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Relationship between population competitive intensity and yield in maize cultivars
Journal of Integrative Agriculture 2017, 16(6): 1312–1321 Available online at www.sciencedirect.com
ScienceDirect
RESEARCH ARTICLE
Relationship between population competitive intensity and yield in maize cultivars ZHAI Li-chao1, 2*, XIE Rui-zhi1*, LI Shao-kun1, FAN Pan-pan1 1
Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing 100081, P.R.China
2
Center for Agricultural Resources Research, Institute of Genetics and Development Biology, Chinese Academy of Sciences, Shijiazhuang 050021, P.R.China
Abstract Competition is a common phenomenon in agriculture production. Research on the relationship between competitive ability and crop yield is extensive, but the results have been inconsistent. Few studies have focused on the relationship between population competitive intensity and yield of maize (Zea mays L.) cultivars. The main objective of this study was to determine if a consistent relationship exists between maize yield and competitive ability. A two-year field experiment was conducted, employing a de Wit replacement series design. When two maize cultivars were grown in a mixture, yield was reduced for the modern cultivar and increased for the older cultivar. In each replacement series, per plant level yield of each cultivar, and population level yield of the mixture, decreased with increasing proportion of the older cultivar. Competitive ratio (CR) reflected differences in competitive ability of the three maize cultivars. In each replacement series, population competition pressure (PCP) increased with increasing proportion of the older cultivar, indicating that the older cultivar was a strong competitor. Biomass yield, grain yield, harvest index, thousand-kernel weight, and kernel number per plant, were negatively correlated with PCP. Our results demonstrated that inter-cultivar competition affects maize productivity, and increasing PCP will decrease translocation of assimilates to grain and, ultimately, reduce yield. Therefore, there is a negative correlation between population competitive intensity and yield performance in maize, breeders should develop a communal ideotype that would not perform well in competition in future. Keywords: maize, competition, competitive ability, population competitive pressure, yield
1. Introduction
Received 20 July, 2016 Accepted 27 November, 2016 Correspondence LI Shao-kun, Tel/Fax: +86-10-82108891, E-mail: [email protected] * These authors contributed equally to this study. © 2017, CAAS. All rights reserved. Published by Elsevier Ltd. doi: 10.1016/S2095-3119(16)61541-1
Competition is a common phenomenon in nature. It is also an important factor in agriculture production. The effects of competition are widespread, and easily observed in crop mixtures. Competition is also known to affect recruitment, growth and reproduction of crop plants (Keddy 2012). Numerous studies have focused on the relationship between competitive ability and crop grain yield, but the results have been inconsistent. Some studies have demonstrated
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an inconsistent relationship between the yield of a cultivar in a mixture and its yield in monoculture (Christian et al. 1941; Sahai 1955). Dong et al. (2007) and Du et al. (2011) also found that the competitive ability of wheat (Triticum aestivum L.) cultivars is not necessarily correlated with its grain yield. However, Worthington and Reberg-Horton (2013) suggested that competitive cereal crops should be bred for weed suppression. Crop cultivars with strong weed competitiveness and high yield potential could be compatible (Garrity et al. 1992; Ni et al. 2000; Fischer et al. 2001; Gibson et al. 2003; Zhao et al. 2006). These results suggest that crop cultivars with strong competitive ability could also produce high yield under a weedy conditions. In general, crops with higher competitive ability perform better in response to weed suppression (Jordan 1993). There is, however, a growing body of evidence indicating that crop yield is negatively correlated with its competitive ability (Fasoula 1990; Reynold et al. 1994; Lemerle et al. 2001; Murphy et al. 2008; Reid et al. 2009; Song et al. 2009; Fang et al. 2011). Snaydon (1984) and Zhang et al. (1999) reported a negative correlation between competitive ability and productive performance of wheat cultivars. Lemerle (2001) found that increased wheat competitive ability might be associated with decreased crop yield, and a study of 63 spring wheat cultivars showed that increased grain yield caused slight reductions in weed suppression over the past 150 years (Murphy et al. 2008). Vandeleur and Gill (2004) found that modern semi-dwarf wheat cultivars have low tolerance to weed competition and suffer greater yield losses from weed competition than older and lower yield potential cultivars. These studies above suggested that modern wheat cultivars with high yield potential are weak competitors. They reported a negative relationship between competitive ability and crop yield. In order to achieve a high yield, Donald (1968) agrued that plants in the crop community will compete with each other to a minimum degree, and suggested that a successful crop ideotype will be a weak competitor, relative to its mass. Crop production is a process of population, the research on the relationship between competitive ability and yield should also be conducted at the populaiton level. However, all previous people measured the competitive ability of crop cultivars at individual level in inter-cultivar competition, but not at population level. Since the competitive ability of crop cultivars is measured according to competitive indices that are based on crop biomass yield or grain yield, our hypothesis is that competition may change the allocation of photosynthate, and a higher population competitive intensity would reduce crop yield. The main objectives of this study were to (1) identify the mixing effects of maize cultivars, and (2) to determine whether there is a relationship between population competitive intensity and yield, if so, how to elucidate that relationship.
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2. Materials and method 2.1. Experiment site Field experiments were conducted in two consecutive years: 7 May to 30 September, 2013 (Year 1) and 25 April to 30 September, 2014 (Year 2) at the Gongzhuling Experimental Station of the Chinese Academy of Agricultural Sciences (43°11´–44°9´N, 124°02´–125°18´E), which is located in a humid, continental monsoon climate in Gongzhuling County of Jilin Province, China. Spring maize is usually grown from late April to late September, under rainfed conditions and with ridge planting. The mean annual air temperature at the experimental station is 5.6°C, average annual precipitation is 594.8 mm, and the annual frost-free period is approximately 144 d. The soil type is chernozem, with 26.3 g kg–1 organic matter, 1.5 g kg–1 total N, 124.90 mg kg–1 available N, 28.52 mg kg–1 available P, and 184.47 mg kg–1 available K in the upper soil profile. The rainfall during the maize growing period was 553.9 mm in 2013 and 438.1 mm in 2014. The accumulated temperatures (≥10°C) were 3 188.5 in 2013 and 3 056.4 in 2014.
2.2. Plant materials Three maize cultivars, released in different eras in China, were used for this study. Zhongdan 2 (ZD2) is a relative old maize cultivar very widely grown in northern China in the 1970s. Yedan 13 (YD13) was grown widely in China in the 1990s. Zhongdan 909 (ZD909), a modern maize cultivar released recently, is currently widely grown in China. All three cultivars were the most popular cultivars in their respective periods. The three maize cultivars differed in plant traits (Table 1), and were easily distinguished when grown in a mixture.
2.3. Experimental design The experimental design was a de Wit replacement series design (de Wit 1960), which consists of a set of pure and mixed populations in which the combined density of the components is held constant. The proportion of each component ranges from 0 to 1. In this study, all cultivar pairs (YD13:ZD909, ZD2:ZD909, ZD2:YD13) were combined in the ratios of 0:6, 1:5, 2:4, 3:3, 4:2, 5:1, and 6:0, respectively. The 2:4, 3:3 and 4:2 treatments were grown at 1:2, 1:1 and 2:1 ratios, respectively. Seeds were sown manually at a plant density of 6.7 plants m–2 and row spacing was 65 cm, with a blank row between plots (Fig. 1). Plots were 6 m×7 m and there were three replicates. Manual sowing occurred on 7 May 2013 and 25 April 2014, at a rate of two seeds per hill, and plots were thinned to one plant per hill at the
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Table 1 Parents, time of release and major characteristics of the three maize cultivars Zhongdan 2 (ZD2), Yedan 13 (YD13) and Zhongdan 909 (ZD909)
Maize cultivar YD13 Ye478♀×Dan340♂ The 1990s Semi-compact 258±4.0 115±2.2 0.917±0.027 28.8±0.8 46.4±1.7 130
ZD2 Mo17♀×Zi330♂ The 1970s Flat-type 300±4.3 131±3.7 0.810±0.042 31.9±0.6 43.5±2.4 128
Parents Time of release Morphological type Plant height (cm) Ear height (cm) Leaf area (m2) Average leaf angle (°) Leaf orientation value (°) Growth period (d)
ZD909 Zheng588♀×HD586♂ The 2010s Compact 263±2.4 117±2.9 0.862±0.01 21.9±0.5 57.3±2.7 126
Values are means±SE.
