fig. 1) than by their average weight (Fig. 1 insets) disregarding whether we considered the isolated individuals (Fig. 1(a)) or the performance of the dense crops (Fig. 1(b)). When considering the two experiments together the relationship was the same (Fig. 1) implying that (i) the environmental effect on yield (i.e. the differences between the two experiments) was also better explained by grain number than by grain size, and that yield variation between cultivars
1 ‘SPAD duration’ is an indirect estimate of the photosynthetic capacity through a particular growing period by integrating actual SPAD measurements at regular intervals (Pedro et al., 2012), an analogy of the ‘leaf area duration’ concept, used frequently as a general estimate of the crops capacity for intercepting radiation through a particular growing period (mostly during grain filling).
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
45
Table 2 Measured and calculated traits in individual plants either regularly through reproductive development or at the different phenological stages. Phenological stages
Measured traits
Calculated traits
Weekly from jointing to one week after anthesis
•Number of tillers •Leaf length •Leaf width •Proportion of leaf senesced •SPAD uppermost expanded leaf •Height •Peduncle length
•Tillering rate before anthesis •Leaf area uppermost expanded leaf; Leaf area duration; leaf senescence rate
Jointing, anthesis and maturity
•Number of tillers per plant •Height •Shoot weight per plant •Leaf area and weight per plant •Total above ground biomass
– – – •Specific leaf weight –
Jointing and anthesis
•Floral development •Nitrogen concentration (stem, leaf, spike)
– •Nitrogen in stems and leaves at jointing and anthesis and spikes at anthesis (in % and mg plant−1 )
Anthesis and maturity
•Number of spikes per plant •Number of spikelets per spike – •Spike dry weight
– – •Biomass accumulated pre-anthesis •Spike to biomass ratio
Maturity
•Grain yield •Grain number per plant •Grain weight – •Nitrogen concentration (biomass, grains)
•Harvest index – – •Biomass accumulated post-anthesis •Nitrogen in straw and grains (in % and mg plant−1 ); N harvest index
•SPAD duration (area underneath the curve of SPAD values over time) •Rates of stem extension –
in experiment I was also mainly due to variation in grain number (Fig. 1). Focusing on experiment II, that had a much larger number of genotypes compared, we observed that both crop yield and isolated plant yield were strongly related to biomass at maturity in all genotypes within each of these conditions (Table 3); although in the case of dense crops differences in biomass were not related at all to final plant height (R2 = 0.01), while differences in individual plant biomass were significantly related to final plant height (R2 = 0.68; P < 0.001). That is why plant height was positively related to yield in individual plants while it was completely unrelated to yield in dense crops (Table 3). The range of variation in plant height was rather narrow in crop canopies, from 70 to 79 cm, and larger in isolated plants, from 39 to 62 cm. In both isolated plants and dense crops, yield was also related to harvest index, though clearly less significantly than to biomass (Table 3). Differences among genotypes in spike dry weight at anthesis explained only partially yield of dense crops and did not explain yield of individual plants
(Table 3). Overall, it can be seen in Table 3, that several traits that may be relevant for conferring improved performance of individual plants were virtually irrelevant in the determination of yield of modern wheat genotypes when grown in dense crops (e.g. final plant height, final number of spikes). 3.2. Yield in dense crops vs traits in isolated individual plants Expectedly, yield of crops grown in dense plots was not related to yield of the individual plants grown in isolation (Fig. 2). For identifying variables in isolated individuals that may be responsible for the crop differences in yield, we focused again the analysis on data from experiment II. Not surprisingly, yield components of isolated individual plant (which were well related to plant yield; Table 3) did not explain crop yield either (Table 4). In fact, none of the traits measured or estimated at maturity in individual plants were significantly related to crop yield (Table 4). For instance, neither biomass nor harvest
1000
20
800
15
600
20
5
200
0
0 10 20 30 40 50 Average grainweight (mg grain-1)
15
400
1000
Crop yield (g m-2)
Individual plant yield (g plant-1)
10
10
5 (a) 0
0
800
0 20 40 60 Average grainweight (mg grain-1)
600 400 200
(b)
0 0
200 400 Individual grain number (plant-1)
600
0
5 10 15 20 Crop grain number (10-3 m-2)
25
Fig. 1. Relationships between plant yield and number of grains per plant for plants grown in isolation (left panel), and between crop yield and number of grains per unit land area for crops grown at a normal pant density (right panel) in experiments I and II (open and closed circles, respectively). Insets are the relationships between yield and average grain weight within the two contrasting growing conditions. Bars indicate the standard error of the means (SEM) for each cultivar.
46
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
Table 3 Correlation coefficients (R) of the relationships between yield (g m−2 ) and a number of traits measured at maturity (9.2 in the decimal code of (Zadoks et al., 1974), anthesis (6.5) or jointing (3.1) in experiment II for the isolated individual plants (left columns) or dense crops (right columns). When the coefficient is placed in between two columns is because the trait corresponds to the phase between the corresponding stages. Traits of individual plants and crop
Individual plants Maturity
Plant height (cm) Peduncle length (cm) Number of tillers (plant−1 ) Number of tillers (m−2 ) Number of spikelets (spike−1 ) Number of spikes (plant−1 ) Number of spikes (m−2 ) Stem dry weight, main shoot (g plant−1 ) Stem dry weight per plant (g plant−1 ) Stem dry weight (g m−2 ) Spike dry weight, main shoot (g plant−1 ) Spike dry weight per plant (g plant−1 ) Spike dry weight (g m−2 ) Biomass (g plant−1 ) Biomass (g m−2 ) Spike to biomass ratio (dimensionless) Number of grains (plant−1 ) Number of grains (m−2 ) Number of grains (spike−1 ) Grains per unit stem length (g cm−1 ) Average grain weight (mg grain−1 ) Harvest index (dimensionless) Uppermost leaf green area (cm2 ) Uppermost leaf SPAD (dimensionless) Green leaf area per plant (cm2 plant−1 ) Specific leaf weight (g m−2 ) Total N uptake (g N plant−1 ) Total N uptake (g N m−2 ) Stem N concentration (%) Leaf N concentration (%) Spike N concentration (%) N harvest index (dimensionless) Biomass accumulationjointing-anthesis (g plant−1 ) Biomass accumulationjointing-anthesis (g m−2 ) Biomass accumulationanthesis-matutity (g plant−1 ) Biomass accumulationanthesis-matutity (g m−2 ) Green leaf area durationjointing-maturity (◦ C d) Senecence rateanthesis-matutity (cm2 [◦ C d−1 ]) Spad durationjointing-maturity (◦ C d)
0.83*** 0.72** 0.72** – 0.48ns 0.79*** – 0.75*** 0.89*** – 0.89*** 0.98*** – 0.98*** – 0.69* 0.93*** – 0.65* 0.82*** 0.39ns 0.62* – – – – 0.99*** – 0.66** – 0.99*** 0.49ns – – 0.65* – 0.41ns −0.57ns 0.17ns
Crops Anthesis
Jointing −0.25 – 0.36ns – – – – −0.21ns −0.03ns – – – – −0.03ns – – – – – – – – −0.02ns −0.43ns 0.01ns −0.3ns 0.1ns – 0.11ns 0.09ns – –
0.80*** – 0.72** – – 0.61* – 0.63* 0.63* – 0.23ns 0.36ns – 0.64* – −0.24ns – – – – – – 0.54* 0.47ns 0.75** 0.17ns 0.68** – 0.67** 0.63* 0.49ns – 0.64* –
– – –
Maturity −0.11 – – 0.47ns – – 0.49ns – – 0.72** – – 0.84*** – 0.95*** 0.17ns – 0.87*** 0.59* 0.56* 0.19ns 0.76*** – – – – – 0.69** 0.29ns – 0.76*** 0.3ns – – – 0.57* – – – ns
Anthesis ns
0.15 – – 0.05ns – – 0.18ns – – 0.52ns – – 0.56* – 0.51ns 0.42ns – – – – – – – – −0.16ns 0.66** – 0.33ns 0.32ns 0.57* 0.11ns – – 0.48ns
– – –
Jointing −0.05ns – – −0.41ns – – – – – 0.1ns – – – – 0.09ns – – – – – – – – – 0.09ns 0.07ns – 0.21ns 0.18ns 0.23ns – –
– – – – –
The significance of the coefficients (*** P < 0.001, **P < 0.01, *P < 0.05, ns P < 0.05) is indicated.
Crop yield (g m -2)
1000 800 600 400 200 0 0
5
10
15
20 -1
Individual plant yield (g plant ) Fig. 2. Relationship between crop and isolated plant yield for experiments I and II (open and closed circles, respectively). Bars indicate the SEM for each cultivar in each of the two contrasting growing conditions.
index of individual plants explained any significant proportion of the variation in yield of the dense crops. In addition, when considering traits integrating through the stem elongation and the grain filling periods (plant growth, leaf area duration or SPAD duration accumulated in these periods) they did not explain well crop yield either (Table 4). Only when considering traits of isolated individual plants measured at anthesis we identified few traits that were somehow related to crop yield (Table 4). They were the partitioning of biomass to the spikes at anthesis (determining spike dry weight at anthesis) and specific leaf weight at anthesis (Table 4 and Fig. 3). All other traits measured or estimated did not explain crop yield well, although nitrogen uptake at anthesis in individual plants exhibited a positive trend (P < 0.1). None of the traits measured or estimated at jointing in individual plants grown in isolation were significantly related to crop yield (Table 4). The two traits identified in isolated individual plants explaining crop yield showed to be, at least in part, independent of density as there was a significant relationship between the trait measured in the dense crop and in isolated plants (Fig. 4). And these traits in the individual isolated plants were also related to the main attributes determining crop yield in the present study (Fig. 5). Particularly, above-ground crop biomass at maturity (Fig. 5(a) and (b)) and number of grain per m2 (Fig. 5(e) and (f)).
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
47
Table 4 Correlation coefficients (R) of the relationships between crop yield (g m−2 ) and several traits of the isolated individual plants measured at particular stages or calculated for specific phases during plant development When the coefficient is placed in between two columns is because the trait correspond to the phase between the corresponding stages. Traits of individual plants
Maturity
Plant height (cm) Peduncle length (cm) Number of tillers (plant−1 ) Number of spikelets (spike−1 ) Number of spikes (plant−1 ) Stem dry weight, main shoot (g plant−1 ) Stem dry weight per plant (g plant−1 ) Spike dry weight, main shoot (g plant−1 ) Spike dry weight per plant (g plant−1 ) Biomass (g plant−1 ) Spike to biomass ratio (dimensionless) Number of grains (plant−1 ) Number of grains (spike−1 ) Grains per unit stem length Grains per unit stem length (g cm−1 ) Average grain weight (mg grain−1 ) Harvest index (dimensionless) Uppermost leaf green area (cm2 ) Uppermost leaf SPAD (dimensionless) Green leaf area per plant (cm2 plant−1 ) Specific leaf weight (g m−2 ) Total N uptake (g N plant−1 ) Stem N concentration (%) Leaf N concentration (%) Spike N concentration (%) N harvest index (dimensionless) Biomass accumulationjointing-anthesis (g plant−1 ) Biomass accumulationanthesis-matutity (g plant−1 ) Green leaf area durationjointing-maturity (◦ C d) Spad durationjointing-maturity (◦ C d)
−0.25ns −0.24ns −0.14ns 0.41ns −0.09ns −0.08ns −0.1ns −0.02ns −0.14ns −0.17ns 0.17ns −0.11ns −0.02ns −0.02ns −0.16ns −0.33ns −0.07ns – – – – −0.16ns −0.12ns – −0.13ns −0.26ns – −0.29ns −0.20ns −0.22ns
Anthesis
Jointing
−0.07ns −0.15ns −0.23ns – −0.24ns 0.1ns 0.21ns 0.54* 0.50* 0.29ns 0.56* – – – – – – −0.15ns 0.21ns −0.12ns 0.61* 0.45ns 0.07ns 0.22ns 0.35ns – 0.31ns
0.35ns – −0.1ns – – 0.08ns −0.13ns – – 0.13ns – – – – – – – −0.11ns 0.01ns −0.1ns −0.2ns −0.26ns 0.25ns 0.24ns – – –
The significance of the coefficients (***P < 0.001, **P < 0.01, *P < 0.05, ns P < 0.05) is indicated.
