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. 2020 May 29;10:8769. doi: 10.1038/s41598-020-65574-0

Inbred varieties outperformed hybrid rice varieties under dense planting with reducing nitrogen

Jian Lu 1,#, Danying Wang 2,#, Ke Liu 1,#, Guang Chu 2, Liying Huang 3, Xiaohai Tian 1,3,4, Yunbo Zhang 1,3,4,✉
PMCID: PMC7260172  PMID: 32472003

Abstract

Field experiments were conducted over two years to evaluate the effects of planting density and nitrogen input rate on grain yield and nitrogen use efficiency (NUE) of inbred and hybrid rice varieties. A significant interaction effect was observed between nitrogen input and planting density on grain yield. Higher number of panicles per square meter and spikelets per panicle largely accounted for the observed advantage in performance of inbred, relative to hybrid varieties. Compared with high nitrogen input rate, nitrogen absorption efficiency, nitrogen recovery efficiency, and partial factor productivity increased by 24.6%, 28.0%, and 33.3% in inbred varieties, and by 32.2%, 29.3%, and 35.0% in hybrids under low nitrogen input, respectively. Inbred varieties showed higher nitrogen absorption efficiency, nitrogen recovery efficiency, and partial factor productivity than hybrids, regardless of nitrogen input level. Nitrogen correlated positively with panicle number, spikelets per panicle, biomass production at flowering, and after flowering in inbred varieties but only with panicle number and biomass production at flowering in hybrids. Inbred varieties are more suitable for high planting density at reduced nitrogen input regarding higher grain yield and NUE. These findings bear important implications for achieving high yield and high efficiency in nutrient uptake and utilization in modern rice-production systems.

Subject terms: Plant ecology, Plant physiology

Introduction

Rice (Oryza sativa L.) is the main staple food for more than half the population of the world1. As one of the largest rice producers and consumers, China occupied 18.8% of the global rice-growing area and accounted for 28.1% of the total production in 20142. Double-season rice cropping has significantly contributed to the increase in rice productivity in China; however, the cultivated area has decreased substantially due to labor migration and increased labor costs over the past decades3. Therefore, it is necessary to develop labor-saving cultivation technologies to reverse the declining trend in rice cultivation area in this country.

Mechanical transplanting is an alternative labor-saving technology in rice production4. As efficient agriculture has been popularized in recent years, mechanical transplanting has been rapidly adopted for rice production in China5. However, rice farmers still follow traditional field management practices even under the mechanical-transplanting production scheme6. Previous studies confirmed that certain traditional management practices, such as nitrogen (N) fertilization utilize resources inefficiently and have negative environmental impacts7,8. In China, the average N application rate for rice production is 180 kg ha−1, which is 75% higher than the global average9–11. Consequently, only 20–30% of applied N is actually absorbed by the crop, while most of it is lost to the environment6. Over the past three decades, this N-fertilizer overuse in China has caused surface water eutrophication, soil acidification, increased greenhouse gas emissions, and enhanced N deposition9–14. Moreover, diminishing returns are being observed with N fertilizer use in China; indeed, the resulting increases in rice production have not been commensurate with the increases in N fertilizer application since the start of the Green Revolution15,16. Therefore, external N input must be reduced in order to realize both environmental and economic benefits from rice production.

High planting density has been recommended to reduce N application rates in rice production15. Thus, for example, Liu et al.17 demonstrated that for conventional seedling broadcasting, the N application rate was lowered by 18% when seedling density was raised by 32%; nevertheless, grain yield was not substantially improved. On the other hand, Hou et al.18 observed that a 165 kg N ha−1 application rate combined with a 24–27 × 104 hills ha−1 for planting density resulted in similar or even greater grain yield and NUE than with a 245.5 kg N ha−1 application rate on mechanically transplanted hybrid rice. Similar results were reported by Huang et al.15 and Xie et al.19, who claimed that high planting density, combined with reduced N input rate, may increase grain yield and NUE even under low light stress. The aforementioned results indicate that high-density planting with lowered N input might be a sustainable strategy for the improvement of rice yield and NUE.