0:6
1:5
2:4
3:3
4:2
5:1
6:0
Fig. 1 Schematic diagram of planting pattern in the experiment design. White circles ( ) and black five-pointed stars (★) represent the two cultivars of each combination.
V3 (the 3rd leaf) stage. Weeds were controlled manually to eliminate negative effects from weed competition. Chemical fertilizers of N, P and K were applied at 150, 45 and 45 kg ha–1, respectively. N was topdressed at the V6 (the 6th leaf) and V12 (the 12th leaf) stages at 75 kg ha–1. All treatments were imposed under rainfed conditions.
2.4. Plant sampling In each replacement series treatment, three plants of each cultivar, within 3 m2 of the middle of each plot, were selected randomly and manually cut at ground level at physiological maturity. Plants were separated into stems, leaves, sheaths, tassels, and ears, and oven-dried to record dry matter yield. In addition, at harvest, 20 plants of each maize cultivar were harvested to record single-plant grain yield. Population-level yields were calculated from single-plant yield data. Harvest index (HI) was calculated as follows: Grain yield (1) HI= DMA Where, DMA is dry matter accumulation.
2.5. Competitive indices Competitive ratio (CR) CR is a commonly used indicator
to assess inter-specific competition between crop species in intercropping systems (Willey and Rao 1980). It measures the ability of one crop to compete with another crop (Dhima et al. 2007; Zhang et al. 2011). In the present study, CR was used as a measure of inter-cultivar competition and was calculated as follows: Yij /Yii (2) CRij = Yji /Yjj Where, CRij is the CR of cultivar i relative to cultivar j in a given mixture, Yii and Yjj are the average single plant biomass yields of cultivars i and j, respectively, in monoculture, and Yij and Yji are the average single plant biomass yields of cultivars i and j, respectively, in the mixture. If CRij is greater than 1.0, the competitive ability of cultivar i is superior to cultivar j in mixed cropping; otherwise, cultivar j has greater competitiveness. CRij is inversely related to CRji, so only one value (CRij) is presented here. Population competition pressure (PCP) To better illustrate the population competitive ability of a replacement mixture, we proposed a new index, PCP. We calculated PCP by using the CRs of the component maize cultivars in a replacement series, as follow: PCP =D×( pCRij+qCRji) (3) p+q=1 Where, D is population plant density (6.7 plants m–2), CRij
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and CRji are the CRs of cultivars i and j, respectively, in a
3.2. Harvest index (HI)
and j, respectively, in a given mixture. The higher the PCP
In each replacement series, the single plant HI of each cultivar and population-level grain yield decreased as the proportion of the older cultivar increased (Table 2). In each replacement series, the component cultivars differed in HI, which was always lower in the older cultivars in monoculture and in mixture. This trend was consistent across years, but there were differences in HI across year.
given mixture, and p and q are the proportions of cultivars i
2.6. Statistical analysis One-way analysis of variance was computed for each year (SPSS 19.0). Graphs were plotted either in SigmaPlot 12.5 or Excel 2010. Treatment means were compared by computing the least significant differences to identify significant differences at the 0.05 probability level. Linear regression analysis was used to examine patterns in yield performance and PCP. Pearson’s correlation coefficients were computed for all combinations of biomass yield, grain yield, HI and PCP.
3. Results 3.1. Single plant dry matter accumulation (DMA) and grain yield In each replacement series, the single plant DMA and grain yield of both component cultivars decreased significantly with increasing proportion of the older cultivars (Fig. 2). Variation in single plant DMA was found in different replacement series for the same cultivar. In addition, differences were observed for each cultivar across years. The reduction from the maximum to minimum single plant DMA varied between 61.3 and 77.1 g for ZD909 in the replacement series. Similarly, the reduction varied between 31.9 and 81.7 g for YD13, and between 53.5 and 81.5 g for ZD2 in the replacement series. The reduction of grain yield for ZD909 varied between 22.4 and 24.0%, the reduction varied between 20.7 and 24.6% for YD13, and it varied between 28.8 and 29.3% for ZD2. The older cultivar ZD2 was suceptible to inter-cultivar competition.
440 420 400 380 360 340 320 300
B 2013 ZD909 2013 YD13 2014 ZD909 2014 YD13
0:6 1:5 2:4 3:3 4:2 5:1 6:0 YD13:ZD909
Single plant dry matter weight (g per plant)
Single plant dry matter weight (g per plant)
A
450 400
3.3. Competitive ratio (CR) CR measures the competitive ability of one crop relative to another in a mixture or an intercropping system. When CR of one crop is greater than 1, the competitive ability of the crop is higher than the other in intercropping. In each replacement series, the CR value was always greater than 1 for different mixed ratios, and no significant differences were observed among the mixed ratios (Table 3). The CR values were also relatively stable across years for each replacement series. Moreover, the CR of ZD2 relative to ZD909 was higher than the CR of ZD2 relative to YD13, and the CR of ZD2 relative to YD13 was higher than the CR of YD13 relative to ZD909. These results indicate that ZD2 was more competitive than ZD909 and YD13, and YD13 was more competitive than ZD909. These results were consistent across 2013 and 2014.
3.4. Population competitive pressure (PCP) To illustrate the competitive ability of populations, we proposed the index PCP, which could reflect the severity of competition of mixed crop populations. PCP was calculated from the CR values of the component cultivars in a mixture. In each replacement series, PCP increased with increasing proportion of older cultivars (Fig. 3). PCP varied across years, but the trend across replacement series was consistent for the two years. These results indirectly suggest that 2013 ZD909 2013 ZD2 2014 ZD909 2014 ZD2
350 300 250 200
0:6 1:5 2:4 3:3 4:2 5:1 6:0 ZD2:ZD909
C Single plant dry matter weight (g per plant)
value, the greater the population competition pressure.
380 360 340 320 300 280 260 240 220
2013 YD13 2013 ZD2 2014 YD13 2014 ZD2
0:6 1:5 2:4 3:3 4:2 5:1 6:0 ZD2:YD13
Fig. 2 Single plant biomass yield and grain yield of maize cultivars in different replacement series in 2013 and 2014. YD13, Yedan 13; ZD909, Zhongdan 909; ZD2, Zhongdan 2. Bars mean SE.
Mixed cropping patterns are the ratios of two cultivars mixed in the cropping system (YD13:ZD909, ZD2:ZD909 and ZD2:YD13). The ratios 0:6 and 6:0 indicate monoculture of each cultivar. Different letters in the same column within each year indicate significant differences (P<0.05). Values are means±SE.