4. Discussion Crop yield in experiment I was relatively low, associated with a late sowing, whilst yield of crops in experiment II was within the range expected from previous studies in the area (Cossani et al., 2007; Marti et al., 2007; Pedro et al., 2011). In all cases yield was related to the number of grains (per plant in isolated plants, and per m2 in crop stands), as it is commonly found in the literature for both bread (Fischer, 2007; Araus et al., 2008; Reynolds et al., 2009a) and
durum wheat (De Vita et al., 2007; Giunta et al., 2007; Pedro et al., 2011). In agronomic crops as well as in plants being selected by natural selection the number of grains is far more plastic than the size of the grain (Sadras, 2007; Sadras and Slafer, 2012; and reference cited therein). In general, all other traits related to yield within each of the two contrasting conditions (isolated plants or dense crops) represented well the most common physiological findings reported. For instance, individual plant yield was well related to plant height and tillers per plant or green leaf area per plant at
1000
(b)
Crop yield (g m-2)
(a) 800 600 400 200 0 20
30
40
Spike partitioning (%)
50
50
60
70
80
90
100 -2
Specific leaf weight (g m )
INDIVIDUAL PLANT TRAITS AT ANTHESIS Fig. 3. Relationships between crop yield and either (a) biomass partitioning to spike, or (b) specific leaf weight, measured at anthesis in individual plants grown in isolation. Bars indicate the SEM for each cultivar.
48
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
Specific leaf weight (g m-2 )
Spike partitioning (%)
CROP TRAITS AT ANTHESIS
30 (a) R2=0.47**
25
20
15 20
25
30
35
Spike partitioning (%)
40
70 (b) R2=0.38*
60
50
40 50
60
70
80
90
100 -2
Specific leaf weight (g m )
INDIVIDUAL PLANT TRAITS AT ANTHESIS Fig. 4. Relationship between traits measured in individual plants grown in isolation and the same traits measured in dense crops. The traits were: spike partitioning (a) and specific leaf weight (b) both at anthesis. Bars indicate the SEM for each cultivar in each of the two contrasting growing conditions. Determination coefficients of the relationships with their level of significance (**P < 0.01, *P < 0.05) are also shown in each panel.
anthesis, whilst crop yield was well related to nitrogen uptake and harvest index at maturity and specific leaf weight at anthesis, corroborating results in many different studies2 (e.g. Hamblin and Donald, 1974; Calderini et al., 1999; Alvaro et al., 2007; Foulkes et al., 2009; Rebetzke et al., 2011). In addition, we expectedly found no relationship between crop yield and yield of the isolated individual plants. This expectation was based on the well established fact that selection for yield in isolated plants is ineffective to breed for high-yielding cultivars (e.g. Bell, 1963; Donald, 1968). Thus, considering both the physiological bases of yield within either isolated plants or dense crops and the lack of relationship between yields in these two contrasting conditions, we can trust that the general picture produced by the cultivars chosen for this study is representative of situations in which breeders do normally work. In this study, instead of hypothesising with likely attributes of individual plants to be used as indicators of crop performance (e.g. Slafer, 2003; Reynolds et al., 2009b), we determined a large number of physiological attributes in individual plants and empirically tested the relationship between crop yield and them. This is the main reason why the number of tested genotypes had to be limited, None of the physiological traits measured in individual plants at maturity did relate well with crop yield. The lack of relationship between individual plant yield components and crop yield is in line with previous studies in which selecting in early populations for yield components did not result in improved crop yield (Donald, 1968; Knott, 1972). On the other hand, for traits such as harvest index and height of individual plants, there are previous studies in which these attributes in individual plants were found highly correlated to yield of the crops (Syme, 1972; Fischer and Kertesz, 1976). The reason for the apparently conflicting result is precisely the past success in breeding yield potential through increasing harvest index, while reducing plant height, particularly through
2 An apparent exception may be that yield was only slightly related with spike dry weight at anthesis in dense crops, whilst this relationship has been often rather strong in many comparisons of cultivars released at different eras (e.g. Calderini et al., 1999 and references quoted therein) or lines differing in semi-dwarfism (Flintham et al., 1997; Miralles and Slafer, 1995). However, the exception is only apparent because in several recent studies, in which the analysis was restricted to modern, well adapted, genotypes (which do not differ markedly in plant height) it has been found that yield differences were associated with either spike dry weight at anthesis or fruiting efficiency (the number of grains set per unit spike dry weight at anthesis), and that this efficiency may be as relevant as, or more relevant than, spike dry weight at anthesis in determining genotypic differences in grain number and yield (e.g. González et al., 2011b; Foulkes et al., 2011; Pedro et al., 2011).
the introgression of Rht genes (e.g. Youssefian et al., 1992; Miralles and Slafer, 1995; Flintham et al., 1997). However, that relationship frequently found in the past (with genotypes varying greatly in harvest index and plant height; Fischer and Kertesz, 1976) could not be expected in the present study. In our experiments all genotypes were modern lines with good agronomic performance, and therefore all having relatively high harvest indexes and plant heights within the optimum range, therefore not varying too much in these two attributes. Having selected these genotypes for the study is relevant as it does represent the most likely situation in realistic breeding elite populations. As we aimed to identify traits that may be conductive to further improving yield, we intentionally selected modern genotypes with good agronomic performance as actual cultivars already possess rather high harvest indexes (Calderini et al., 1999) and optimum plant height (Richards, 1992; Miralles and Slafer, 1995; Flintham et al., 1997). It would merely be an academic exercise to work with a heterogeneous population varying strongly in harvest index and plant height (without any doubt, strong negative relationships between height of isolated plant and crop yield would have been found if we would have used genotypes strongly varying in plant height, but these relationships would have meant virtually nothing to further raise yield potential in wheat respect to the best adapted modern genotypes). We must try identifying true alternative traits through which crop yields can be further improved (e.g. Foulkes et al., 2011; Reynolds et al., 2012). Despite that we tested a number of traits before maturity, at jointing and anthesis, none of the measured or calculated traits in isolated individual plants showed a clear-cut value to be considered a critical selection criterion in individual plants able to strongly determining crop yield. This exacerbates the difficulties in properly selecting in individual isolated plants, beyond discarding individual plants lacking “good agronomic type”, and emphasises the need of deepening in this sort of studies, instead of only building up knowledge based on results of comparisons of genotypes compared only in crop stands. The latter type of studies, which are the most common ones, are critical for a crop-physiological understanding of which traits determine crop yield (in dense crop conditions) but are ill-suited to soundly speculating on which traits might be valuable when selecting for in early generations. Having acknowledged unambiguously that none of the many traits studied in isolated individual plants could unequivocally be pointed as a definite selection criterion, it is worthwhile recognising that there were few traits of individual plants exhibiting some ability to predict crop yield. The most significant ones were
Biomass (g m -2 )
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
49
2000
(a)
(b)
R2 =0.30*
R2 =0.63***
1500 1000 500 0 20
25
30
35
40
0
2
4
6
8
10
6
8
10
6
8
10
6
8
10
Spike dry weight (g m -2 )
(c)
(d)
R2 =0.16 ns
R2 =0.28 ns
1000
500
0 20
25
30
35
40
0
2
4
25
(e)
(f)
R2 =0.56**
R2 =0.62***
20
Grain number (10 -3 m-2 )
CROP YIELD COMPONENTS
1500
15 10 5 0 20
25
30
35
40
0
2
4
Harvest Index
0.55
(g)
(h)
R2 =0.23 ns
R2 =0.09 ns
0.50 0.45 0.40 0.35 20
25
30
35
Spike partitioning (%)
40
0
2
4
Specific leaf weight (g m -2 )
INDIVIDUAL PLANT TRAITS AT ANTHESIS Fig. 5. Relationship between the main crop yield determinants and spike partitioning (left panels) or the specific leaf weight (right panels) at anthesis in individual plants grown in isolation. Crop yield determinants considered were biomass (a and b), spike dry weight (c and d), grain number per unit land area (e and f), and harvest index (g and h). Bars indicate the SEM for each cultivar. Determination coefficients of the relationships with their level of significance (**P < 0.01, *P < 0.05, ns P > 0.05) are also shown in each panel.
measured at anthesis and were related to either the gain in growth of either the plant (specific leaf weight) or the juvenile spike (spike partitioning). Both traits seem to be largely dense independent (Fig. 4), and may genuinely impact on grain yield. This might be related with the fact that both traits may represent allometric relationships, characterising the relative growth of a part in comparison with a whole (Reddy et al., 1998), and would be therefore more stable (as the probability of a ratio being affected by the resource availability is lower than that of growth being affected).