Most previous studies focused on only one type of rice variety. In contrast, very few studies have compared the relative effects of combining high planting density with reduced nitrogen application rate on yield and NUE in inbred and hybrid varieties simultaneously. Super hybrid cultivars have high yield potential associated with a relatively larger number of spikelets per panicle and higher biomass production than inbred rice cultivars20–22. Thus, for example, Zhang et al.20 observed that super hybrid varieties had 12% higher yield potential than ordinary hybrid and inbred varieties. They hypothesized that mechanically transplanted hybrid-rice cultivated at low N input and high planting density, may still show superior grain yield compared with inbred varieties.

In this study, field experiments were conducted using inbred and hybrid varieties grown at different N application rates and planting densities. We used the method of cluster analysis, and the different agronomic characters of inbred and hybrid rice were analyzed by variance analysis, and the effect of nitrogen rate and planting density of the same type of rice was compared further. The objectives of this study were: 1) to compare grain yield and NUE between inbred and hybrid rice varieties grown under different N input rates and planting densities, and 2) to identify the factors accounting for the relative differences in grain yield and NUE between inbred and hybrid rice varieties.

Results

Climate conditions

Average temperature during the growing season was 0.5–1.8 °C lower in Jingzhou than in Hangzhou (Fig. 1). Seasonal mean maximum temperatures in Jingzhou were 30.0 °C in 2017 and 32.4 °C in Hangzhou in 2018. Seasonal mean minimum temperatures in Jingzhou were 23.0 °C in 2017 and 24.2 °C in Hangzhou in 2018, respectively. As can be seen, temperatures did not differ much between Jingzhou and Hangzhou. Further, the difference in average daily solar radiation during the growing season was only ~7.3% between the two sites. The seasonal average daily radiation levels were 15.9 MJ m−2 d−1 and 14.7 MJ m−2 d−1 in 2017 and 2018 for Jingzhou and Hangzhou, respectively. Therefore, the difference in seasonal average daily radiation between Jingzhou and Hangzhou was similar.

Figure 1.

Figure 1

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Daily maximum and minimum temperatures and solar radiation during the rice-growing season at Jingzhou in 2017 (a) and Hangzhou in 2018 (b).

Grain yield

N application rate, planting density, and variety significantly (P < 0.01) affected grain yield of hybrid and inbred cultivars at both sites (Tables 1 and 2). However, the interactive effects of these factors on grain yield were not significant (P > 0.05). Grain yield significantly increased (N1) and either remained constant (N2) or decreased (N3) with increasing N application rate at all planting densities. Yield increase in inbred and hybrid varieties differed among N treatments. Average grain-yield increases were 26.32% for the inbred varieties and 8.84% for the hybrid varieties (Tables 1 and 2). At Jingzhou, N1×D3 was the most effective of all combination treatments to increase grain yield in both inbred and hybrid varieties. In turn, at Hangzhou, N3×D3 realized the highest grain yield for the inbred varieties, while N3×D1 was optimal for enhancing grain yield in the hybrids tested. Varietal differences were not significant (P > 0.05) across N treatments, except for N0 at Jingzhou and N3×D2 at Hangzhou.

Table 1.

Grain yield (kg ha−1) relative N application rate and planting density in inbred and hybrid rice at Jingzhou in 2017.

Variety N0 N1 N2 N3
D1 D2 D3 D1 D2 D3 D1 D2 D3 D1 D2 D3
HHZ 4.35b 4.55b 5.36b 8.56b 9.60a 10.46a 10.25a 9.79a 9.59a 10.35ab 9.69a 9.14b
YNSM 4.65b 4.57b 5.28b 9.59a 9.91a 10.45a 10.30a 9.75a 9.60a 10.44a 9.70a 9.48b
Y-LY900 7.73a 8.47a 8.67a 9.77a 10.13a 10.43a 9.53b 10.03a 10.13a 9.90a 9.60a 10.43a
QLYSM 8.01a 7.90a 8.73a 9.53a 9.67a 10.43a 8.77c 8.80b 9.73a 9.07b 8.73b 9.63b
ANOVA Variety (V) **
Nitrogen (N) **
Density (D) *
V*N **
V*D ns
N*D ns
V*N*D ns
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† Different lowercase letters within columns indicate significant differences among varieties at P < 0.05 (n = 3). *P < 0.05. **P < 0.01. ns, not significant.