1)
0.481±0.005 a 0.478±0.014 a 0.455±0.021 a 0.438±0.055 a 0.435±0.023 a 0.429±0.001 a 0.559±0.006 a 0.554±0.008 a 0.543±0.007 a 0.540±0.005 a 0.521±0.005 b 0.506±0.004 b 0.541±0.006 a 0.518±0.008 ab 0.506±0.004 b 0.499±0.007 b 0.494±0.012 b 0.492±0.009 b 0.548±0.009 a 0.549±0.003 a 0.541±0.014 a 0.532±0.002 a 0.524±0.011 ab 0.501±0.009 b 2014
2013
Mixed cropping pattern1) 0:6 1:5 2:4 3:3 4:2 5:1 6:0 0:6 1:5 2:4 3:3 4:2 5:1 6:0
ZD909 0.548±0.003 a 0.544±0.002 a 0.545±0.001 a 0.540±0.004 b 0.528±0.001 c 0.515±0.002 d
YD13:ZD909 YD13
0.534±0.002 a 0.511±0.002 ab 0.501±0.004 bc 0.498±0.003 cd 0.487±0.002 de 0.480±0.007 e
Population 0.548±0.003 a 0.543±0.001 ab 0.535±0.001 b 0.523±0.003 c 0.509±0.002 d 0.492±0.002 e 0.480±0.007 f 0.548±0.009 a 0.547±0.002 a 0.533±0.012 ab 0.519±0.003 bc 0.507±0.007 bc 0.495±0.011 c 0.492±0.009 c
ZD909 0.547±0.005 a 0.540±0.003 ab 0.535±0.009 ab 0.528±0.005 ab 0.523±0.007 b 0.523±0.004 b
ZD2:ZD909 ZD2
0.452±0.006 a 0.428±0.004 b 0.421±0.006 bc 0.408±0.009 cd 0.406±0.005 cd 0.392±0.004 d
Population 0.547±0.005 a 0.534±0.003 b 0.511±0.004 c 0.493±0.002 d 0.461±0.004 e 0.438±0.004 f 0.392±0.004 g 0.559±0.006 a 0.543±0.007 ab 0.523±0.003 b 0.500±0.012 c 0.477±0.006 d 0.445±0.007 ef 0.429±0.001 f
YD13 0.492±0.004 a 0.488±0.007a b 0.490±0.004 ab 0.484±0.006 ab 0.473±0.008 bc 0.465±0.002 c
YD13:ZD2 ZD2
Population 0.492±0.004 a 0.456±0.004 a 0.485±0.006 ab 0.438±0.006 b 0.476±0.001 b 0.420±0.001 c 0.463±0.00 6c 0.408±0.001 cd 0.449±0.003 d 0.403±0.006 d 0.432±0.004 e 0.403±0.005 d 0.403±0.005 f 0.512±0.003 a 0.512±0.003 a 0.505±0.004 ab 0.496±0.005 a 0.504±0.004 ab 0.497±0.004 abc 0.497±0.003 a 0.497±0.004 bc 0.481±0.003 bc 0.478±0.011 ab 0.479±0.004 cd 0.473±0.004 c 0.466±0.006 b 0.468±0.003 de 0.471±0.020 c 0.455±0.011 bc 0.457±0.012 ef 0.439±0.007 c 0.439±0.007 f
ZHAI Li-chao et al. Journal of Integrative Agriculture 2017, 16(6): 1312–1321
Year
Table 2 Harvest index of Zhongdan909 (ZD909), Yedan 13 (YD13), and Zhongdan 2 (ZD2) in three different mixed cropping combinations (YD13:ZD909, ZD2:ZD909 and ZD2:YD13)
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the older maize cultivar is a strong competitor.
3.5. The relationship between yield and population competitive pressure Maize yield was highly correlated with PCP. A linear relationship existed between maize population-level biomass yield, grain yield, HI and PCP. In each replacement series, the population-level biomass yield, grain yield and HI were negatively correlated with PCP, and the correlation coefficients were significant (P<0.05) or highly significant (P<0.01; Fig. 4). Although a significant year effect was observed for each replacement mixture, the variation was consistent across 2013 and 2014.
3.6. The relationship between yield components and population competitive pressure Kernel weight and kernel number are important components of maize yield. In each replacement series, both thousand kernel weight and kernel number per plant of each cultivar were slightly reduced with increasing PCP (Fig. 5), and they were negatively correlated. However, the correlation coefficients were not significant in most cases. In addition, in each replacement series, cultivars differed in thousand-kernel weight and kernel number. They also varied across years.
4. Discussion Inter-specific competition plays an important role in determining crop yield in intercropping systems (Li et al. 2001; Zhang et al. 2007). Similarly, inter-cultivar competition has a significant effect on yield (Treder et al. 2008; Song et al. 2009, 2010; Fang et al. 2011; Lithourgidis et al. 2011). When crop cultivars are planted together, both negative and positive interactions can occur simultaneously (Callaway and Walker 1997; Mariotti et al. 2009). In the present study, when two maize cultivars released in different eras were grown in a mixture, yield of the modern cultivar decreased, and increased for the older cultivar. In each replacement series, the individual- and population-level biomass yield and grain yield were significantly reduced with increasing proportion of the older cultivar. Fig. 2 indicated that the older maize cultivar benefitted from the inter-cultivar competition in terms of above-ground DMA and grain yield. The modern cultivar experienced significantly reduced growth in mixtures, as compared to monoculture. These results were consistent with earlier reports on wheat cultivars (Song et al. 2009; Fang et al. 2011). Our previous studies also confirmed that maize grain yield decreased with an increasing proportion of the stronger competitor (Zhai et al. 2015, 2016). Under the same population density, crop PCP was closely
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Table 3 Competitive ratio of Yedan 13 (YD13):Zhongdan 909 (ZD909), Zhongdan 2 (ZD2):ZD909, and ZD2:YD13, for varying mixed ratios Mixed cropping pattern YD13:ZD909 ZD2:ZD909 ZD2:YD13 YD13:ZD909 ZD2:ZD909 ZD2:YD13
Year 2013
2014
1:5 1.224±0.036 a 1.415±0.016 a 1.312±0.017 a 1.183±0.022 a 1.330±0.029 a 1.247±0.056 a
2:4 1.197±0.011 a 1.367±0.050 ab 1.293±0.002 a 1.216±0.003 a 1.334±0.054 a 1.248±0.029 a
Mixed ratio 3:3 1.184±0.017 a 1.362±0.018 ab 1.267±0.007 ab 1.191±0.021 a 1.361±0.073 a 1.264±0.024 a
4:2 1.181±0.013 a 1.362±0.028 ab 1.254±0.007 ab 1.222±0.040 a 1.340±0.031 a 1.283±0.082 a
5:1 1.200±0.010 a 1.281±0.008 b 1.229±0.033 b 1.228±0.062 a 1.361±0.057 a 1.300±0.027 a
Average 1.197 1.357 1.271 1.208 1.345 1.268
Different letters in the same column within each year indicate significant differences (P<0.05). Values are means±SE.
B
2013 2014
8 7 6 5 4
1:5
2:4 3:3 4:2 YD13:ZD909
5:1
9
C
2013 2014
Populaiton competition pressure
9
Populaiton competition pressure
Populaiton competition pressure
A
8 7 6 5 4
1:5
2:4 3:3 4:2 ZD2:ZD909
5:1
9
2013 2014
8 7 6 5 4
1:5
2:4 3:3 4:2 ZD2:YD13
5:1
Fig. 3 Changes of population competition pressure of different replacement series. YD13, Yedan 13; ZD909, Zhongdan 909; ZD2, Zhongdan 2.