Specific leaf weight may be related to radiation use efficiency (Shearman et al., 2005). This is rather important in modern crops as radiation interception during the critical phase of stem elongation is normally maximised and the only way to increase biomass would then be through greater radiation use efficiency (Reynolds et al., 2007). Selection to increase biomass is essential to improve the performance as in modern cultivars harvest index is close to the theoretical maximum (Reynolds et al., 2009a). Spike partitioning at anthesis, may increase the number of grains (Miralles and Slafer, 2007; Fischer, 2011; Foulkes et al., 2011; González et al.,
50
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
2011b). As yield of modern cultivars is commonly more sinkthan source-limited during grain filling (Acreche and Slafer, 2009; Reynolds et al., 2009a; Pedro et al., 2011), the number of grain must be increased to further increase yield (Slafer et al., 2005; Foulkes et al., 2011). In addition, an increase in post-anthesis sink strength may increase crop photosynthesis during grain filling (Reynolds et al., 2005; Acreche et al., 2009; Parry et al., 2011). Actually, in the few cases where the relationships between maximum leaf photosynthesis and the year of release of cultivars were positive (Fischer et al., 1998) the increased photosynthesis was associated with an increased demand from a larger sink in modern cultivars compared with the older counterparts. The fact that attributes of isolated individual plants related to radiation interception (e.g. leaf area at anthesis) were hardly important to influence crop yield is not actually surprising. Firstly these attributes are dependant on density (and a plant with a large potential to produce leaf area may not achieve that potential in crowed environments, like those of realistic crops). Secondly, because well managed modern wheat crops possess a maximum leaf area index higher than that which is critical to maximise radiation interception (Acreche et al., 2009), with the exception of agricultural systems with very short growing seasons (e.g. Nordic countries). Consequently, there may be little room for improvements in crop growth and yield through selecting for traits related to radiation interception. In conclusion, we tried to find out morpho-physiological traits measured or calculated at different stages of development in single spaced plants associated with crop yield. Two traits, spike partitioning and specific leaf weight at anthesis, which are denseindependent and may have implication in yield determination, were found positively correlated to crop yield and may be potentially useful selection criteria, if surrogates to determine them more easily become available or if markers could be identified so that molecular assisted selection would be possible. Acknowledgments We thank Jaume Gregori (DAAR, Generalitat de Catalunya, Spain) for general agronomic advice within Agramunt area, and Miloudi Nachit (ICARDA, Syria) for providing the seeds of Cham 1, Lahn and the RILs 2004, 2410, 2408 and 2517. This work was mainly supported by OPTIWHEAT, an INCO-Project of the European Union on “Improving the Yield Stability of Durum Wheat under Mediterranean Conditions” (EC Contract Number: INCO-CT-2006-015460); with partial additional support from a project funded by the Spanish Ministry of Science and Innovation on “Physiological bases of yield and quality of cereals” (AGL2006-07814/AGR). AP held a FPI scholarship from the Spanish Ministry of Science and Innovation. References Abeledo, L.G., Calderini, D.F., Slafer, G.A., 2003. Genetic improvement of barley yield potential and its physiological determinants in Argentina (1944–1998). Euphytica 130, 325–334. Acreche, M.M., Slafer, G.A., 2006. Grain weight response to increases in number of grains in wheat in a Mediterranean area. Field Crops Res. 98, 52–59. Acreche, M.M., Briceno-Felix, G., Martin Sanchez, J.A., Slafer, G.A., 2009. Radiation interception and use efficiency as affected by breeding in Mediterranean wheat. Field Crops Res. 110, 91–97. Acreche, M.M., Slafer, G.A., 2009. Grain weight, radiation interception and use efficiency as affected by sink-strength in Mediterranean wheats released from 1940 to 2005. Field Crops Res. 110, 98–105. Alvaro, F., Garcia del Moral, L.F., Royo, C., 2007. Usefulness of remote sensing for the assessment of growth traits in individual cereal plants grown in the field. Int. J. Remote Sens. 28, 2497–2512. Alvaro, F., Isidro, J., Villegas, D., Garcia del Moral, L.F., Royo, C., 2008. Breeding effects on grain filling, biomass partitioning, and remobilization in Mediterranean durum wheat. Agron. J. 100, 361–370. Araus, J.L., Slafer, G.A., Royo, C., Dolores Serret, M., 2008. Breeding for yield potential and stress adaptation in cereals. Crit. Rev. Plant Sci. 27, 377–412.
Austin, R.B., Ford, M.A., Morgan, C.L., 1989. Genetic-improvement in the yield of winter-wheat – a further evaluation. J. Agric. Sci. 112, 295–301. Bell, G.D.H., 1963. Breeding techniques. In: Anonymous Barley Genetics I. Pudoc, Wageningen, pp. 285–306. Calderini, D.F., Dreccer, M.F., Slafer, G.A., 1995. Genetic-improvement in wheat yield and associated traits – a reexamination of previous results and the latest trends. Plant Breed. 114, 108–112. Calderini, D.F., Slafer, G.A., 1998. Changes in yield and yield stability in wheat during the 20th century. Field Crops Res. 57, 335–347. Calderini, D.F., Reynolds, M.P., Slafer, G.A., 1999. Genetic gains in wheat yield and main physiological changes associated with them during the 20th century. In: Satorre, E.H., Slafer, G.A. (Eds.), Wheat: Ecology and Physiology of Yield Determination. Food Product Press, New York, pp. 351–377. Calderini, D.F., Slafer, G.A., 1999. Has yield stability changed with genetic improvement of wheat yield? Euphytica 107, 51–59. Cossani, C.M., Savin, R., Slafer, G.A., 2007. Contrasting performance of barley and wheat in a wide range of conditions in Mediterranean Catalonia (Spain). Ann. Appl. Biol. 151, 167–173. De Vita, P., Nicosia, O.L.D., Nigro, F., Platani, C., Riefolo, C., Di Fonzo, N., Cattivelli, L., 2007. Breeding progress in morpho-physiological, agronomical and qualitative traits of durum wheat cultivars released in Italy during the 20th century. Eur. J. Agron. 26, 39–53. Donald, C.M., 1968. Breeding of crop ideotypes. Euphytica 17, 385–403. Donald, C.M., Hamblin, J., 1976. Biological yield and harvest index of cereals as agronomic and plant breeding criteria. Adv. Agron. 28, 361–405. FAO, 1990. F.A.O. UNESCO soil map of the world: revised legend. World Soil Resources Report 60. Fischer, R.A., Kertesz, Z., 1976. Harvest index in spaced populations and grain weight in microplots as indicators of yielding ability in spring wheat. Crop Sci. 16, 55–59. Fischer, R.A., 1985. Number of kernels in wheat crops and the influence of solarradiation and temperature. J. Agric. Sci. 105, 447–461. Fischer, R.A., Rees, D., Sayre, K.D., Lu, Z.M., Condon, A.G., Saavedra, A.L., 1998. Wheat yield progress associated with higher stomatal conductance and photosynthetic rate, and cooler canopies. Crop Sci. 38, 1467–1475. Fischer, R.A., 2007. Understanding the physiological basis of yield potential in wheat. J. Agric. Sci. 145, 99–113. Fischer, R.A., Edmeades, G.O., 2010. Breeding and cereal yield progress. Crop Sci. 50, S85–S98. Fischer, R.A., 2011. Wheat physiology: a review of recent developments. Crop Pasture Sci. 62, 95–114. Flintham, J.E., Borner, A., Worland, A.J., Gale, M.D., 1997. Optimizing wheat grain yield: effects of Rht (gibberellin-insensitive) dwarfing genes. J. Agric. Sci. 128, 11–25. Foulkes, M.J., Hawkesford, M.J., Barraclough, P.B., Holdsworth, M.J., Kerr, S., Kightley, S., Shewry, P.R., 2009. Identifying traits to improve the nitrogen economy of wheat: recent advances and future prospects. Field Crops Res. 114, 329–342. Foulkes, M.J., Slafer, G.A., Davies, W.J., Berry, P.M., Sylvester-Bradley, R., Martre, P., Calderini, D.F., Griffiths, S., Reynolds, M.P., 2011. Raising yield potential of wheat. III. Optimizing partitioning to grain while maintaining lodging resistance. J. Exp. Bot. 62, 469–486. Fowler, C.W., Rasmusson, D.C., 1969. Leaf area relationships and inheritance in barley. Crop Sci. 9, 729–731. Giunta, F., Motzo, R., Pruneddu, G., 2007. Trends since 1900 in the yield potential of Italian-bred durum wheat cultivars. Eur. J. Agron. 27, 12–24. González, F.G., Slafer, G.A., Miralles, D.J., 2003. Grain and floret number in response to photoperiod during stem elongation in fully and slightly vernalized wheats. Field Crops Res. 81, 17–27. González, F.G., Slafer, G.A., Miralles, D.J., 2005. Photoperiod during stem elongation in wheat: is its impact on fertile floret and grain number determination similar to that of radiation? Funct. Plant Biol. 32, 181–188. González, F.G., Miralles, D.J., Slafer, G.A., 2011a. Wheat floret survival as related to pre-anthesis spike growth. J. Exp. Bot. 62, 4889–4901. González, F.G., Terrile, I.J., Falcon, M.O., 2011b. Spike fertility and duration of stem elongation as promising traits to improve potential grain number (and yield): variation in modern Argentinean wheats. Crop Sci. 51, 1693–1702, http://dx.doi.org/10.2135/cropsci2010.08.0447. Hamblin, J., Donald, C.M., 1974. Relationships between plant form, competitive ability and grain yield in a barley cross. Euphytica 23, 535–542. Hsu, P., Walton, P.D., 1970. Inheritance of morphological and agronomic characters in spring wheat. Euphytica 19, 54–60. Kirby, E.J.M., 1988. Analysis of leaf, stem and ear growth in wheat from terminal spikelet stage to anthesis. Field Crops Res. 18, 127–140. Knott, D.R., 1972. Effects of selection for F2 plant yield on subsequent generations in wheat. Can. J. Plant Sci. 52, 721–726. Marti, J., Bort, J., Slafer, G.A., Araus, J.L., 2007. Can wheat yield be assessed by early measurements of normalized difference vegetation index? Ann. Appl. Biol. 150, 253–257. Miralles, D.J., Slafer, G.A., 1995. Yield, biomass and yield components in dwarf, semidwarf and tall isogenic lines of spring wheat under recommended and late sowing dates. Plant Breed. 114, 392–396. Miralles, D.J., Slafer, G.A., 2007. Sink limitations to yield in wheat: how could it be reduced? J. Agric. Sci. 145, 139–149. Nachit, M.M., Elouafi, I., Pagnotta, M.A., El Saleh, A., Iacono, E., Labhilili, M., Asbati, A., Azrak, M., Hazzam, H., Benscher, D., Khairallah, M., Ribaut, J.M., Tanzarella, O.A., Porceddu, E., Sorrells, M.E., 2001. Molecular linkage map for an
A. Pedró et al. / Field Crops Research 138 (2012) 42–51 intraspecific recombinant inbred population of durum wheat (Triticum turgidum L. var. durum). Theor. Appl. Genet. 102, 177–186. Park, S.J., Reinbergs, E., Song, L.S.P., 1977. Grain-yield and its components in spring barley under row and hill plot conditions. Euphytica 26, 521–526. Parry, M.A.J., Reynolds, M., Salvucci, M.E., Raines, C., Andralojc, P.J., Zhu, X., Price, G.D., Condon, A.G., Furbank, R.T., 2011. Raising yield potential of wheat. II. Increasing photosynthetic capacity and efficiency. J. Exp. Bot. 62, 453–467. Pedro, A., Savin, R., Habash, D.Z., Slafer, G.A., 2011. Physiological attributes associated with yield and stability in selected lines of a durum wheat population. Euphytica 180, 195–208. Pedro, A., Savin, R., Parry, M.A.J., Slafer, G.A., 2012. Selection for high grain number per unit stem length through four generations from mutants in a durum wheat population to increase yields of individual plants and crops. Field Crops Res. 129, 59–70. Rebetzke, G.J., Ellis, M.H., Bonnett, D.G., Condon, A.G., Falk, D., Richards, R.A., 2011. The Rht13 dwarfing gene reduces peduncle length and plant height to increase grain number and yield of wheat. Field Crops Res. 124, 323–331. Reddy, V.R., Pachepsky, Y.A., Whisler, F.D., 1998. Allometric relationships in fieldgrown soybean. Ann. Bot. 82, 125–131. Rekika, D., Nachit, M.M., Araus, J.L., Monneveux, P., 1998. Effects of water deficit on photosynthetic rate and osmotic adjustment in tetraploid wheats. Photosynthetica 35, 129–138. Reynolds, M., Calderini, D., Condon, A., Vargas, M., 2007. Association of source/sink traits with yield, biomass and radiation use efficiency among random sister lines from three wheat crosses in a high-yield environment. J. Agric. Sci. 145, 3–16. Reynolds, M., Foulkes, M.J., Slafer, G.A., Berry, P., Parry, M.A.J., Snape, J.W., Angus, W.J., 2009a. Raising yield potential in wheat. J. Exp. Bot. 60, 1899–1918. Reynolds, M., Manes, Y., Izanloo, A., Langridge, P., 2009b. Phenotyping approaches for physiological breeding and gene discovery in wheat. Ann. Appl. Biol. 155, 309–320. Reynolds, M., Foulkes, J., Furbank, R., Griffiths, S., King, J., Murchie, E., Parry, M.J., Slafer, G.A., 2012. Achieving yield gains in wheat. Plant Cell Envriron. 35, 1799–1823. Reynolds, M.P., Pellegrineschi, A., Skovmand, B., 2005. Sink-limitation to yield and biomass: a summary of some investigations in spring wheat. Ann. Appl. Biol. 146, 39–49.