Table 2.

Grain yield (kg ha−1) relative N application rate and planting density in inbred and hybrid rice at Hangzhou in 2018.

Variety N0 N1 N2 N3
D1 D2 D3 D1 D2 D3 D1 D2 D3 D1 D2 D3
HHZ 6.24a 6.24bc 7.04a 8.12a 8.78b 9.34ab 9.80a 9.61a 9.33ab 10.11a 10.27a 11.32a
YD-6 5.43a 5.91c 6.55a 6.72b 7.74c 8.21ac 8.62b 8.61b 8.90b 7.92b 8.54b 9.92ab
ZZY-8 6.57a 6.82ab 7.11a 8.47a 9.72a 8.41bc 9.31a 9.29ab 9.81ab 9.22a 9.12b 9.31b
C-LYHZ 6.90a 7.21a 7.02a 8.79a 9.22ab 9.52a 9.91a 9.13ab 9.81a 10.22a 10.23a 10.04ab
ANOVA Variety (V) **
Nitrogen (N) **
Density (D) **
V*N ns
V*D ns
N*D ns
V*N*D ns
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†Different lowercase letters within columns indicate significant differences among varieties at P < 0.05 (n = 3). *P < 0.05. **P < 0.01. ns, not significant.

Yield components, biomass, and NUE

Yield component responses to plant density varied with N application rate (Tables 3 and 4). Panicle number significantly (P < 0.05) increased with N application rate and plant density for inbred and hybrid rice varieties. The number of spikelets per panicle significantly (P < 0.05) increased with N application rate but decreased with increasing planting density. The number of panicles in the treatments receiving N was 22.1% and 32.1% higher for the hybrid and the inbred varieties, respectively, relative to the N0 treatment, (Tables 3 and 4). Conversely, relative to N0, the number of spikelets per panicle in all N treatments was 27.0% and 9.9%, respectively, higher for the inbred and the hybrid varieties (Tables 3 and 4). At Jingzhou, N1×D3 was optimal for inducing greater panicle and spikelet number per panicle across treatments in both inbred and hybrid varieties (Table 3). In turn, at Hangzhou, the optimal combination treatment for promoting higher panicle and spikelets number per panicle in inbred varieties was N3×D3, while N3×D1 was the best combination treatment for the hybrid varieties under study (Table 4).

Table 3.

Yield components relative to N application rate and planting density in inbred and hybrid rice varieties at Jingzhou. Different lowercase letters indicate significant differences at P < 0.05 (n = 3).