related to individual plant competitive ability. The stronger the competitive ability of individual plant, the greater the PCP is. In the present study, in each replacement series, PCP increased with an increasing proportion of the older maize cultivar (Fig. 4). Through related analysis, population level biomass yield, HI, grain yield, thousand kernel weight and kernel number per plant were reduced with the increasing PCP (Fig. 5). Du et al. (2011) and Dong et al. (2007) reported that there is no clear relationship between competitive ability and grain yield in wheat cultivars. It has been shown that crop cultivars with strong weed suppression (i.e., a strong competitive ability against weeds) could have high yield potential (Hucl 1998; Gibson et al. 2003; Zhao et al. 2006). These results are different from our findings. However, a growing body of research evidence suggests that crop populations with weak individual competitive ability produce more grain when population density is constant (Reynolds et al. 1994; Vandeleur and Gill 2004; Murphy et al. 2008; Song et al. 2009; Fang et al. 2011; Zhai et al. 2015). Donald (1968, 1981) argued that, to increase yield potential of annual crops, breeders must develop a “communal” ideotype that would not perform well in competition. In a crop population consisting of plants that are weak competitors, PCP is low and the individual plants tend to allocate more resources to seeds. However, when crop populations primarily consist
of strong competitors, more resources will be allocated to resource-foraging organs (e.g., root, stems and leaves) to increase competitive ability, but not to reproductive organs. Therefore, a crop to be high yielding the individual plants making it up should be weak competitors, breeders should develop a communal ideotype that would not perform well in competition in future. HI is a key determinant of maize yield (Echarte and Andrade 2003), as it reflects the partitioning of photosynthate. Evans (1981) proposed that cultivars with high grain yield are weak competitors, due to the increased allocation of photosynthate to the ear and grain filling rather than to the leaves. The competitive ability of crop cultivars might be associated with HI. Donald (1968) argued that competitive ability or partitioning to organs, such as stems and leaves, could be sacrificed to some degree for increased reproductive allocation. In our results, in each replacement series, plant-level and population-level HI decreased with increasing proportions of the older maize cultivar (Table 2), illustrating that competition reduces the partitioning to grain, which reduces grain yield. According to Qin et al. (2012, 2013), the process of artificial selection in breeding is actully the adjustment of allometric growth in above-ground and below-ground, they indicated that domestication has resulted in an increase in an increased biomass allocation in shoot compared to root biomass allocation, this may be the main
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26 25 24 2013: y=–3.8776x+52.45 R=0.9976 2014: y=–1.4638x+33.997 R=0.9493*
***
B
28
Population biomass yield (t ha–1)
27
1
26
8.0
24 23 22 21 20
2013: y=–2.7669x+42.396 R=0.9810**
19
2014: y=–1.6986x+33.845 R=0.9759**
24
5.5
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
2014 ZD2:YD13
21 20 19 18
2013: y=–2.0934x+34.378 R=0.9858** 2014: y=–1.8666x+33.418 R=0.9968**
17 5.5
15 14 2013: y=–3.2739x+38.086 R=0.9977
13 12 5.5
9.0
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
0.51 2013: y=–0.0306x+0.7282 R=0.9889** 2014: y=–0.0297x+0.7243 R=0.9935**
0.48 5.5
8.0
6.0 6.5 7.0 7.5 Population competition pressure
0.56
2 2013 ZD2:ZD909
0.54
2014 ZD2:ZD909
0.52
14 13 12
8.0
3 2013 ZD2:ZD909 2014 ZD2:ZD909
0.50 0.48 0.46
11 10 2013: y=–2.5851x+30.929 R=0.9913 2014: y=–1.8944x+26.038 R=0.9918** 9 5.0 5.5 6.0 6.5 7.0 7.5 8.0 Population competition pressure
0.44 8.5
9.0
2 2014 ZD2:ZD909
12 11 10
0.42 5.0
6.0 6.5 7.0 7.5 8.0 Population competition pressure
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
9.0
2013 ZD2:YD13 2014 ZD2:ZD909
0.48 0.46 0.44
8.5
5.5
3
0.50
2013: y=–1.9041x+23.521 R=0.9948*** 2014: y=–1.5493x+22.223 R=0.9952***
8 5.5
2013: y=–0.0368x+0.7424 R=0.9818** 2014: y=–0.0354x+0.7462 R=0.9983**
0.52 2013 ZD2:YD13
13
9
0.52
0.49
6.0 6.5 7.0 7.5 Population competition pressure
15
2014 YD13:ZD909
0.53
0.50
***
2014: y=–1.732x+26.382 r=0.9706**
16
2013 YD13:ZD909
0.54
16
14 2013 ZD2:YD13
22
2014 YD13:ZD909
3
0.55
**
1
23
17
17 2013 ZD2:ZD909 2014 ZD2:ZD909
25
18 5.0
Population biomass yield (t ha–1)
6.0 6.5 7.0 7.5 Population competition pressure
Population grain yield (t ha–1)
23
2013 YD13:ZD909 Population HI
27
0.56
2
18
Population HI
2014 YD13:ZD909
28
22 5.5
C
19 2013 YD13:ZD909
Population HI
1
29
Population grain yield (t ha–1)
30
Population grain yield (t ha–1)
Population biomass yield (t ha–1)
A
ZHAI Li-chao et al. Journal of Integrative Agriculture 2017, 16(6): 1312–1321
2013: y=–0.0256x+0.6354 R=0.9808** 2014: y=–0.0215x+0.6307 r=0.9915***
0.42 5.5
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
Fig. 4 Changes in maize above-ground biomass yield, grain yield and harvest index (HI) with population competition pressure. A, B, and C represent three different replacement series, respectively. 1, 2, and 3 represent biomass yield, grain yield and HI, respectively. *, ** and *** correlation coefficients significantly different at the 0.05, 0.01, and 0.001 probability levels, respectively.
reason for the declined competitive ability of modern crop cultivars. Song et al. (2010) also reported that the modern wheat cultivar is a weak competitor, but yielded more than the older cultivar, the main reason is that the modern cultivar allocated more photosynthate to grain which would sacrisfied to some extent to the resource-foraging organs (root, leaf and stem). When crop cultivars are grown in a mixture or intercropping system, the competitive ability of component crops could be defined in terms of aggressivity (AG), relative crowding coefficient (RCC) and CR (Weigelt and Jolliffe 2003; Bhatti et al. 2006; Wahla et al. 2009). CR is considered to be a better measure of competitive ability of crops compared with RCC and AG (Willey and Rao 1980; Wahla et al. 2009). However, these competitive indices, which were used in previous studies, were based on individual competitive ability, it measures the competitive ability of one cultivar relative to another cultivar in a mixture, not the competitiveness of mixed population. As crop production
is a function of population performance, competitive ability should be considered from the population level. In the present study, we introduced PCP, which could reflect the severity of competition of mixed population. This index has a certain superiority when compared with some other indices, as it was calculated from CR, and no significant differences between different mixtures were observed for CR in each replacement series. The CR value was stable, according to the formula of PCP, which is only related to the proportion of the two-component cultivars in a mixture (i.e., p and q). In short, if CR is stable, only one mixture is needed in a replacement experiment, the replacement series would consist of three treatments: 0:6, 3:3 and 6:0, and CR would calculated from the yield of component cultivars in mixtures and monoculture. Based on the stable CR, the PCP of mixed crop populations, with any mixed proportions, could be easily calculated according to the proportion of component crops. Two important points must be emphasized in the present study. First, as PCP is related to population density, this
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400 350 300
y=–8.4232x+426.8 R=0.3479
250 5.5
2013 ZD909 2013 YD13 2014 ZD909 2014 YD13
6.0 6.5 7.0 7.5 8.0 8.5 Populaiton competition pressure
450
9.0
ZD2:ZD909
Kernel number per plant
Thousand-kernel weight (g)
200 5.0
Thousand-kernel weight (g)
Kernel number per plant
YD13:ZD909
400 350 300 y=–4.4373x+392.66 R=0.1177
250 200
5
5.5
2013 ZD909 2013 ZD2 2014 ZD909 2014 ZD2
6 6.5 7 7.5 8 8.5 Population competiiton pressure
ZD2:YD13
400 350 300
200 5.0
YD13:ZD909
y=–28.129x+824.66 R2=0.5814**
5.5
y=–15.538x+436.05 R=0.4859* 5.5
2013 YD13 2013 ZD2 2014 YD13 2014 ZD2
6.0 6.5 7.0 7.5 8.0 8.5 Populaiton competition pressure
9.0
2013 ZD909 2013 YD13 2014 ZD909 2014 YD13
6.0 6.5 7.0 7.5 8.0 8.5 9.0 Population competiiton pressure
700
ZD2:ZD909
650
2013 ZD909 2013 ZD2 2014 ZD909 2014 ZD2
600 550
y=–27.748x+813.95 R=0.6809** 5
5.5
750
450
250
700 680 660 640 620 600 580 560 540 520 500 5.0
500
9
Kernel number per plant
Thousand-kernel weight (g)
450
6 6.5 7 7.5 8 8.5 Populaiton competition pressure
9
ZD2:YD13
700 650 600 550 500
y=–23.025x+801.6 R2=0.4465* 5
5.5
2013 YD13 2013 ZD2 2014 YD13 2014 ZD2
6 6.5 7 7.5 8 8.5 Population competiiton pressure
9
Fig. 5 Changes of thousand-kernel weight and kernel number with variation in population competitive pressure. * and ** correlation coefficients significantly different at the 0.05 and 0.01 probability levels, respectively.
study was conducted only under a single population density. Second, our study mainly focused on the above-ground competition, but below-ground competition is also known as an important component in crop competition. Recognizing this limitation, this study suggested that PCP was negatively correlated to yield under a mixed cropping system. Further studies are needed to fully understand this relationship.
5. Conclusion The present study demonstrated that PCP was increased as the proportion of the older maize cultivar increased when grown in a mixture. Biomass yield, grain yield, HI, thousand kernel weight and kernel number per plant were negatively
correlated to PCP. Under the same population density, the declined population competitive pressure increased translocation of assimilates to grains and, ultimately, increased grain yield. Therefore, there is a negative correlation between population competitive intensity and yield performance in maize, breeders should develop a communal ideotype that would not perform well in competition in the process of breeding in future.
Acknowledgements We thank the National Basic Research Program of China (973 Program, 2015CB150401), the National Maize Industry Technology Research and Development Center, Ministry of
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Agriculture, China, and the Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences for their supports. The authors would like to thank Textcheck, Switzerland for their language help.