51
Richards, R.A., 1992. The effect of dwarfing genes in spring wheat in dry environments. 1. Agronomic characteristics. Aust. J. Agric. Res. 43, 517–527. Royo, C., Alvaro, F., Martos, V., Ramdani, A., Isidro, J., Villegas, D., Garcia del Moral, L.F., 2007. Genetic changes in durum wheat yield components and associated traits in Italian and Spanish varieties during the 20th century. Euphytica 155, 259–270. Sadras, V.O., 2007. Evolutionary aspects of the trade-off between seed size and number in crops. Field Crops Res. 100, 125–138. Sadras, V.O., Slafer, G.A., 2012. Environmental modulation of yield components in cereals: heritabilities reveal a hierarchy of phenotypic plasticities. Field Crops Res. 127, 215–224. Shearman, V.J., Sylvester-Bradley, R., Scott, R.K., Foulkes, M.J., 2005. Physiological processes associated with wheat yield progress in the UK. Crop Sci. 45, 175–185. Siddique, K.H.M., Kirby, E.J.M., Perry, M.W., 1989. Ear stem ratio in old and modern wheat-varieties – relationship with improvement in number of grains per ear and yield. Field Crops Res. 21, 59–78. Slafer, G.A., Andrade, F.H., 1991. Changes in physiological attributes of the dry-matter economy of bread wheat (Triticum aestivum) through geneticimprovement of grain-yield potential at different regions of the world – a review. Euphytica 58, 37–49. Slafer, G.A., Andrade, F.H., 1993. Physiological attributes related to the generation of grain-yield in bread wheat cultivars released at different eras. Field Crops Res. 31, 351–367. Slafer, G.A., 2003. Genetic basis of yield as viewed from a crop physiologist’s perspective. Ann. Appl. Biol. 142, 117–128. Slafer, G.A., Araus, J.L., Royo, C., Garcia del Moral, L.F., 2005. Promising ecophysiological traits for genetic improvement of cereal yields in Mediterranean environments. Ann. Appl. Biol. 146, 61–70. Syme, J.R., 1972. Single-plant characters as a measure of field plot performance of wheat cultivars. Aust. J. Agric. Res. 23, 753–760. Youssefian, S., Kirby, E.J.M., Gale, M.D., 1992. Pleiotropic effects of the Ga-insensitive Rht dwarfing genes in wheat. Effects on development of the ear, stem and leaves. Field Crops Res. 28, 179–190. Zadoks, J.C., Chang, T.T., Konzak, C.F., 1974. Decimal code for growth stages of cereals. Weed Res. 14, 415–421.
Contents lists available at SciVerse ScienceDirect
Field Crops Research journal homepage: www.elsevier.com/locate/fcr
Crop productivity as related to single-plant traits at key phenological stages in durum wheat Anna Pedró a , Roxana Savin a , Gustavo A. Slafer a,b,∗ a b
Department of Crop and Forest Sciences and AGROTECNIO (Centre for Research in Agrotechnology), University of Lleida, Av. Rovira Roure 191, 25198 Lleida, Spain ICREA (Catalonian Institution for Research and Advanced Studies), Barcelona, Spain
a r t i c l e
i n f o
Article history: Received 2 April 2012 Received in revised form 16 August 2012 Accepted 19 September 2012 Keywords: Grain yield Grain yield components Morpho-physiological traits Selection criteria Isolated plants, Triticum durum
a b s t r a c t Selection based on single plants is a necessary step during early generations in breeding programs, where populations are still heterogeneous. A major problem is that individual plant performance is rather independent of crop performance, and there are few studies indicating physiological traits in individual plants that are reliable to select for to increase crop yield. In this context we aimed to find out whether it is possible to identify morpho-physiological traits in single spaced plants that might be trustworthily used for selecting in early generations for improving crop performance in durum wheat. We have grown during two seasons both isolated plants and dense populations of the same durum wheat genotypes. Isolated plants were sown at <20 plants m−2 while crop populations were grown at 200 plants m−2 during the first experiment and 400 plants m−2 during the second one. Several traits (57 and 114 in the first and second experiments, respectively) were measured or estimated at different steps during the crop cycle in both conditions. Both, crop and individual plant yields were better explained by the number of grains than by the average weight of the grains. As expected, there was no relationship between crop yield and yield of the individual plants. Yield components and other traits measured in individual plants at maturity did not relate well with crop yield. However, specific leaf weight and spike partitioning of isolated plants determined at anthesis exhibited clear trends to be positively related to crop yield. Both traits are dense independent and may be potentially useful selection criteria, if surrogates to determine them more easily or molecular markers become available. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Breeding of grain crops has been very successful during the second half of the 20th century, essentially based on an empirical approach of selecting for yield per se (Slafer and Andrade, 1991). But we now face a worrisome slowdown in the rate of genetic gains (Reynolds et al., 2009a; Fischer and Edmeades, 2010). It has been speculated several times that achieving a better understanding of yield physiology would be instrumental to regain healthier rates of genetic gains in yield (Calderini and Slafer, 1999; Slafer, 2003; Fischer, 2007, 2011; Araus et al., 2008; Reynolds et al., 2009a,b, 2012; Foulkes et al., 2011). However, most of the knowledge we have gained on yield physiology in the last decades derives from studies analysing crop yield together with other crop physiological attributes. Focusing on attributes of the crop canopy would be useful in selection of late generations in which breeders select on
∗ Corresponding author at: Department of Crop and Forest Sciences and AGROTECNIO (Centre for Research in Agrotechnology), University of Lleida, Av. Rovira Roure 191, 25198 Lleida, Spain. Tel.: +34 973 003659. E-mail address: [email protected] (G.A. Slafer). 0378-4290/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fcr.2012.09.016
actual near-homogeneous populations in a crop dense stand. However, the problem remains that the strongest selection pressure is applied in early generations when selection is based on single plant performance and individual plant productivity may be rather independent of that of the crop, as lucidly evidenced by Donald some half-century ago when introducing the concept of ideotype (Donald, 1968; Donald and Hamblin, 1976). Even though there have been many attempts to offer ideotypes in the literature, it is noticeably small the body of evidences in which morpho-physiological traits of isolated individuals of a particular genotype are actually compared with the performance of the crop of that genotype in dense stands. This sort of comparison might provide breeders with selection criteria to be used on isolated plants in early generations to increase the likelihood of producing high-yielding cultivars few generations later. If such attributes in isolated plants were known, their use as selection criteria in early generations can improve the likelihood of success. Examples of good correlations between isolated plant traits and crop performance were the basis for ideotype selection. For instance, Hamblin and Donald (1974) found a significant inverse relationship between yield of F5 lines grown in plots and plant
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
height in single plants from F3 lines. Shorter plants with shorter leaves in the F3 tended to produce lines of similar habit in the F5 , and these characters were associated with lower F3 plant yield but higher F5 crop yield. Fischer and Kertesz (1976) and Syme (1972) examined the correlation between some single plant characters and crop yield and suggested that harvest index of spaced plants might be a useful predictor of crop yielding ability. This was in line with the suggestion by Hamblin and Donald (1974), as harvest index is inversely related to plant height (Siddique et al., 1989; Slafer and Andrade, 1993; Calderini et al., 1995; Acreche and Slafer, 2006). Importantly, the differences among genotypes in these traits seem to be dense-independent (differences in single isolated plants are maintained in dense crops; Fowler and Rasmusson, 1969), and as these traits were related to crop yield they became classical examples of wheat and barley ideotypes. In fact, it is well known that past increases in potential and actual yields have been largely associated with changes in harvest index, whereas increases in biomass have been small or negligible in bread wheat (Austin et al., 1989; Slafer and Andrade, 1993; Calderini and Slafer, 1998), barley (Abeledo et al., 2003) and durum wheat (Royo et al., 2007; Alvaro et al., 2008). As modern cereal cultivars have already reached optimum plant height for maximising yield (c. 0.75–0.95 m; Richards, 1992; Miralles and Slafer, 1995) and it would be limited opportunities to further rise harvest index (Foulkes et al., 2011). In this context, it would be important to identify alternative individual plant traits exhibiting some ability to predict crop yield (e.g. Pedro et al., 2012). Past attempts to identify traits in individual plants that may be useful to improve crop yield where mostly based on traits determined at maturity (Hsu and Walton, 1970; Syme, 1972; Fischer and Kertesz, 1976; Park et al., 1977). We now know that yield of wheat at maturity is largely determined at anthesis, as (i) yield is far more related to grain number than to average grain weight (Slafer, 2003, and references quoted therein), and (ii) grain number is largely determined by spike dry weight at anthesis (Fischer, 1985, 2007) as floret survival is related to pre-anthesis spike growth in wheat (González et al., 2011a). As spike growth does only occur during the stem elongation phase from terminal spikelet to anthesis (Kirby, 1988; González et al., 2003, 2005), traits in isolated plants at these two stages may be relevant for determining crop yield. Thus, it might be instrumental to test whether traits in individual isolated plants at critical stages (i.e. the period between the onset of stem elongation and anthesis; Miralles and Slafer, 2007; Fischer, 2011) may be responsible for crop productivity. The main objective of the present study was to test whether morpho-physiological traits at key developmental stages in single spaced plants would be associated with crop yield. If such traits could be identified, they might then be trustworthily used to select for in early generations aiming to improve crop performance in durum wheat.