Variety N D Panicles Skikete panicle−1 Seed setting precentage(%) 1000-grain weight(mg)
HHZ N0 D1 214.5d 118.5d 90.3a 20.2a
D2 231.8 cd 104.5d 90.5a 20.2a
D3 262.9c 128.7d 89.4ab 19.8ab
N1 D1 345.1b 167.8c 89.5ab 19.5abc
D2 354.2ab 188.6abc 88.4abc 19.5abc
D3 397.2a 196.5abc 83.5abcd 18.9cde
N2 D1 354.7ab 198.5abc 87.6abc 19.3bc
D2 374.6ab 180.5bc 85.2abcd 18.6def
D3 396.3a 180.8bc 81.4bcd 18.2f
N3 D1 376.2ab 215.2a 80.1cd 19.0cd
D2 390.4ab 199.8ab 78.2d 18.2ef
D3 395.6a 190.4abc 78.7d 18.0f
YNSM N0 D1 240.3a 123.5b 90.8a 20.4a
D2 239.5c 117.9b 90.3a 20.2ab
D3 261.0c 123.5b 90.2a 20.2ab
N1 D1 332.8d 197.5a 87.4abc 20.1abc
D2 342.7cd 189.8a 84.6abcd 19.8abc
D3 394.4abc 192.6a 84.3abcd 19.5abcd
N2 D1 353.3bcd 210.5a 87.8ab 19.5abcd
D2 371.2abcd 191.5a 84.5abcd 19.1abcd
D3 401.6ab 195.5a 81.8bcd 18.8bcd
N3 D1 377.1abcd 219.2a 81.5bcd 18.8cd
D2 390.6abc 201.2a 80.7cd 18.4cd
D3 409.3a 190.6a 78.5d 18.3d
Y-LY900 N0 D1 151.6cef 339.1ab 79.0ab 20.7b
D2 147.3cf 319.7ab 80.8ab 21.1ab
D3 212.0abc 221.5 cd 83.5a 21.6ab
N1 D1 198.3bcd 260.4abcd 61.3e 22.2a
D2 200.8bc 254.3bcd 72.3bcd 20.8b
D3 242.1ab 209.2d 70.9bcde 21.5ab
N2 D1 168.8cdef 344.4a 63.0de 21.9ab
D2 187.5cde 338.6ab 66.5de 21.5ab
D3 257.3a 295.0abcd 68.1cde 21.8ab
N3 D1 132.9f 266.6abcd 72.5bcd 21.1ab
D2 176.6cdef 304.9abc 67.1de 21.3ab
D3 173.9cdef 302.6abc 77.8abc 21.4ab
QLYSM N0 D1 177.8cd 167.5bcde 87.4ab 24.2cd
D2 171.7d 217.1ab 72.3de 24.6abc
D3 210.7bcd 133.5e 89.7a 24.3bcd
N1 D1 179.2 cd 246.6a 83.9abc 24.3abcd
D2 218.9bcd 208.3abc 75.0cde 24.7ab
D3 257.6b 188.6abcde 82.3abcd 24.5abc
N2 D1 164.0d 221.0ab 70.3e 24.2cd
D2 262.5b 128.6e 75.6cde 24.3bcd
D3 268.8b 142.2de 80.5abcde 24.0d
N3 D1 244.9bc 151.6cde 77.5bcde 24.8a
D2 247.5b 194.7abcd 78.9bcde 24.7ab
D3 432.0a 130.8e 82.2abcd 24.5abc
ANOVA Variety (V) ns ns ns *
Nitrogen (N) ** ** ns ns
Density (D) ** * ns ns
V*N * ns * *
V*D ns ns ns ns
N*D ns ns ns ns
V*N*D * ns ns ns
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†Different lowercase letters within columns indicate significant differences at P < 0.05 across N rates (n = 3).

Table 4.

Yield components relative to N application rate and planting density in inbred and hybrid rice varieties at Hangzhou.