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ScienceDirect
RESEARCH ARTICLE
Relationship between population competitive intensity and yield in maize cultivars ZHAI Li-chao1, 2*, XIE Rui-zhi1*, LI Shao-kun1, FAN Pan-pan1 1
Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing 100081, P.R.China
2
Center for Agricultural Resources Research, Institute of Genetics and Development Biology, Chinese Academy of Sciences, Shijiazhuang 050021, P.R.China
Abstract Competition is a common phenomenon in agriculture production. Research on the relationship between competitive ability and crop yield is extensive, but the results have been inconsistent. Few studies have focused on the relationship between population competitive intensity and yield of maize (Zea mays L.) cultivars. The main objective of this study was to determine if a consistent relationship exists between maize yield and competitive ability. A two-year field experiment was conducted, employing a de Wit replacement series design. When two maize cultivars were grown in a mixture, yield was reduced for the modern cultivar and increased for the older cultivar. In each replacement series, per plant level yield of each cultivar, and population level yield of the mixture, decreased with increasing proportion of the older cultivar. Competitive ratio (CR) reflected differences in competitive ability of the three maize cultivars. In each replacement series, population competition pressure (PCP) increased with increasing proportion of the older cultivar, indicating that the older cultivar was a strong competitor. Biomass yield, grain yield, harvest index, thousand-kernel weight, and kernel number per plant, were negatively correlated with PCP. Our results demonstrated that inter-cultivar competition affects maize productivity, and increasing PCP will decrease translocation of assimilates to grain and, ultimately, reduce yield. Therefore, there is a negative correlation between population competitive intensity and yield performance in maize, breeders should develop a communal ideotype that would not perform well in competition in future. Keywords: maize, competition, competitive ability, population competitive pressure, yield
1. Introduction
Received 20 July, 2016 Accepted 27 November, 2016 Correspondence LI Shao-kun, Tel/Fax: +86-10-82108891, E-mail: [email protected] * These authors contributed equally to this study. © 2017, CAAS. All rights reserved. Published by Elsevier Ltd. doi: 10.1016/S2095-3119(16)61541-1
Competition is a common phenomenon in nature. It is also an important factor in agriculture production. The effects of competition are widespread, and easily observed in crop mixtures. Competition is also known to affect recruitment, growth and reproduction of crop plants (Keddy 2012). Numerous studies have focused on the relationship between competitive ability and crop grain yield, but the results have been inconsistent. Some studies have demonstrated
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an inconsistent relationship between the yield of a cultivar in a mixture and its yield in monoculture (Christian et al. 1941; Sahai 1955). Dong et al. (2007) and Du et al. (2011) also found that the competitive ability of wheat (Triticum aestivum L.) cultivars is not necessarily correlated with its grain yield. However, Worthington and Reberg-Horton (2013) suggested that competitive cereal crops should be bred for weed suppression. Crop cultivars with strong weed competitiveness and high yield potential could be compatible (Garrity et al. 1992; Ni et al. 2000; Fischer et al. 2001; Gibson et al. 2003; Zhao et al. 2006). These results suggest that crop cultivars with strong competitive ability could also produce high yield under a weedy conditions. In general, crops with higher competitive ability perform better in response to weed suppression (Jordan 1993). There is, however, a growing body of evidence indicating that crop yield is negatively correlated with its competitive ability (Fasoula 1990; Reynold et al. 1994; Lemerle et al. 2001; Murphy et al. 2008; Reid et al. 2009; Song et al. 2009; Fang et al. 2011). Snaydon (1984) and Zhang et al. (1999) reported a negative correlation between competitive ability and productive performance of wheat cultivars. Lemerle (2001) found that increased wheat competitive ability might be associated with decreased crop yield, and a study of 63 spring wheat cultivars showed that increased grain yield caused slight reductions in weed suppression over the past 150 years (Murphy et al. 2008). Vandeleur and Gill (2004) found that modern semi-dwarf wheat cultivars have low tolerance to weed competition and suffer greater yield losses from weed competition than older and lower yield potential cultivars. These studies above suggested that modern wheat cultivars with high yield potential are weak competitors. They reported a negative relationship between competitive ability and crop yield. In order to achieve a high yield, Donald (1968) agrued that plants in the crop community will compete with each other to a minimum degree, and suggested that a successful crop ideotype will be a weak competitor, relative to its mass. Crop production is a process of population, the research on the relationship between competitive ability and yield should also be conducted at the populaiton level. However, all previous people measured the competitive ability of crop cultivars at individual level in inter-cultivar competition, but not at population level. Since the competitive ability of crop cultivars is measured according to competitive indices that are based on crop biomass yield or grain yield, our hypothesis is that competition may change the allocation of photosynthate, and a higher population competitive intensity would reduce crop yield. The main objectives of this study were to (1) identify the mixing effects of maize cultivars, and (2) to determine whether there is a relationship between population competitive intensity and yield, if so, how to elucidate that relationship.
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2. Materials and method 2.1. Experiment site Field experiments were conducted in two consecutive years: 7 May to 30 September, 2013 (Year 1) and 25 April to 30 September, 2014 (Year 2) at the Gongzhuling Experimental Station of the Chinese Academy of Agricultural Sciences (43°11´–44°9´N, 124°02´–125°18´E), which is located in a humid, continental monsoon climate in Gongzhuling County of Jilin Province, China. Spring maize is usually grown from late April to late September, under rainfed conditions and with ridge planting. The mean annual air temperature at the experimental station is 5.6°C, average annual precipitation is 594.8 mm, and the annual frost-free period is approximately 144 d. The soil type is chernozem, with 26.3 g kg–1 organic matter, 1.5 g kg–1 total N, 124.90 mg kg–1 available N, 28.52 mg kg–1 available P, and 184.47 mg kg–1 available K in the upper soil profile. The rainfall during the maize growing period was 553.9 mm in 2013 and 438.1 mm in 2014. The accumulated temperatures (≥10°C) were 3 188.5 in 2013 and 3 056.4 in 2014.
2.2. Plant materials Three maize cultivars, released in different eras in China, were used for this study. Zhongdan 2 (ZD2) is a relative old maize cultivar very widely grown in northern China in the 1970s. Yedan 13 (YD13) was grown widely in China in the 1990s. Zhongdan 909 (ZD909), a modern maize cultivar released recently, is currently widely grown in China. All three cultivars were the most popular cultivars in their respective periods. The three maize cultivars differed in plant traits (Table 1), and were easily distinguished when grown in a mixture.
2.3. Experimental design The experimental design was a de Wit replacement series design (de Wit 1960), which consists of a set of pure and mixed populations in which the combined density of the components is held constant. The proportion of each component ranges from 0 to 1. In this study, all cultivar pairs (YD13:ZD909, ZD2:ZD909, ZD2:YD13) were combined in the ratios of 0:6, 1:5, 2:4, 3:3, 4:2, 5:1, and 6:0, respectively. The 2:4, 3:3 and 4:2 treatments were grown at 1:2, 1:1 and 2:1 ratios, respectively. Seeds were sown manually at a plant density of 6.7 plants m–2 and row spacing was 65 cm, with a blank row between plots (Fig. 1). Plots were 6 m×7 m and there were three replicates. Manual sowing occurred on 7 May 2013 and 25 April 2014, at a rate of two seeds per hill, and plots were thinned to one plant per hill at the
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Table 1 Parents, time of release and major characteristics of the three maize cultivars Zhongdan 2 (ZD2), Yedan 13 (YD13) and Zhongdan 909 (ZD909)
Maize cultivar YD13 Ye478♀×Dan340♂ The 1990s Semi-compact 258±4.0 115±2.2 0.917±0.027 28.8±0.8 46.4±1.7 130
ZD2 Mo17♀×Zi330♂ The 1970s Flat-type 300±4.3 131±3.7 0.810±0.042 31.9±0.6 43.5±2.4 128
Parents Time of release Morphological type Plant height (cm) Ear height (cm) Leaf area (m2) Average leaf angle (°) Leaf orientation value (°) Growth period (d)
ZD909 Zheng588♀×HD586♂ The 2010s Compact 263±2.4 117±2.9 0.862±0.01 21.9±0.5 57.3±2.7 126
Values are means±SE.