2. Materials and methods 2.1. General Two field experiments were conducted during 2006/07 and 2008/09 growing seasons in Catalonia, NE Spain. Experiment I (2006/07) was located in a farmer field at Mafet (lat. 41◦ 48 42 N, long. 1◦ 5 43 E; altitude 340 m). Experiment II (2008/2009) was located in another farmer field at Agramunt (lat. 41◦ 47 17 N, long. 1◦ 5 59 E; altitude 337 m) in both neighbouring sites the soil type was classified as fluvisol calcari, following the soil classification of FAO (1990). Details of each experiment including soil nitrogen (N) and water contents at the beginning of the experiments, the amounts of N
43
fertilised as well as overall climatic conditions from sowing to the onset of stem elongation, from then to anthesis, and from then to maturity are shown in Table 1. Sowing date in the first experiment was too late for the region, due to delays in receiving the seeds of Cham 1. Due to this reason the seedlings did not need to go through the winter survival process and therefore the sowing density was relatively lower than in the second season in which we sowed the experiment in the optimal sowing period in the region and therefore used a much higher density to compensate for likely failures in winter survival (Table 1). In any case, crop canopies were well established in both cases with canopy fully intercepting incoming radiation well before anthesis. Weeds, insects and diseases were controlled or prevented using conventional commercial pesticides applied following the recommendations from their manufacturers.
2.2. Treatments and design Treatments in each of the experiments consisted of the factorial combination of (i) a number of genotypes, all high-yielding modern cultivars or lines, and (ii) a qualitative difference in the magnitude of interplant competition (isolated plants or dense canopy). The choice of genotypes restricting the variability to those that may be considered elite material in any realistic breeding programme reduces dramatically the likelihood of finding positive results (traits in isolated plants clearly related to crop yield) though the results that might be found would be readily applicable. The qualitative difference was sought to represent the most likely scenario of plant growth condition in early generations (mainly rather isolated plants with virtually inexistent interplant competition) and in actual crops grown to maximise yield per unit land area (dense crops with a strong interplant competition through most of the growing season). Experiment I was a first exploratory approach with only four genotypes: three durum wheat cultivars very well adapted to different regions of Spain (Simeto, Claudio, and Vitron; the three of them have been used as checks in the Spanish network of cultivar yield comparison) and a durum cultivar from ICARDA (Cham 1) known for combining high yield potential (Nachit et al., 2001) and some drought tolerance (Rekika et al., 1998); which previously exhibited high-yielding capacity in the experimental sites (Pedro et al., 2011). Experiment II was more comprehensive as it included 13 genotypes; seven of them were chosen because they were all well adapted to the Spanish Mediterranean conditions (the three cultivars used in experiment I plus Avispa, Arcoduro, Molino and Donduro), while the other six genotypes were four RILs derived from a cross of Cham 1 with Lahn (2004, 2410, 2408 and 2517), and both parental lines of the population, all proven to have good agronomic performance in the region in a previous independent study (Pedro et al., 2011). The treatments establishing the qualitative difference in interplant competition (isolated plants or dense canopy) were identical in both years. Isolated plants were sown in rows, 0.20 m apart, with a 0.30 m inter-row distance between plants (<20 plants m−2 ). In all the cases, each plot had one row per cultivar with 20 seeds per row, and plants in adjacent rows were planted in a zig–zag pattern, to minimise any interaction even at the very low density used. Dense canopies were achieved by installing conventional field plots sown at a density of 200 plants m−2 during the first growing season and 400 plants m−2 during the second one. The dense canopy treatment plots consisted of 6 rows, 18 cm apart (experiment I) or 20 cm apart (experiment II), and 6 m long. Treatments (genotypes by canopy structure, isolated plants or dense canopy) were arranged in a completed randomised design with three replicates.
24.8 19.8 9.1 20.3 11.9 5.3 110 38
156 38
129 46 120
9
25 20 8.1 20.7 15.7 6.2 32 60
An–Mt (d) )
0 204
100 201
)
(mm)
(kg N ha
−1
3.1. Yield in isolated individual plants and in dense crops
20-November II – 2008–2009
102
22-February I – 2006–2007
150
Sowing date
(kg N ha
−1
N fertilisation
At the onset of stem elongation (jointing, DC 3.1; Zadoks et al., 1974), anthesis (DC 6.5) and physiological maturity (DC 9.5) above ground biomass samples were taken both in isolated individual plants (5 plants per plot and replication) and in plots with dense crops (c. 0.1 m2 per plot and replication). Each sample from both, crop and isolated plants, was separated into main shoot and tillers, and within each of these two categories of shoots into stems (including leaf sheaths), green and senescent leaf laminae and spikes. At maturity yield and its main components, numbers of grains and spikes per unit land area or per plant (depending on whether they were determined in dense crop or in isolated plants, respectively), number of grains per spike and the average weight of the individual grains, were also determined. Nitrogen content of the samples taken at the three mentioned stages was analysed separately, for the different organs, by micro-Kjeldahl. In addition, in the single plant treatment, from jointing onwards plant height (measured from the soil up to the base of the spike), peduncle height (measured from the last extended node to the base of the spike), number of tillers, green area, flag leaf senescence (evaluated as a percentage of the leaf laminae that has lost the green colour) and SPAD (measured with Konica Minolta SPAD502) on the uppermost expanded leaf (from booting onwards the flag leaf) were determined weekly. With the measurements from all the growing periods, we calculated rates of stem extension, of tillering (before flowering) and of leaf senescence (after flowering) as reduction in both green area of the leaves and SPAD values; and estimated leaf area and SPAD durations,1 as the integral underneath the curve describing the dynamics of these two measurements over time. These durations were estimated for the whole period from jointing to maturity or for the periods from jointing to anthesis and from then to maturity. Taking into account the number of measured or estimated traits and their timings, a total of 57 (experiment I) and 114 traits (experiment II) in isolated individual plants were considered in this analysis (Table 2). We then analysed the relationships of yield, biomass and number of grains per unit land area in the dense crops as dependant variables against each of these 57 and 114 traits in the isolated individual plants as independent variables. 3. Results
Experiment and season
Initial N and water
97
Sw–Se (mm) Se–An (d) Sw–Se (d)
Se–An (mm)
Seasonal rainfall
72
Se–An (MJ m−2 d−1 ) Sw–Se (MJ m−2 d−1 ) An–Mt (◦ C) Se–An (◦ C) Sw–Se (◦ C)
2.3. Sampling and measurements
Duration
An–Mt (mm)
Average temperature
Average daily radiation
An–Mt (MJ m−2 d−1 )
A. Pedró et al. / Field Crops Research 138 (2012) 42–51 Table 1 Sowing date, water and mineral nitrogen (N–NO3 ) contents in the soil (1 m depth) at sowing, the amount of nitrogen fertilised and irrigation applied. Average duration for phenological phases [from sowing (Sw) to the onset of stem elongation (Se), from then to anthesis (An) and from anthesis to maturity (Mt)], seasonal rainfall, average temperature and radiation averaged for the three different phases are given for each of the two experiments grown in NE Spain.
44
There was a large degree of genotypic variation (P < 0.001), particularly in experiment II in which a much wider range of genotypes were grown. The range of yields observed in experiment II was from slightly under 5 to well above 15 g plant−1 when considering the isolated individual plants, and from less than 400 to more than 800 g m−2 for the dense crops (Fig. 1). As expected, yield was better explained by the number of grains (Fig. 1) than by their average weight (Fig. 1 insets) disregarding whether we considered the isolated individuals (Fig. 1(a)) or the performance of the dense crops (Fig. 1(b)). When considering the two experiments together the relationship was the same (Fig. 1) implying that (i) the environmental effect on yield (i.e. the differences between the two experiments) was also better explained by grain number than by grain size, and that yield variation between cultivars
1 ‘SPAD duration’ is an indirect estimate of the photosynthetic capacity through a particular growing period by integrating actual SPAD measurements at regular intervals (Pedro et al., 2012), an analogy of the ‘leaf area duration’ concept, used frequently as a general estimate of the crops capacity for intercepting radiation through a particular growing period (mostly during grain filling).
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
45
Table 2 Measured and calculated traits in individual plants either regularly through reproductive development or at the different phenological stages. Phenological stages
Measured traits
Calculated traits
Weekly from jointing to one week after anthesis
•Number of tillers •Leaf length •Leaf width •Proportion of leaf senesced •SPAD uppermost expanded leaf •Height •Peduncle length
•Tillering rate before anthesis •Leaf area uppermost expanded leaf; Leaf area duration; leaf senescence rate
Jointing, anthesis and maturity
•Number of tillers per plant •Height •Shoot weight per plant •Leaf area and weight per plant •Total above ground biomass
– – – •Specific leaf weight –
Jointing and anthesis
•Floral development •Nitrogen concentration (stem, leaf, spike)
– •Nitrogen in stems and leaves at jointing and anthesis and spikes at anthesis (in % and mg plant−1 )
Anthesis and maturity
•Number of spikes per plant •Number of spikelets per spike – •Spike dry weight
– – •Biomass accumulated pre-anthesis •Spike to biomass ratio
Maturity
•Grain yield •Grain number per plant •Grain weight – •Nitrogen concentration (biomass, grains)
•Harvest index – – •Biomass accumulated post-anthesis •Nitrogen in straw and grains (in % and mg plant−1 ); N harvest index
•SPAD duration (area underneath the curve of SPAD values over time) •Rates of stem extension –
in experiment I was also mainly due to variation in grain number (Fig. 1). Focusing on experiment II, that had a much larger number of genotypes compared, we observed that both crop yield and isolated plant yield were strongly related to biomass at maturity in all genotypes within each of these conditions (Table 3); although in the case of dense crops differences in biomass were not related at all to final plant height (R2 = 0.01), while differences in individual plant biomass were significantly related to final plant height (R2 = 0.68; P < 0.001). That is why plant height was positively related to yield in individual plants while it was completely unrelated to yield in dense crops (Table 3). The range of variation in plant height was rather narrow in crop canopies, from 70 to 79 cm, and larger in isolated plants, from 39 to 62 cm. In both isolated plants and dense crops, yield was also related to harvest index, though clearly less significantly than to biomass (Table 3). Differences among genotypes in spike dry weight at anthesis explained only partially yield of dense crops and did not explain yield of individual plants
(Table 3). Overall, it can be seen in Table 3, that several traits that may be relevant for conferring improved performance of individual plants were virtually irrelevant in the determination of yield of modern wheat genotypes when grown in dense crops (e.g. final plant height, final number of spikes). 3.2. Yield in dense crops vs traits in isolated individual plants Expectedly, yield of crops grown in dense plots was not related to yield of the individual plants grown in isolation (Fig. 2). For identifying variables in isolated individuals that may be responsible for the crop differences in yield, we focused again the analysis on data from experiment II. Not surprisingly, yield components of isolated individual plant (which were well related to plant yield; Table 3) did not explain crop yield either (Table 4). In fact, none of the traits measured or estimated at maturity in individual plants were significantly related to crop yield (Table 4). For instance, neither biomass nor harvest
1000
20
800
15
600
20
5
200
0
0 10 20 30 40 50 Average grainweight (mg grain-1)
15
400
1000
Crop yield (g m-2)
Individual plant yield (g plant-1)
10
10
5 (a) 0
0
800
0 20 40 60 Average grainweight (mg grain-1)
600 400 200
(b)
0 0
200 400 Individual grain number (plant-1)
600
0
5 10 15 20 Crop grain number (10-3 m-2)
25
Fig. 1. Relationships between plant yield and number of grains per plant for plants grown in isolation (left panel), and between crop yield and number of grains per unit land area for crops grown at a normal pant density (right panel) in experiments I and II (open and closed circles, respectively). Insets are the relationships between yield and average grain weight within the two contrasting growing conditions. Bars indicate the standard error of the means (SEM) for each cultivar.