Variety N D Panicles Skikete panicle−1 Seed setting precentage(%) 1000-grain weight(mg)
HHZ N0 D1 196.8g 165.5b 92.8a 18.9ab
D2 223.5fg 169.8ab 91.9a 18.8ab
D3 244.7defg 166.8b 92.7a 19.0ab
N1 D1 240.5efg 170.1ab 92.7a 18.8ab
D2 259.5cdef 177.3ab 92.4a 19.0ab
D3 304.0bc 174.0ab 93.2a 18.1b
N2 D1 278.5cde 191.0a 91.5a 18.2b
D2 348.6ab 184.7ab 91.2a 19.0ab
D3 377.2a 186.3ab 94.3a 18.5ab
N3 D1 358.3a 190.9a 91.0a 19.1ab
D2 297.4bcd 190.7a 92.6a 18.9ab
D3 367.9a 182.8ab 93.2a 19.4a
YD-6 N0 D1 161.0bc 147.6bcd 91.9a 28.1ab
D2 177.5bc 135.5d 92.4a 27.9b
D3 142.7c 143.3cd 89.9ab 28.3ab
N1 D1 169.9bc 188.7a 91.3a 28.2ab
D2 217.0ab 182.3ab 90.3ab 28.3ab
D3 172.9bc 159.3abcd 87.5ab 28.5ab
N2 D1 173.1bc 193.2a 92.2a 28.2ab
D2 221.7ab 174.9abc 89.5ab 28.2ab
D3 211.9ab 177.0abc 83.5b 28.5ab
N3 D1 205.8abc 189.2a 91.0a 27.9b
D2 248.3a 177.8abc 90.0ab 28.9a
D3 265.9a 166.7abcd 85.4ab 28.0b
ZZY-8 N0 D1 192.6d 178.7c 83.3abc 22.5a
D2 203.6 cd 193.8bc 86.6a 22.6a
D3 212.1bcd 200.1bc 83.4ab 22.6a
N1 D1 226.6abcd 233.8ab 81.5abcd 22.8a
D2 247.3abc 230.1ab 80.3abcd 22.6a
D3 233.9abcd 237.7ab 81.0abcd 22.1a
N2 D1 236.3abcd 250.9a 80.1abcd 22.5a
D2 242.2abcd 246.1a 78.4bcde 22.7a
D3 262.5ab 245.2a 81.4abcd 22.5a
N3 D1 246.8abc 249.1a 75.4de 22.6a
D2 264.8ab 247.5a 70.9e 22.8a
D3 271.5a 251.1a 75.7cde 22.6a
C-LYHZ N0 D1 201.2e 183.3b 86.3a 20.9a
D2 235.1 cde 181.9b 84.7ab 20.7ab
D3 226.5de 179.6b 84.5ab 20.9a
N1 D1 292.0ab 211.8ab 79.0abc 20.4ab
D2 308.7ab 214.8ab 78.2abc 20.4ab
D3 285.8abc 212.5ab 80.2abc 21.1a
N2 D1 316.0ab 218.6ab 79.1abc 21.0a
D2 273.9bcd 227.6a 74.9c 19.9b
D3 304.5ab 225.4a 74.3c 20.4ab
N3 D1 333.6a 226.2a 77.0bc 20.7ab
D2 323.9ab 230.1a 73.4c 20.5ab
D3 337.8a 231.5a 73.7c 20.9a
ANOVA Variety (V) ns ns ns ns
Nitrogen (N) ** * ns *
Density (D) * ns ns ns
V*N * ** ns ns
V*D ns ns ns ns
N*D * ns ns ns
V*N*D ns ns ns ns
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†Different lowercase letters within columns indicate significant differences at P < 0.05 across N rates (n = 3).

Different lowercase letters indicate significant differences at P < 0.05 (n = 3).

The effects of N application rate and plant density on percent seed set were not significant (P > 0.05) for the inbred varieties but they were (P < 0.05) for the hybrid varieties. In contrast, grain filling significantly (P < 0.05) decreased with increasing N application rate in hybrid rice varieties. Grain filling in ZZY-8 and C-LYHZ decreased from 85% under N0 to 75% under N3. 1,000-grain weight did not (P > 0.05) change significantly in either rice varietal group across N application rates or planting densities. Interaction analysis showed that N application rate significantly (P < 0.05) influenced panicle number, spikelet number per panicle, percent grain filling, and 1,000-grain weight, whereas planting densities only (P < 0.05) affected significantly panicle number and spikelet number per panicle.

Biomass, nitrogen uptake, and NUE

Total aboveground biomass at maturity significantly (P < 0.05) increased with N application rate and planting density (Tables 5 and 6). At both sites and across N treatments, ordinary hybrids had consistently higher biomass than inbred varieties. Total aboveground biomass for hybrid varieties was 14.3% higher than that for inbred varieties (Tables 5 and 6). Total aboveground biomass at maturity under all N treatments was 10.1% and 33.7% higher in hybrids and inbred varieties compared with the N0 treatment, respectively (Tables 5 and 6). At Jingzhou, N2×D3 was the optimal combination treatment for higher biomass accumulation in both inbred and hybrid varieties. In turn, at Hangzhou, N3×D3 was optimal for elevated biomass accumulation in inbred varieties and N3×D1 was best for increased biomass accumulation in hybrid varieties.