0:6
1:5
2:4
3:3
4:2
5:1
6:0
Fig. 1 Schematic diagram of planting pattern in the experiment design. White circles ( ) and black five-pointed stars (★) represent the two cultivars of each combination.
V3 (the 3rd leaf) stage. Weeds were controlled manually to eliminate negative effects from weed competition. Chemical fertilizers of N, P and K were applied at 150, 45 and 45 kg ha–1, respectively. N was topdressed at the V6 (the 6th leaf) and V12 (the 12th leaf) stages at 75 kg ha–1. All treatments were imposed under rainfed conditions.
2.4. Plant sampling In each replacement series treatment, three plants of each cultivar, within 3 m2 of the middle of each plot, were selected randomly and manually cut at ground level at physiological maturity. Plants were separated into stems, leaves, sheaths, tassels, and ears, and oven-dried to record dry matter yield. In addition, at harvest, 20 plants of each maize cultivar were harvested to record single-plant grain yield. Population-level yields were calculated from single-plant yield data. Harvest index (HI) was calculated as follows: Grain yield (1) HI= DMA Where, DMA is dry matter accumulation.
2.5. Competitive indices Competitive ratio (CR) CR is a commonly used indicator
to assess inter-specific competition between crop species in intercropping systems (Willey and Rao 1980). It measures the ability of one crop to compete with another crop (Dhima et al. 2007; Zhang et al. 2011). In the present study, CR was used as a measure of inter-cultivar competition and was calculated as follows: Yij /Yii (2) CRij = Yji /Yjj Where, CRij is the CR of cultivar i relative to cultivar j in a given mixture, Yii and Yjj are the average single plant biomass yields of cultivars i and j, respectively, in monoculture, and Yij and Yji are the average single plant biomass yields of cultivars i and j, respectively, in the mixture. If CRij is greater than 1.0, the competitive ability of cultivar i is superior to cultivar j in mixed cropping; otherwise, cultivar j has greater competitiveness. CRij is inversely related to CRji, so only one value (CRij) is presented here. Population competition pressure (PCP) To better illustrate the population competitive ability of a replacement mixture, we proposed a new index, PCP. We calculated PCP by using the CRs of the component maize cultivars in a replacement series, as follow: PCP =D×( pCRij+qCRji) (3) p+q=1 Where, D is population plant density (6.7 plants m–2), CRij
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and CRji are the CRs of cultivars i and j, respectively, in a
3.2. Harvest index (HI)
and j, respectively, in a given mixture. The higher the PCP
In each replacement series, the single plant HI of each cultivar and population-level grain yield decreased as the proportion of the older cultivar increased (Table 2). In each replacement series, the component cultivars differed in HI, which was always lower in the older cultivars in monoculture and in mixture. This trend was consistent across years, but there were differences in HI across year.
given mixture, and p and q are the proportions of cultivars i
2.6. Statistical analysis One-way analysis of variance was computed for each year (SPSS 19.0). Graphs were plotted either in SigmaPlot 12.5 or Excel 2010. Treatment means were compared by computing the least significant differences to identify significant differences at the 0.05 probability level. Linear regression analysis was used to examine patterns in yield performance and PCP. Pearson’s correlation coefficients were computed for all combinations of biomass yield, grain yield, HI and PCP.
3. Results 3.1. Single plant dry matter accumulation (DMA) and grain yield In each replacement series, the single plant DMA and grain yield of both component cultivars decreased significantly with increasing proportion of the older cultivars (Fig. 2). Variation in single plant DMA was found in different replacement series for the same cultivar. In addition, differences were observed for each cultivar across years. The reduction from the maximum to minimum single plant DMA varied between 61.3 and 77.1 g for ZD909 in the replacement series. Similarly, the reduction varied between 31.9 and 81.7 g for YD13, and between 53.5 and 81.5 g for ZD2 in the replacement series. The reduction of grain yield for ZD909 varied between 22.4 and 24.0%, the reduction varied between 20.7 and 24.6% for YD13, and it varied between 28.8 and 29.3% for ZD2. The older cultivar ZD2 was suceptible to inter-cultivar competition.
440 420 400 380 360 340 320 300
B 2013 ZD909 2013 YD13 2014 ZD909 2014 YD13
0:6 1:5 2:4 3:3 4:2 5:1 6:0 YD13:ZD909
Single plant dry matter weight (g per plant)
Single plant dry matter weight (g per plant)
A
450 400
3.3. Competitive ratio (CR) CR measures the competitive ability of one crop relative to another in a mixture or an intercropping system. When CR of one crop is greater than 1, the competitive ability of the crop is higher than the other in intercropping. In each replacement series, the CR value was always greater than 1 for different mixed ratios, and no significant differences were observed among the mixed ratios (Table 3). The CR values were also relatively stable across years for each replacement series. Moreover, the CR of ZD2 relative to ZD909 was higher than the CR of ZD2 relative to YD13, and the CR of ZD2 relative to YD13 was higher than the CR of YD13 relative to ZD909. These results indicate that ZD2 was more competitive than ZD909 and YD13, and YD13 was more competitive than ZD909. These results were consistent across 2013 and 2014.
3.4. Population competitive pressure (PCP) To illustrate the competitive ability of populations, we proposed the index PCP, which could reflect the severity of competition of mixed crop populations. PCP was calculated from the CR values of the component cultivars in a mixture. In each replacement series, PCP increased with increasing proportion of older cultivars (Fig. 3). PCP varied across years, but the trend across replacement series was consistent for the two years. These results indirectly suggest that 2013 ZD909 2013 ZD2 2014 ZD909 2014 ZD2
350 300 250 200
0:6 1:5 2:4 3:3 4:2 5:1 6:0 ZD2:ZD909
C Single plant dry matter weight (g per plant)
value, the greater the population competition pressure.
380 360 340 320 300 280 260 240 220
2013 YD13 2013 ZD2 2014 YD13 2014 ZD2
0:6 1:5 2:4 3:3 4:2 5:1 6:0 ZD2:YD13
Fig. 2 Single plant biomass yield and grain yield of maize cultivars in different replacement series in 2013 and 2014. YD13, Yedan 13; ZD909, Zhongdan 909; ZD2, Zhongdan 2. Bars mean SE.
Mixed cropping patterns are the ratios of two cultivars mixed in the cropping system (YD13:ZD909, ZD2:ZD909 and ZD2:YD13). The ratios 0:6 and 6:0 indicate monoculture of each cultivar. Different letters in the same column within each year indicate significant differences (P<0.05). Values are means±SE.