46
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
Table 3 Correlation coefficients (R) of the relationships between yield (g m−2 ) and a number of traits measured at maturity (9.2 in the decimal code of (Zadoks et al., 1974), anthesis (6.5) or jointing (3.1) in experiment II for the isolated individual plants (left columns) or dense crops (right columns). When the coefficient is placed in between two columns is because the trait corresponds to the phase between the corresponding stages. Traits of individual plants and crop
Individual plants Maturity
Plant height (cm) Peduncle length (cm) Number of tillers (plant−1 ) Number of tillers (m−2 ) Number of spikelets (spike−1 ) Number of spikes (plant−1 ) Number of spikes (m−2 ) Stem dry weight, main shoot (g plant−1 ) Stem dry weight per plant (g plant−1 ) Stem dry weight (g m−2 ) Spike dry weight, main shoot (g plant−1 ) Spike dry weight per plant (g plant−1 ) Spike dry weight (g m−2 ) Biomass (g plant−1 ) Biomass (g m−2 ) Spike to biomass ratio (dimensionless) Number of grains (plant−1 ) Number of grains (m−2 ) Number of grains (spike−1 ) Grains per unit stem length (g cm−1 ) Average grain weight (mg grain−1 ) Harvest index (dimensionless) Uppermost leaf green area (cm2 ) Uppermost leaf SPAD (dimensionless) Green leaf area per plant (cm2 plant−1 ) Specific leaf weight (g m−2 ) Total N uptake (g N plant−1 ) Total N uptake (g N m−2 ) Stem N concentration (%) Leaf N concentration (%) Spike N concentration (%) N harvest index (dimensionless) Biomass accumulationjointing-anthesis (g plant−1 ) Biomass accumulationjointing-anthesis (g m−2 ) Biomass accumulationanthesis-matutity (g plant−1 ) Biomass accumulationanthesis-matutity (g m−2 ) Green leaf area durationjointing-maturity (◦ C d) Senecence rateanthesis-matutity (cm2 [◦ C d−1 ]) Spad durationjointing-maturity (◦ C d)
0.83*** 0.72** 0.72** – 0.48ns 0.79*** – 0.75*** 0.89*** – 0.89*** 0.98*** – 0.98*** – 0.69* 0.93*** – 0.65* 0.82*** 0.39ns 0.62* – – – – 0.99*** – 0.66** – 0.99*** 0.49ns – – 0.65* – 0.41ns −0.57ns 0.17ns
Crops Anthesis
Jointing −0.25 – 0.36ns – – – – −0.21ns −0.03ns – – – – −0.03ns – – – – – – – – −0.02ns −0.43ns 0.01ns −0.3ns 0.1ns – 0.11ns 0.09ns – –
0.80*** – 0.72** – – 0.61* – 0.63* 0.63* – 0.23ns 0.36ns – 0.64* – −0.24ns – – – – – – 0.54* 0.47ns 0.75** 0.17ns 0.68** – 0.67** 0.63* 0.49ns – 0.64* –
– – –
Maturity −0.11 – – 0.47ns – – 0.49ns – – 0.72** – – 0.84*** – 0.95*** 0.17ns – 0.87*** 0.59* 0.56* 0.19ns 0.76*** – – – – – 0.69** 0.29ns – 0.76*** 0.3ns – – – 0.57* – – – ns
Anthesis ns
0.15 – – 0.05ns – – 0.18ns – – 0.52ns – – 0.56* – 0.51ns 0.42ns – – – – – – – – −0.16ns 0.66** – 0.33ns 0.32ns 0.57* 0.11ns – – 0.48ns
– – –
Jointing −0.05ns – – −0.41ns – – – – – 0.1ns – – – – 0.09ns – – – – – – – – – 0.09ns 0.07ns – 0.21ns 0.18ns 0.23ns – –
– – – – –
The significance of the coefficients (*** P < 0.001, **P < 0.01, *P < 0.05, ns P < 0.05) is indicated.
Crop yield (g m -2)
1000 800 600 400 200 0 0
5
10
15
20 -1
Individual plant yield (g plant ) Fig. 2. Relationship between crop and isolated plant yield for experiments I and II (open and closed circles, respectively). Bars indicate the SEM for each cultivar in each of the two contrasting growing conditions.
index of individual plants explained any significant proportion of the variation in yield of the dense crops. In addition, when considering traits integrating through the stem elongation and the grain filling periods (plant growth, leaf area duration or SPAD duration accumulated in these periods) they did not explain well crop yield either (Table 4). Only when considering traits of isolated individual plants measured at anthesis we identified few traits that were somehow related to crop yield (Table 4). They were the partitioning of biomass to the spikes at anthesis (determining spike dry weight at anthesis) and specific leaf weight at anthesis (Table 4 and Fig. 3). All other traits measured or estimated did not explain crop yield well, although nitrogen uptake at anthesis in individual plants exhibited a positive trend (P < 0.1). None of the traits measured or estimated at jointing in individual plants grown in isolation were significantly related to crop yield (Table 4). The two traits identified in isolated individual plants explaining crop yield showed to be, at least in part, independent of density as there was a significant relationship between the trait measured in the dense crop and in isolated plants (Fig. 4). And these traits in the individual isolated plants were also related to the main attributes determining crop yield in the present study (Fig. 5). Particularly, above-ground crop biomass at maturity (Fig. 5(a) and (b)) and number of grain per m2 (Fig. 5(e) and (f)).
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
47
Table 4 Correlation coefficients (R) of the relationships between crop yield (g m−2 ) and several traits of the isolated individual plants measured at particular stages or calculated for specific phases during plant development When the coefficient is placed in between two columns is because the trait correspond to the phase between the corresponding stages. Traits of individual plants
Maturity
Plant height (cm) Peduncle length (cm) Number of tillers (plant−1 ) Number of spikelets (spike−1 ) Number of spikes (plant−1 ) Stem dry weight, main shoot (g plant−1 ) Stem dry weight per plant (g plant−1 ) Spike dry weight, main shoot (g plant−1 ) Spike dry weight per plant (g plant−1 ) Biomass (g plant−1 ) Spike to biomass ratio (dimensionless) Number of grains (plant−1 ) Number of grains (spike−1 ) Grains per unit stem length Grains per unit stem length (g cm−1 ) Average grain weight (mg grain−1 ) Harvest index (dimensionless) Uppermost leaf green area (cm2 ) Uppermost leaf SPAD (dimensionless) Green leaf area per plant (cm2 plant−1 ) Specific leaf weight (g m−2 ) Total N uptake (g N plant−1 ) Stem N concentration (%) Leaf N concentration (%) Spike N concentration (%) N harvest index (dimensionless) Biomass accumulationjointing-anthesis (g plant−1 ) Biomass accumulationanthesis-matutity (g plant−1 ) Green leaf area durationjointing-maturity (◦ C d) Spad durationjointing-maturity (◦ C d)
−0.25ns −0.24ns −0.14ns 0.41ns −0.09ns −0.08ns −0.1ns −0.02ns −0.14ns −0.17ns 0.17ns −0.11ns −0.02ns −0.02ns −0.16ns −0.33ns −0.07ns – – – – −0.16ns −0.12ns – −0.13ns −0.26ns – −0.29ns −0.20ns −0.22ns
Anthesis
Jointing
−0.07ns −0.15ns −0.23ns – −0.24ns 0.1ns 0.21ns 0.54* 0.50* 0.29ns 0.56* – – – – – – −0.15ns 0.21ns −0.12ns 0.61* 0.45ns 0.07ns 0.22ns 0.35ns – 0.31ns
0.35ns – −0.1ns – – 0.08ns −0.13ns – – 0.13ns – – – – – – – −0.11ns 0.01ns −0.1ns −0.2ns −0.26ns 0.25ns 0.24ns – – –
The significance of the coefficients (***P < 0.001, **P < 0.01, *P < 0.05, ns P < 0.05) is indicated.
4. Discussion Crop yield in experiment I was relatively low, associated with a late sowing, whilst yield of crops in experiment II was within the range expected from previous studies in the area (Cossani et al., 2007; Marti et al., 2007; Pedro et al., 2011). In all cases yield was related to the number of grains (per plant in isolated plants, and per m2 in crop stands), as it is commonly found in the literature for both bread (Fischer, 2007; Araus et al., 2008; Reynolds et al., 2009a) and
durum wheat (De Vita et al., 2007; Giunta et al., 2007; Pedro et al., 2011). In agronomic crops as well as in plants being selected by natural selection the number of grains is far more plastic than the size of the grain (Sadras, 2007; Sadras and Slafer, 2012; and reference cited therein). In general, all other traits related to yield within each of the two contrasting conditions (isolated plants or dense crops) represented well the most common physiological findings reported. For instance, individual plant yield was well related to plant height and tillers per plant or green leaf area per plant at
1000
(b)
Crop yield (g m-2)
(a) 800 600 400 200 0 20
30
40
Spike partitioning (%)
50
50
60
70
80
90
100 -2
Specific leaf weight (g m )
INDIVIDUAL PLANT TRAITS AT ANTHESIS Fig. 3. Relationships between crop yield and either (a) biomass partitioning to spike, or (b) specific leaf weight, measured at anthesis in individual plants grown in isolation. Bars indicate the SEM for each cultivar.