Table 5.

Biomass at maturity, nitrogen uptake, and NUE relative to N application rate and planting density in inbred and hybrid rice at Jingzhou in 2017.

Variety N D Biomass AE RE PFP
(g m−2) (kg kg−1) (%) (kg kg−1)
HHZ N0 D1 764.7d
D2 823.2d
D3 873.6d
N1 D1 1125.0c 31.2c 26.7bc 63.4c
D2 1294.5abc 37.5ab 34.9a 71.1b
D3 1362.6ab 37.8a 36.2a 77.5a
N2 D1 1250.3bc 32.8bc 27.0bc 57.0d
D2 1293.5abc 29.1cd 26.1bc 54.4d
D3 1370.4ab 23.5ef 27.6b 53.3d
N3 D1 1227.1bc 28.6 cd 20.6d 46.0e
D2 1335.7abc 24.5de 22.8 cd 43.1ef
D3 1485.3a 18.8 f 27.2bc 40.7 f
YNSM N0 D1 810.3d
D2 830.2d
D3 870.2d
N1 D1 1290.3bc 36.6a 35.6bc 71.6b
D2 1341.0abc 39.6a 37.9b 73.5b
D3 1480.5ab 38.3a 45.2a 77.4a
N2 D1 1204.5c 31.4b 21.9e 57.3c
D2 1337.4abc 28.8bc 28.2d 54.2 cd
D3 1486.6ab 24.0d 34.3c 53.3d
N3 D1 1352.5abc 25.8cd 24.1e 46.4e
D2 1484.4ab 22.8de 29.1d 43.1ef
D3 1541.9a 18.6e 29.9d 42.1 f
Y-LY900 N0 D1 1216.1de
D2 1518.2ab
D3 1533.0a
N1 D1 1248.8d 8.0b 17.1cd 54.3a
D2 1580.5a 9.3a 39.2a 56.3a
D3 1531.1a 9.4a 34.5b 58.0a
N2 D1 1264.3d 6.5d 8.2e 45.1b
D2 1437.0c 7.0c 30.7b 44.6b
D3 1557.4a 5.0e 32.8b 42.4bc
N3 D1 1157.5e 4.3f 15.2d 37.4cd
D2 1450.2bc 4.2f 20.7c 35.6d
D3 1527.5a 4.1f 20.5c 34.2d
QLYSM N0 D1 1199.2 g
D2 1429.8bcd
D3 1491.3ab
N1 D1 1371.5de 10.3ab 61.7a 58.0a
D2 1483.9abc 9.8b 38.6b 53.7b
D3 1468.8abc 13.0a 15.6c 53.0b
N2 D1 1252.3fg 4.9cd 15.9c 43.3c
D2 1413.3 cd 4.0d 19.5c 39.1d
D3 1538.9a 7.4bc 4.8d 39.0d
N3 D1 1204.4 g 5.2cd 34.3b 35.7e
D2 1309.4ef 3.1d 18.4c 32.4e
D3 1479.4abc 5.8cd 2.4d 33.6e
ANOVA Variety (V) ** * ns ns
Nitrogen (N) ** ** * *
Density (D) * * ns ns
V*N ** ns * *
V*D ns ns ns ns
N*D ns ns ns ns
V*N*D ** ns ns ns
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†Different lowercase letters within columns indicate significant differences at P < 0.05 across N rates (n = 3).

Table 6.

Biomass at maturity, nitrogen uptake, and NUE relative to N application rate and planting density in inbred and hybrid rice at Hangzhou in 2018.