1)
0.481±0.005 a 0.478±0.014 a 0.455±0.021 a 0.438±0.055 a 0.435±0.023 a 0.429±0.001 a 0.559±0.006 a 0.554±0.008 a 0.543±0.007 a 0.540±0.005 a 0.521±0.005 b 0.506±0.004 b 0.541±0.006 a 0.518±0.008 ab 0.506±0.004 b 0.499±0.007 b 0.494±0.012 b 0.492±0.009 b 0.548±0.009 a 0.549±0.003 a 0.541±0.014 a 0.532±0.002 a 0.524±0.011 ab 0.501±0.009 b 2014
2013
Mixed cropping pattern1) 0:6 1:5 2:4 3:3 4:2 5:1 6:0 0:6 1:5 2:4 3:3 4:2 5:1 6:0
ZD909 0.548±0.003 a 0.544±0.002 a 0.545±0.001 a 0.540±0.004 b 0.528±0.001 c 0.515±0.002 d
YD13:ZD909 YD13
0.534±0.002 a 0.511±0.002 ab 0.501±0.004 bc 0.498±0.003 cd 0.487±0.002 de 0.480±0.007 e
Population 0.548±0.003 a 0.543±0.001 ab 0.535±0.001 b 0.523±0.003 c 0.509±0.002 d 0.492±0.002 e 0.480±0.007 f 0.548±0.009 a 0.547±0.002 a 0.533±0.012 ab 0.519±0.003 bc 0.507±0.007 bc 0.495±0.011 c 0.492±0.009 c
ZD909 0.547±0.005 a 0.540±0.003 ab 0.535±0.009 ab 0.528±0.005 ab 0.523±0.007 b 0.523±0.004 b
ZD2:ZD909 ZD2
0.452±0.006 a 0.428±0.004 b 0.421±0.006 bc 0.408±0.009 cd 0.406±0.005 cd 0.392±0.004 d
Population 0.547±0.005 a 0.534±0.003 b 0.511±0.004 c 0.493±0.002 d 0.461±0.004 e 0.438±0.004 f 0.392±0.004 g 0.559±0.006 a 0.543±0.007 ab 0.523±0.003 b 0.500±0.012 c 0.477±0.006 d 0.445±0.007 ef 0.429±0.001 f
YD13 0.492±0.004 a 0.488±0.007a b 0.490±0.004 ab 0.484±0.006 ab 0.473±0.008 bc 0.465±0.002 c
YD13:ZD2 ZD2
Population 0.492±0.004 a 0.456±0.004 a 0.485±0.006 ab 0.438±0.006 b 0.476±0.001 b 0.420±0.001 c 0.463±0.00 6c 0.408±0.001 cd 0.449±0.003 d 0.403±0.006 d 0.432±0.004 e 0.403±0.005 d 0.403±0.005 f 0.512±0.003 a 0.512±0.003 a 0.505±0.004 ab 0.496±0.005 a 0.504±0.004 ab 0.497±0.004 abc 0.497±0.003 a 0.497±0.004 bc 0.481±0.003 bc 0.478±0.011 ab 0.479±0.004 cd 0.473±0.004 c 0.466±0.006 b 0.468±0.003 de 0.471±0.020 c 0.455±0.011 bc 0.457±0.012 ef 0.439±0.007 c 0.439±0.007 f
ZHAI Li-chao et al. Journal of Integrative Agriculture 2017, 16(6): 1312–1321
Year
Table 2 Harvest index of Zhongdan909 (ZD909), Yedan 13 (YD13), and Zhongdan 2 (ZD2) in three different mixed cropping combinations (YD13:ZD909, ZD2:ZD909 and ZD2:YD13)
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the older maize cultivar is a strong competitor.
3.5. The relationship between yield and population competitive pressure Maize yield was highly correlated with PCP. A linear relationship existed between maize population-level biomass yield, grain yield, HI and PCP. In each replacement series, the population-level biomass yield, grain yield and HI were negatively correlated with PCP, and the correlation coefficients were significant (P<0.05) or highly significant (P<0.01; Fig. 4). Although a significant year effect was observed for each replacement mixture, the variation was consistent across 2013 and 2014.
3.6. The relationship between yield components and population competitive pressure Kernel weight and kernel number are important components of maize yield. In each replacement series, both thousand kernel weight and kernel number per plant of each cultivar were slightly reduced with increasing PCP (Fig. 5), and they were negatively correlated. However, the correlation coefficients were not significant in most cases. In addition, in each replacement series, cultivars differed in thousand-kernel weight and kernel number. They also varied across years.
4. Discussion Inter-specific competition plays an important role in determining crop yield in intercropping systems (Li et al. 2001; Zhang et al. 2007). Similarly, inter-cultivar competition has a significant effect on yield (Treder et al. 2008; Song et al. 2009, 2010; Fang et al. 2011; Lithourgidis et al. 2011). When crop cultivars are planted together, both negative and positive interactions can occur simultaneously (Callaway and Walker 1997; Mariotti et al. 2009). In the present study, when two maize cultivars released in different eras were grown in a mixture, yield of the modern cultivar decreased, and increased for the older cultivar. In each replacement series, the individual- and population-level biomass yield and grain yield were significantly reduced with increasing proportion of the older cultivar. Fig. 2 indicated that the older maize cultivar benefitted from the inter-cultivar competition in terms of above-ground DMA and grain yield. The modern cultivar experienced significantly reduced growth in mixtures, as compared to monoculture. These results were consistent with earlier reports on wheat cultivars (Song et al. 2009; Fang et al. 2011). Our previous studies also confirmed that maize grain yield decreased with an increasing proportion of the stronger competitor (Zhai et al. 2015, 2016). Under the same population density, crop PCP was closely
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Table 3 Competitive ratio of Yedan 13 (YD13):Zhongdan 909 (ZD909), Zhongdan 2 (ZD2):ZD909, and ZD2:YD13, for varying mixed ratios Mixed cropping pattern YD13:ZD909 ZD2:ZD909 ZD2:YD13 YD13:ZD909 ZD2:ZD909 ZD2:YD13
Year 2013
2014
1:5 1.224±0.036 a 1.415±0.016 a 1.312±0.017 a 1.183±0.022 a 1.330±0.029 a 1.247±0.056 a
2:4 1.197±0.011 a 1.367±0.050 ab 1.293±0.002 a 1.216±0.003 a 1.334±0.054 a 1.248±0.029 a
Mixed ratio 3:3 1.184±0.017 a 1.362±0.018 ab 1.267±0.007 ab 1.191±0.021 a 1.361±0.073 a 1.264±0.024 a
4:2 1.181±0.013 a 1.362±0.028 ab 1.254±0.007 ab 1.222±0.040 a 1.340±0.031 a 1.283±0.082 a
5:1 1.200±0.010 a 1.281±0.008 b 1.229±0.033 b 1.228±0.062 a 1.361±0.057 a 1.300±0.027 a
Average 1.197 1.357 1.271 1.208 1.345 1.268
Different letters in the same column within each year indicate significant differences (P<0.05). Values are means±SE.
B
2013 2014
8 7 6 5 4
1:5
2:4 3:3 4:2 YD13:ZD909
5:1
9
C
2013 2014
Populaiton competition pressure
9
Populaiton competition pressure
Populaiton competition pressure
A
8 7 6 5 4
1:5
2:4 3:3 4:2 ZD2:ZD909
5:1
9
2013 2014
8 7 6 5 4
1:5
2:4 3:3 4:2 ZD2:YD13
5:1
Fig. 3 Changes of population competition pressure of different replacement series. YD13, Yedan 13; ZD909, Zhongdan 909; ZD2, Zhongdan 2.