48
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
Specific leaf weight (g m-2 )
Spike partitioning (%)
CROP TRAITS AT ANTHESIS
30 (a) R2=0.47**
25
20
15 20
25
30
35
Spike partitioning (%)
40
70 (b) R2=0.38*
60
50
40 50
60
70
80
90
100 -2
Specific leaf weight (g m )
INDIVIDUAL PLANT TRAITS AT ANTHESIS Fig. 4. Relationship between traits measured in individual plants grown in isolation and the same traits measured in dense crops. The traits were: spike partitioning (a) and specific leaf weight (b) both at anthesis. Bars indicate the SEM for each cultivar in each of the two contrasting growing conditions. Determination coefficients of the relationships with their level of significance (**P < 0.01, *P < 0.05) are also shown in each panel.
anthesis, whilst crop yield was well related to nitrogen uptake and harvest index at maturity and specific leaf weight at anthesis, corroborating results in many different studies2 (e.g. Hamblin and Donald, 1974; Calderini et al., 1999; Alvaro et al., 2007; Foulkes et al., 2009; Rebetzke et al., 2011). In addition, we expectedly found no relationship between crop yield and yield of the isolated individual plants. This expectation was based on the well established fact that selection for yield in isolated plants is ineffective to breed for high-yielding cultivars (e.g. Bell, 1963; Donald, 1968). Thus, considering both the physiological bases of yield within either isolated plants or dense crops and the lack of relationship between yields in these two contrasting conditions, we can trust that the general picture produced by the cultivars chosen for this study is representative of situations in which breeders do normally work. In this study, instead of hypothesising with likely attributes of individual plants to be used as indicators of crop performance (e.g. Slafer, 2003; Reynolds et al., 2009b), we determined a large number of physiological attributes in individual plants and empirically tested the relationship between crop yield and them. This is the main reason why the number of tested genotypes had to be limited, None of the physiological traits measured in individual plants at maturity did relate well with crop yield. The lack of relationship between individual plant yield components and crop yield is in line with previous studies in which selecting in early populations for yield components did not result in improved crop yield (Donald, 1968; Knott, 1972). On the other hand, for traits such as harvest index and height of individual plants, there are previous studies in which these attributes in individual plants were found highly correlated to yield of the crops (Syme, 1972; Fischer and Kertesz, 1976). The reason for the apparently conflicting result is precisely the past success in breeding yield potential through increasing harvest index, while reducing plant height, particularly through
2 An apparent exception may be that yield was only slightly related with spike dry weight at anthesis in dense crops, whilst this relationship has been often rather strong in many comparisons of cultivars released at different eras (e.g. Calderini et al., 1999 and references quoted therein) or lines differing in semi-dwarfism (Flintham et al., 1997; Miralles and Slafer, 1995). However, the exception is only apparent because in several recent studies, in which the analysis was restricted to modern, well adapted, genotypes (which do not differ markedly in plant height) it has been found that yield differences were associated with either spike dry weight at anthesis or fruiting efficiency (the number of grains set per unit spike dry weight at anthesis), and that this efficiency may be as relevant as, or more relevant than, spike dry weight at anthesis in determining genotypic differences in grain number and yield (e.g. González et al., 2011b; Foulkes et al., 2011; Pedro et al., 2011).
the introgression of Rht genes (e.g. Youssefian et al., 1992; Miralles and Slafer, 1995; Flintham et al., 1997). However, that relationship frequently found in the past (with genotypes varying greatly in harvest index and plant height; Fischer and Kertesz, 1976) could not be expected in the present study. In our experiments all genotypes were modern lines with good agronomic performance, and therefore all having relatively high harvest indexes and plant heights within the optimum range, therefore not varying too much in these two attributes. Having selected these genotypes for the study is relevant as it does represent the most likely situation in realistic breeding elite populations. As we aimed to identify traits that may be conductive to further improving yield, we intentionally selected modern genotypes with good agronomic performance as actual cultivars already possess rather high harvest indexes (Calderini et al., 1999) and optimum plant height (Richards, 1992; Miralles and Slafer, 1995; Flintham et al., 1997). It would merely be an academic exercise to work with a heterogeneous population varying strongly in harvest index and plant height (without any doubt, strong negative relationships between height of isolated plant and crop yield would have been found if we would have used genotypes strongly varying in plant height, but these relationships would have meant virtually nothing to further raise yield potential in wheat respect to the best adapted modern genotypes). We must try identifying true alternative traits through which crop yields can be further improved (e.g. Foulkes et al., 2011; Reynolds et al., 2012). Despite that we tested a number of traits before maturity, at jointing and anthesis, none of the measured or calculated traits in isolated individual plants showed a clear-cut value to be considered a critical selection criterion in individual plants able to strongly determining crop yield. This exacerbates the difficulties in properly selecting in individual isolated plants, beyond discarding individual plants lacking “good agronomic type”, and emphasises the need of deepening in this sort of studies, instead of only building up knowledge based on results of comparisons of genotypes compared only in crop stands. The latter type of studies, which are the most common ones, are critical for a crop-physiological understanding of which traits determine crop yield (in dense crop conditions) but are ill-suited to soundly speculating on which traits might be valuable when selecting for in early generations. Having acknowledged unambiguously that none of the many traits studied in isolated individual plants could unequivocally be pointed as a definite selection criterion, it is worthwhile recognising that there were few traits of individual plants exhibiting some ability to predict crop yield. The most significant ones were
Biomass (g m -2 )
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
49
2000
(a)
(b)
R2 =0.30*
R2 =0.63***
1500 1000 500 0 20
25
30
35
40
0
2
4
6
8
10
6
8
10
6
8
10
6
8
10
Spike dry weight (g m -2 )
(c)
(d)
R2 =0.16 ns
R2 =0.28 ns
1000
500
0 20
25
30
35
40
0
2
4
25
(e)
(f)
R2 =0.56**
R2 =0.62***
20
Grain number (10 -3 m-2 )
CROP YIELD COMPONENTS
1500
15 10 5 0 20
25
30
35
40
0
2
4
Harvest Index
0.55
(g)
(h)
R2 =0.23 ns
R2 =0.09 ns
0.50 0.45 0.40 0.35 20
25
30
35
Spike partitioning (%)
40
0
2
4
Specific leaf weight (g m -2 )
INDIVIDUAL PLANT TRAITS AT ANTHESIS Fig. 5. Relationship between the main crop yield determinants and spike partitioning (left panels) or the specific leaf weight (right panels) at anthesis in individual plants grown in isolation. Crop yield determinants considered were biomass (a and b), spike dry weight (c and d), grain number per unit land area (e and f), and harvest index (g and h). Bars indicate the SEM for each cultivar. Determination coefficients of the relationships with their level of significance (**P < 0.01, *P < 0.05, ns P > 0.05) are also shown in each panel.
measured at anthesis and were related to either the gain in growth of either the plant (specific leaf weight) or the juvenile spike (spike partitioning). Both traits seem to be largely dense independent (Fig. 4), and may genuinely impact on grain yield. This might be related with the fact that both traits may represent allometric relationships, characterising the relative growth of a part in comparison with a whole (Reddy et al., 1998), and would be therefore more stable (as the probability of a ratio being affected by the resource availability is lower than that of growth being affected).
Specific leaf weight may be related to radiation use efficiency (Shearman et al., 2005). This is rather important in modern crops as radiation interception during the critical phase of stem elongation is normally maximised and the only way to increase biomass would then be through greater radiation use efficiency (Reynolds et al., 2007). Selection to increase biomass is essential to improve the performance as in modern cultivars harvest index is close to the theoretical maximum (Reynolds et al., 2009a). Spike partitioning at anthesis, may increase the number of grains (Miralles and Slafer, 2007; Fischer, 2011; Foulkes et al., 2011; González et al.,
50
A. Pedró et al. / Field Crops Research 138 (2012) 42–51
2011b). As yield of modern cultivars is commonly more sinkthan source-limited during grain filling (Acreche and Slafer, 2009; Reynolds et al., 2009a; Pedro et al., 2011), the number of grain must be increased to further increase yield (Slafer et al., 2005; Foulkes et al., 2011). In addition, an increase in post-anthesis sink strength may increase crop photosynthesis during grain filling (Reynolds et al., 2005; Acreche et al., 2009; Parry et al., 2011). Actually, in the few cases where the relationships between maximum leaf photosynthesis and the year of release of cultivars were positive (Fischer et al., 1998) the increased photosynthesis was associated with an increased demand from a larger sink in modern cultivars compared with the older counterparts. The fact that attributes of isolated individual plants related to radiation interception (e.g. leaf area at anthesis) were hardly important to influence crop yield is not actually surprising. Firstly these attributes are dependant on density (and a plant with a large potential to produce leaf area may not achieve that potential in crowed environments, like those of realistic crops). Secondly, because well managed modern wheat crops possess a maximum leaf area index higher than that which is critical to maximise radiation interception (Acreche et al., 2009), with the exception of agricultural systems with very short growing seasons (e.g. Nordic countries). Consequently, there may be little room for improvements in crop growth and yield through selecting for traits related to radiation interception. In conclusion, we tried to find out morpho-physiological traits measured or calculated at different stages of development in single spaced plants associated with crop yield. Two traits, spike partitioning and specific leaf weight at anthesis, which are denseindependent and may have implication in yield determination, were found positively correlated to crop yield and may be potentially useful selection criteria, if surrogates to determine them more easily become available or if markers could be identified so that molecular assisted selection would be possible. Acknowledgments We thank Jaume Gregori (DAAR, Generalitat de Catalunya, Spain) for general agronomic advice within Agramunt area, and Miloudi Nachit (ICARDA, Syria) for providing the seeds of Cham 1, Lahn and the RILs 2004, 2410, 2408 and 2517. This work was mainly supported by OPTIWHEAT, an INCO-Project of the European Union on “Improving the Yield Stability of Durum Wheat under Mediterranean Conditions” (EC Contract Number: INCO-CT-2006-015460); with partial additional support from a project funded by the Spanish Ministry of Science and Innovation on “Physiological bases of yield and quality of cereals” (AGL2006-07814/AGR). AP held a FPI scholarship from the Spanish Ministry of Science and Innovation. References Abeledo, L.G., Calderini, D.F., Slafer, G.A., 2003. Genetic improvement of barley yield potential and its physiological determinants in Argentina (1944–1998). Euphytica 130, 325–334. Acreche, M.M., Slafer, G.A., 2006. Grain weight response to increases in number of grains in wheat in a Mediterranean area. Field Crops Res. 98, 52–59. Acreche, M.M., Briceno-Felix, G., Martin Sanchez, J.A., Slafer, G.A., 2009. Radiation interception and use efficiency as affected by breeding in Mediterranean wheat. Field Crops Res. 110, 91–97. Acreche, M.M., Slafer, G.A., 2009. Grain weight, radiation interception and use efficiency as affected by sink-strength in Mediterranean wheats released from 1940 to 2005. Field Crops Res. 110, 98–105. Alvaro, F., Garcia del Moral, L.F., Royo, C., 2007. Usefulness of remote sensing for the assessment of growth traits in individual cereal plants grown in the field. Int. J. Remote Sens. 28, 2497–2512. Alvaro, F., Isidro, J., Villegas, D., Garcia del Moral, L.F., Royo, C., 2008. Breeding effects on grain filling, biomass partitioning, and remobilization in Mediterranean durum wheat. Agron. J. 100, 361–370. Araus, J.L., Slafer, G.A., Royo, C., Dolores Serret, M., 2008. Breeding for yield potential and stress adaptation in cereals. Crit. Rev. Plant Sci. 27, 377–412.