Variety N D Biomass AE RE PFP
(g m−2) (kg kg−1) (%) (kg kg−1)
HHZ N0 D1 781.2f
D2 1007.4ef
D3 1134.6e
N1 D1 1393.5d 15.7f 32.6b 67.6c
D2 1580.4 cd 21.3a 31.5bc 72.8b
D3 1827.4abc 19.6bcd 39.3a 77.7a
N2 D1 1459.8d 18.8d 25.4e 56.5de
D2 1458.1d 21.0ab 22.0f 58.4d
D3 1976.8a 17.1ef 28.9 cd 59.3d
N3 D1 1593.7bcd 18.5de 27.1de 48.1 f
D2 1611.5bcd 19.3cd 17.3g 48.7 f
D3 1831.3ab 20.6abc 18.7g 53.8e
YD-6 N0 D1 1076.5bcd
D2 1112.5bcd
D3 1020.7cd
N1 D1 1031.8 cd 10.7f 14.9c 55.7b
D2 1340.1ab 14.6bc 17.1b 64.1a
D3 1613.7a 13.5cde 14.5c 67.9a
N2 D1 898.4d 19.3a 14.4c 52.0b
D2 1156.8bcd 15.9b 19.8a 51.9bc
D3 1240.2bc 14.1bcd 11.3d 53.7b
N3 D1 1041.1cd 11.7ef 11.6d 37.4d
D2 1350.8ab 12.4def 11.7d 40.7d
D3 1586.9a 15.9b 14.8c 47.0c
ZZY-8 N0 D1 1093.9e
D2 1077.0e
D3 1761.6abc
N1 D1 1237.9de 15.5bc 10.2g 70.0b
D2 1640.5abc 23.7a 20.2b 80.5a
D3 1936.0a 10.6e 32.9a 70.1b
N2 D1 1383.5cde 17.0b 15.3de 56.7c
D2 1671.4abc 14.7c 18.7c 56.0c
D3 1588.7abcd 16.4bc 16.2d 59.7c
N3 D1 1532.7bcd 12.8d 15.0e 43.9d
D2 1908.0ab 10.7e 19.9b 43.1d
D3 1854.1ab 10.2e 11.9f 44.2d
C-LYHZ N0 D1 1155.5f
D2 1373.5def
D3 1727.7bc
N1 D1 1271.9ef 14.2d 15.3d 72.1c
D2 1595.6 cd 16.3bcd 20.2b 76.2b
D3 1915.3ab 21.1a 14.6d 79.3a
N2 D1 1271.4ef 18.2b 14.0d 60.3d
D2 1663.1c 11.7e 18.0c 55.3e
D3 2025.2a 17.1bc 20.8b 59.4d
N3 D1 1507.7cde 15.5 cd 17.5c 48.5f
D2 1944.6ab 14.8d 25.3a 49.1f
D3 2098.2a 14.5d 17.3c 47.8f
ANOVA Variety (V) ** * ns ns
Nitrogen (N) ** ** * *
Density (D) * * ns ns
V*N ** ns * *
V*D ns ns ns ns
N*D ns ns ns ns
V*N*D ** ns ns ns
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†Different lowercase letters within columns indicate significant differences at P < 0.05 across N rates (n = 3).

Nitrogen uptake and NUE varied among treatments (Tables 5 and 6). N uptake and NUE under the various N application rates and planting densities were similar at both sites. Inbred varieties showed higher AE, RE, and PFP than hybrids. AE and PFP significantly (P < 0.05) increased with planting density at low N rates (N1) but significantly (P < 0.05) decreased with increasing planting density at high N rates (N2 and N3) for both types of variety. RE increased with planting density but decreased with N application rate. AE, RE, and PFP were 24.6%, 28.0%, and 33.3% higher in inbred varieties and 32.2%, 29.3%, and 35.0% higher in hybrid varieties under the N1 treatment relative to N3 (Tables 5 and 6). At Jingzhou, N1×D3 was optimal for higher AE, RE, and PFP for both inbred and hybrid varieties. In turn, at Hangzhou, N1×D3 was optimal for higher AE, RE, and PFP in hybrid varieties, while N1×D2 was optimal for higher AE, RE, and PFP in inbred varieties.