related to individual plant competitive ability. The stronger the competitive ability of individual plant, the greater the PCP is. In the present study, in each replacement series, PCP increased with an increasing proportion of the older maize cultivar (Fig. 4). Through related analysis, population level biomass yield, HI, grain yield, thousand kernel weight and kernel number per plant were reduced with the increasing PCP (Fig. 5). Du et al. (2011) and Dong et al. (2007) reported that there is no clear relationship between competitive ability and grain yield in wheat cultivars. It has been shown that crop cultivars with strong weed suppression (i.e., a strong competitive ability against weeds) could have high yield potential (Hucl 1998; Gibson et al. 2003; Zhao et al. 2006). These results are different from our findings. However, a growing body of research evidence suggests that crop populations with weak individual competitive ability produce more grain when population density is constant (Reynolds et al. 1994; Vandeleur and Gill 2004; Murphy et al. 2008; Song et al. 2009; Fang et al. 2011; Zhai et al. 2015). Donald (1968, 1981) argued that, to increase yield potential of annual crops, breeders must develop a “communal” ideotype that would not perform well in competition. In a crop population consisting of plants that are weak competitors, PCP is low and the individual plants tend to allocate more resources to seeds. However, when crop populations primarily consist
of strong competitors, more resources will be allocated to resource-foraging organs (e.g., root, stems and leaves) to increase competitive ability, but not to reproductive organs. Therefore, a crop to be high yielding the individual plants making it up should be weak competitors, breeders should develop a communal ideotype that would not perform well in competition in future. HI is a key determinant of maize yield (Echarte and Andrade 2003), as it reflects the partitioning of photosynthate. Evans (1981) proposed that cultivars with high grain yield are weak competitors, due to the increased allocation of photosynthate to the ear and grain filling rather than to the leaves. The competitive ability of crop cultivars might be associated with HI. Donald (1968) argued that competitive ability or partitioning to organs, such as stems and leaves, could be sacrificed to some degree for increased reproductive allocation. In our results, in each replacement series, plant-level and population-level HI decreased with increasing proportions of the older maize cultivar (Table 2), illustrating that competition reduces the partitioning to grain, which reduces grain yield. According to Qin et al. (2012, 2013), the process of artificial selection in breeding is actully the adjustment of allometric growth in above-ground and below-ground, they indicated that domestication has resulted in an increase in an increased biomass allocation in shoot compared to root biomass allocation, this may be the main
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26 25 24 2013: y=–3.8776x+52.45 R=0.9976 2014: y=–1.4638x+33.997 R=0.9493*
***
B
28
Population biomass yield (t ha–1)
27
1
26
8.0
24 23 22 21 20
2013: y=–2.7669x+42.396 R=0.9810**
19
2014: y=–1.6986x+33.845 R=0.9759**
24
5.5
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
2014 ZD2:YD13
21 20 19 18
2013: y=–2.0934x+34.378 R=0.9858** 2014: y=–1.8666x+33.418 R=0.9968**
17 5.5
15 14 2013: y=–3.2739x+38.086 R=0.9977
13 12 5.5
9.0
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
0.51 2013: y=–0.0306x+0.7282 R=0.9889** 2014: y=–0.0297x+0.7243 R=0.9935**
0.48 5.5
8.0
6.0 6.5 7.0 7.5 Population competition pressure
0.56
2 2013 ZD2:ZD909
0.54
2014 ZD2:ZD909
0.52
14 13 12
8.0
3 2013 ZD2:ZD909 2014 ZD2:ZD909
0.50 0.48 0.46
11 10 2013: y=–2.5851x+30.929 R=0.9913 2014: y=–1.8944x+26.038 R=0.9918** 9 5.0 5.5 6.0 6.5 7.0 7.5 8.0 Population competition pressure
0.44 8.5
9.0
2 2014 ZD2:ZD909
12 11 10
0.42 5.0
6.0 6.5 7.0 7.5 8.0 Population competition pressure
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
9.0
2013 ZD2:YD13 2014 ZD2:ZD909
0.48 0.46 0.44
8.5
5.5
3
0.50
2013: y=–1.9041x+23.521 R=0.9948*** 2014: y=–1.5493x+22.223 R=0.9952***
8 5.5
2013: y=–0.0368x+0.7424 R=0.9818** 2014: y=–0.0354x+0.7462 R=0.9983**
0.52 2013 ZD2:YD13
13
9
0.52
0.49
6.0 6.5 7.0 7.5 Population competition pressure
15
2014 YD13:ZD909
0.53
0.50
***
2014: y=–1.732x+26.382 r=0.9706**
16
2013 YD13:ZD909
0.54
16
14 2013 ZD2:YD13
22
2014 YD13:ZD909
3
0.55
**
1
23
17
17 2013 ZD2:ZD909 2014 ZD2:ZD909
25
18 5.0
Population biomass yield (t ha–1)
6.0 6.5 7.0 7.5 Population competition pressure
Population grain yield (t ha–1)
23
2013 YD13:ZD909 Population HI
27
0.56
2
18
Population HI
2014 YD13:ZD909
28
22 5.5
C
19 2013 YD13:ZD909
Population HI
1
29
Population grain yield (t ha–1)
30
Population grain yield (t ha–1)
Population biomass yield (t ha–1)
A
ZHAI Li-chao et al. Journal of Integrative Agriculture 2017, 16(6): 1312–1321
2013: y=–0.0256x+0.6354 R=0.9808** 2014: y=–0.0215x+0.6307 r=0.9915***
0.42 5.5
6.0 6.5 7.0 7.5 8.0 Population competition pressure
8.5
Fig. 4 Changes in maize above-ground biomass yield, grain yield and harvest index (HI) with population competition pressure. A, B, and C represent three different replacement series, respectively. 1, 2, and 3 represent biomass yield, grain yield and HI, respectively. *, ** and *** correlation coefficients significantly different at the 0.05, 0.01, and 0.001 probability levels, respectively.
reason for the declined competitive ability of modern crop cultivars. Song et al. (2010) also reported that the modern wheat cultivar is a weak competitor, but yielded more than the older cultivar, the main reason is that the modern cultivar allocated more photosynthate to grain which would sacrisfied to some extent to the resource-foraging organs (root, leaf and stem). When crop cultivars are grown in a mixture or intercropping system, the competitive ability of component crops could be defined in terms of aggressivity (AG), relative crowding coefficient (RCC) and CR (Weigelt and Jolliffe 2003; Bhatti et al. 2006; Wahla et al. 2009). CR is considered to be a better measure of competitive ability of crops compared with RCC and AG (Willey and Rao 1980; Wahla et al. 2009). However, these competitive indices, which were used in previous studies, were based on individual competitive ability, it measures the competitive ability of one cultivar relative to another cultivar in a mixture, not the competitiveness of mixed population. As crop production
is a function of population performance, competitive ability should be considered from the population level. In the present study, we introduced PCP, which could reflect the severity of competition of mixed population. This index has a certain superiority when compared with some other indices, as it was calculated from CR, and no significant differences between different mixtures were observed for CR in each replacement series. The CR value was stable, according to the formula of PCP, which is only related to the proportion of the two-component cultivars in a mixture (i.e., p and q). In short, if CR is stable, only one mixture is needed in a replacement experiment, the replacement series would consist of three treatments: 0:6, 3:3 and 6:0, and CR would calculated from the yield of component cultivars in mixtures and monoculture. Based on the stable CR, the PCP of mixed crop populations, with any mixed proportions, could be easily calculated according to the proportion of component crops. Two important points must be emphasized in the present study. First, as PCP is related to population density, this
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400 350 300
y=–8.4232x+426.8 R=0.3479
250 5.5
2013 ZD909 2013 YD13 2014 ZD909 2014 YD13
6.0 6.5 7.0 7.5 8.0 8.5 Populaiton competition pressure
450
9.0
ZD2:ZD909
Kernel number per plant
Thousand-kernel weight (g)
200 5.0
Thousand-kernel weight (g)
Kernel number per plant
YD13:ZD909
400 350 300 y=–4.4373x+392.66 R=0.1177
250 200
5
5.5
2013 ZD909 2013 ZD2 2014 ZD909 2014 ZD2
6 6.5 7 7.5 8 8.5 Population competiiton pressure
ZD2:YD13
400 350 300
200 5.0
YD13:ZD909
y=–28.129x+824.66 R2=0.5814**
5.5
y=–15.538x+436.05 R=0.4859* 5.5
2013 YD13 2013 ZD2 2014 YD13 2014 ZD2
6.0 6.5 7.0 7.5 8.0 8.5 Populaiton competition pressure
9.0
2013 ZD909 2013 YD13 2014 ZD909 2014 YD13
6.0 6.5 7.0 7.5 8.0 8.5 9.0 Population competiiton pressure
700
ZD2:ZD909
650
2013 ZD909 2013 ZD2 2014 ZD909 2014 ZD2
600 550
y=–27.748x+813.95 R=0.6809** 5
5.5
750
450
250
700 680 660 640 620 600 580 560 540 520 500 5.0
500
9
Kernel number per plant
Thousand-kernel weight (g)
450
6 6.5 7 7.5 8 8.5 Populaiton competition pressure
9
ZD2:YD13
700 650 600 550 500
y=–23.025x+801.6 R2=0.4465* 5
5.5
2013 YD13 2013 ZD2 2014 YD13 2014 ZD2
6 6.5 7 7.5 8 8.5 Population competiiton pressure
9
Fig. 5 Changes of thousand-kernel weight and kernel number with variation in population competitive pressure. * and ** correlation coefficients significantly different at the 0.05 and 0.01 probability levels, respectively.
study was conducted only under a single population density. Second, our study mainly focused on the above-ground competition, but below-ground competition is also known as an important component in crop competition. Recognizing this limitation, this study suggested that PCP was negatively correlated to yield under a mixed cropping system. Further studies are needed to fully understand this relationship.
5. Conclusion The present study demonstrated that PCP was increased as the proportion of the older maize cultivar increased when grown in a mixture. Biomass yield, grain yield, HI, thousand kernel weight and kernel number per plant were negatively
correlated to PCP. Under the same population density, the declined population competitive pressure increased translocation of assimilates to grains and, ultimately, increased grain yield. Therefore, there is a negative correlation between population competitive intensity and yield performance in maize, breeders should develop a communal ideotype that would not perform well in competition in the process of breeding in future.
Acknowledgements We thank the National Basic Research Program of China (973 Program, 2015CB150401), the National Maize Industry Technology Research and Development Center, Ministry of
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Agriculture, China, and the Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences for their supports. The authors would like to thank Textcheck, Switzerland for their language help.
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