Austin, R.B., Ford, M.A., Morgan, C.L., 1989. Genetic-improvement in the yield of winter-wheat – a further evaluation. J. Agric. Sci. 112, 295–301. Bell, G.D.H., 1963. Breeding techniques. In: Anonymous Barley Genetics I. Pudoc, Wageningen, pp. 285–306. Calderini, D.F., Dreccer, M.F., Slafer, G.A., 1995. Genetic-improvement in wheat yield and associated traits – a reexamination of previous results and the latest trends. Plant Breed. 114, 108–112. Calderini, D.F., Slafer, G.A., 1998. Changes in yield and yield stability in wheat during the 20th century. Field Crops Res. 57, 335–347. Calderini, D.F., Reynolds, M.P., Slafer, G.A., 1999. Genetic gains in wheat yield and main physiological changes associated with them during the 20th century. In: Satorre, E.H., Slafer, G.A. (Eds.), Wheat: Ecology and Physiology of Yield Determination. Food Product Press, New York, pp. 351–377. Calderini, D.F., Slafer, G.A., 1999. Has yield stability changed with genetic improvement of wheat yield? Euphytica 107, 51–59. Cossani, C.M., Savin, R., Slafer, G.A., 2007. Contrasting performance of barley and wheat in a wide range of conditions in Mediterranean Catalonia (Spain). Ann. Appl. Biol. 151, 167–173. De Vita, P., Nicosia, O.L.D., Nigro, F., Platani, C., Riefolo, C., Di Fonzo, N., Cattivelli, L., 2007. Breeding progress in morpho-physiological, agronomical and qualitative traits of durum wheat cultivars released in Italy during the 20th century. Eur. J. Agron. 26, 39–53. Donald, C.M., 1968. Breeding of crop ideotypes. Euphytica 17, 385–403. Donald, C.M., Hamblin, J., 1976. Biological yield and harvest index of cereals as agronomic and plant breeding criteria. Adv. Agron. 28, 361–405. FAO, 1990. F.A.O. UNESCO soil map of the world: revised legend. World Soil Resources Report 60. Fischer, R.A., Kertesz, Z., 1976. Harvest index in spaced populations and grain weight in microplots as indicators of yielding ability in spring wheat. Crop Sci. 16, 55–59. Fischer, R.A., 1985. Number of kernels in wheat crops and the influence of solarradiation and temperature. J. Agric. Sci. 105, 447–461. Fischer, R.A., Rees, D., Sayre, K.D., Lu, Z.M., Condon, A.G., Saavedra, A.L., 1998. Wheat yield progress associated with higher stomatal conductance and photosynthetic rate, and cooler canopies. Crop Sci. 38, 1467–1475. Fischer, R.A., 2007. Understanding the physiological basis of yield potential in wheat. J. Agric. Sci. 145, 99–113. Fischer, R.A., Edmeades, G.O., 2010. Breeding and cereal yield progress. Crop Sci. 50, S85–S98. Fischer, R.A., 2011. Wheat physiology: a review of recent developments. Crop Pasture Sci. 62, 95–114. Flintham, J.E., Borner, A., Worland, A.J., Gale, M.D., 1997. Optimizing wheat grain yield: effects of Rht (gibberellin-insensitive) dwarfing genes. J. Agric. Sci. 128, 11–25. Foulkes, M.J., Hawkesford, M.J., Barraclough, P.B., Holdsworth, M.J., Kerr, S., Kightley, S., Shewry, P.R., 2009. Identifying traits to improve the nitrogen economy of wheat: recent advances and future prospects. Field Crops Res. 114, 329–342. Foulkes, M.J., Slafer, G.A., Davies, W.J., Berry, P.M., Sylvester-Bradley, R., Martre, P., Calderini, D.F., Griffiths, S., Reynolds, M.P., 2011. Raising yield potential of wheat. III. Optimizing partitioning to grain while maintaining lodging resistance. J. Exp. Bot. 62, 469–486. Fowler, C.W., Rasmusson, D.C., 1969. Leaf area relationships and inheritance in barley. Crop Sci. 9, 729–731. Giunta, F., Motzo, R., Pruneddu, G., 2007. Trends since 1900 in the yield potential of Italian-bred durum wheat cultivars. Eur. J. Agron. 27, 12–24. González, F.G., Slafer, G.A., Miralles, D.J., 2003. Grain and floret number in response to photoperiod during stem elongation in fully and slightly vernalized wheats. Field Crops Res. 81, 17–27. González, F.G., Slafer, G.A., Miralles, D.J., 2005. Photoperiod during stem elongation in wheat: is its impact on fertile floret and grain number determination similar to that of radiation? Funct. Plant Biol. 32, 181–188. González, F.G., Miralles, D.J., Slafer, G.A., 2011a. Wheat floret survival as related to pre-anthesis spike growth. J. Exp. Bot. 62, 4889–4901. González, F.G., Terrile, I.J., Falcon, M.O., 2011b. Spike fertility and duration of stem elongation as promising traits to improve potential grain number (and yield): variation in modern Argentinean wheats. Crop Sci. 51, 1693–1702, http://dx.doi.org/10.2135/cropsci2010.08.0447. Hamblin, J., Donald, C.M., 1974. Relationships between plant form, competitive ability and grain yield in a barley cross. Euphytica 23, 535–542. Hsu, P., Walton, P.D., 1970. Inheritance of morphological and agronomic characters in spring wheat. Euphytica 19, 54–60. Kirby, E.J.M., 1988. Analysis of leaf, stem and ear growth in wheat from terminal spikelet stage to anthesis. Field Crops Res. 18, 127–140. Knott, D.R., 1972. Effects of selection for F2 plant yield on subsequent generations in wheat. Can. J. Plant Sci. 52, 721–726. Marti, J., Bort, J., Slafer, G.A., Araus, J.L., 2007. Can wheat yield be assessed by early measurements of normalized difference vegetation index? Ann. Appl. Biol. 150, 253–257. Miralles, D.J., Slafer, G.A., 1995. Yield, biomass and yield components in dwarf, semidwarf and tall isogenic lines of spring wheat under recommended and late sowing dates. Plant Breed. 114, 392–396. Miralles, D.J., Slafer, G.A., 2007. Sink limitations to yield in wheat: how could it be reduced? J. Agric. Sci. 145, 139–149. Nachit, M.M., Elouafi, I., Pagnotta, M.A., El Saleh, A., Iacono, E., Labhilili, M., Asbati, A., Azrak, M., Hazzam, H., Benscher, D., Khairallah, M., Ribaut, J.M., Tanzarella, O.A., Porceddu, E., Sorrells, M.E., 2001. Molecular linkage map for an
A. Pedró et al. / Field Crops Research 138 (2012) 42–51 intraspecific recombinant inbred population of durum wheat (Triticum turgidum L. var. durum). Theor. Appl. Genet. 102, 177–186. Park, S.J., Reinbergs, E., Song, L.S.P., 1977. Grain-yield and its components in spring barley under row and hill plot conditions. Euphytica 26, 521–526. Parry, M.A.J., Reynolds, M., Salvucci, M.E., Raines, C., Andralojc, P.J., Zhu, X., Price, G.D., Condon, A.G., Furbank, R.T., 2011. Raising yield potential of wheat. II. Increasing photosynthetic capacity and efficiency. J. Exp. Bot. 62, 453–467. Pedro, A., Savin, R., Habash, D.Z., Slafer, G.A., 2011. Physiological attributes associated with yield and stability in selected lines of a durum wheat population. Euphytica 180, 195–208. Pedro, A., Savin, R., Parry, M.A.J., Slafer, G.A., 2012. Selection for high grain number per unit stem length through four generations from mutants in a durum wheat population to increase yields of individual plants and crops. Field Crops Res. 129, 59–70. Rebetzke, G.J., Ellis, M.H., Bonnett, D.G., Condon, A.G., Falk, D., Richards, R.A., 2011. The Rht13 dwarfing gene reduces peduncle length and plant height to increase grain number and yield of wheat. Field Crops Res. 124, 323–331. Reddy, V.R., Pachepsky, Y.A., Whisler, F.D., 1998. Allometric relationships in fieldgrown soybean. Ann. Bot. 82, 125–131. Rekika, D., Nachit, M.M., Araus, J.L., Monneveux, P., 1998. Effects of water deficit on photosynthetic rate and osmotic adjustment in tetraploid wheats. Photosynthetica 35, 129–138. Reynolds, M., Calderini, D., Condon, A., Vargas, M., 2007. Association of source/sink traits with yield, biomass and radiation use efficiency among random sister lines from three wheat crosses in a high-yield environment. J. Agric. Sci. 145, 3–16. Reynolds, M., Foulkes, M.J., Slafer, G.A., Berry, P., Parry, M.A.J., Snape, J.W., Angus, W.J., 2009a. Raising yield potential in wheat. J. Exp. Bot. 60, 1899–1918. Reynolds, M., Manes, Y., Izanloo, A., Langridge, P., 2009b. Phenotyping approaches for physiological breeding and gene discovery in wheat. Ann. Appl. Biol. 155, 309–320. Reynolds, M., Foulkes, J., Furbank, R., Griffiths, S., King, J., Murchie, E., Parry, M.J., Slafer, G.A., 2012. Achieving yield gains in wheat. Plant Cell Envriron. 35, 1799–1823. Reynolds, M.P., Pellegrineschi, A., Skovmand, B., 2005. Sink-limitation to yield and biomass: a summary of some investigations in spring wheat. Ann. Appl. Biol. 146, 39–49.
51
Richards, R.A., 1992. The effect of dwarfing genes in spring wheat in dry environments. 1. Agronomic characteristics. Aust. J. Agric. Res. 43, 517–527. Royo, C., Alvaro, F., Martos, V., Ramdani, A., Isidro, J., Villegas, D., Garcia del Moral, L.F., 2007. Genetic changes in durum wheat yield components and associated traits in Italian and Spanish varieties during the 20th century. Euphytica 155, 259–270. Sadras, V.O., 2007. Evolutionary aspects of the trade-off between seed size and number in crops. Field Crops Res. 100, 125–138. Sadras, V.O., Slafer, G.A., 2012. Environmental modulation of yield components in cereals: heritabilities reveal a hierarchy of phenotypic plasticities. Field Crops Res. 127, 215–224. Shearman, V.J., Sylvester-Bradley, R., Scott, R.K., Foulkes, M.J., 2005. Physiological processes associated with wheat yield progress in the UK. Crop Sci. 45, 175–185. Siddique, K.H.M., Kirby, E.J.M., Perry, M.W., 1989. Ear stem ratio in old and modern wheat-varieties – relationship with improvement in number of grains per ear and yield. Field Crops Res. 21, 59–78. Slafer, G.A., Andrade, F.H., 1991. Changes in physiological attributes of the dry-matter economy of bread wheat (Triticum aestivum) through geneticimprovement of grain-yield potential at different regions of the world – a review. Euphytica 58, 37–49. Slafer, G.A., Andrade, F.H., 1993. Physiological attributes related to the generation of grain-yield in bread wheat cultivars released at different eras. Field Crops Res. 31, 351–367. Slafer, G.A., 2003. Genetic basis of yield as viewed from a crop physiologist’s perspective. Ann. Appl. Biol. 142, 117–128. Slafer, G.A., Araus, J.L., Royo, C., Garcia del Moral, L.F., 2005. Promising ecophysiological traits for genetic improvement of cereal yields in Mediterranean environments. Ann. Appl. Biol. 146, 61–70. Syme, J.R., 1972. Single-plant characters as a measure of field plot performance of wheat cultivars. Aust. J. Agric. Res. 23, 753–760. Youssefian, S., Kirby, E.J.M., Gale, M.D., 1992. Pleiotropic effects of the Ga-insensitive Rht dwarfing genes in wheat. Effects on development of the ear, stem and leaves. Field Crops Res. 28, 179–190. Zadoks, J.C., Chang, T.T., Konzak, C.F., 1974. Decimal code for growth stages of cereals. Weed Res. 14, 415–421.