Correlation analyses of grain yield, yield components, and biomass at various nitrogen application rates and planting densities

Correlation matrices among the various grain yield components and biomass parameters for inbred and hybrid varieties are shown in Figs. 2 and 3. N application rate significantly (P < 0.01) and positively correlated with GY, P, SP, DMF, and DMAF for the inbred varieties and with GY, P, and DMF for the hybrid varieties. Additionally, there was a significant (P < 0.01) positive correlation between D and DMAF for both the inbred and hybrid varieties. The significant (P < 0.01) positive correlations among GY, P, SP, DMF, and DMAF were identical for the inbred and hybrid varieties. However, GF was significantly (P < 0.05) and negatively correlated with GY for both inbred and hybrid varieties.

Figure 2.

Figure 2

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Correlation matrix of various grain yield parameters and biomass in inbred rice (n = 42). N, nitrogen application rate; D, planting density; P, panicles m-2; S, spikelets per panicle; GF, percent seed set; GW, 1,000-grain weight; DMF, dry matter production at flowering; DMAF, dry matter production after flowering; Y, grain yield. Numbers are determination coefficients. *P < 0.05. **P < 0.01.

Figure 3.

Figure 3

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Correlation matrix of various grain yield parameters and biomass in hybrid rice (n = 48). N, nitrogen application rate; D, planting densities; P, panicles m-2; S, spikelets per panicle; GF, percent seed set; GW, 1,000-grain weight; DMF, dry matter production at flowering; DMAF, dry matter production after flowering; Y, grain yield. Numbers are determination coefficients. *P < 0.05. **P < 0.01.

Discussion

Several studies have confirmed that super hybrid rice varieties had higher yields than ordinary hybrids or inbred varieties20,23,24. However, it is not conclusively known whether the same holds under conditions of high planting density and reduced nitrogen application rate. The present study compared yield and NUE for inbred and hybrid rice varieties cultivated under different N rates and planting densities. Neither super nor ordinary hybrid varieties surpassed inbred varieties in terms of grain yield or NUE.

Neither the super hybrid rice variety (Y-LY900) nor the ordinary hybrid rice varieties (ZZY-8, C-LYHZ and QLYSM) showed any significant advantage over the inbred varieties (HHZ and YNSM) with regard to grain yield. There were no significant differences in grain yield among varieties or across N treatments, except relative to N0 (Tables 1 and 2). A two-year field experiment conducted by Hou et al.18 revealed that the average grain yield of rice hybrid Liangyou 3905 was ca 9.2 ton ha−1 even under optimal 165 kg N ha−1 and 24–27 × 104 hills ha–1 planting density. Here, the average grain yield for inbred varieties under N1 (135 kg N ha−1) were 9.8 ton ha−1 at Jiangzhou and 8.1 ton ha−1 under N1 (120 kg N ha−1) at Hangzhou. Thus, inbred varieties achieved equal or higher grain yield than super/ordinary hybrid varieties and are relatively less dependent on exogenous nitrogen application. Huang et al.15 proposed that high planting density at reduced nitrogen application rate increases grain yield and NUE in hybrid rice varieties even under low light-intensity stress. However, our previous studies showed that super/ordinary hybrid varieties are more sensitive to shade stress than inbred rice varieties. Shade stress at flowering caused substantially higher yield losses by super/ordinary hybrid rice varieties than it did for inbred rice varieties25,26. Inbred rice varieties may be better suited for high planting density at reduced nitrogen application rate than super/ordinary hybrid rice varieties.

Inbred varieties can attain equal or higher grain yield than hybrid varieties under high planting density in combination with reduced nitrogen application rate, as the former showed superior sources and sinks. High planting density and low nitrogen application rate markedly increased panicle number and spikelets per panicle in inbred varieties, compared with hybrid varieties. Correlation analyses showed that N was significantly (P < 0.01) and positively correlated with panicle number, spikelets per panicle, biomass production at flowering, and biomass production after flowering in inbred varieties. In contrast, N was significantly (P < 0.01) and positively correlated only with panicle number and biomass production at flowering in hybrid rice varieties. Compared to N0, under the other N treatments evaluated here, the number of panicles increased by 22.1% and by 32.1% in the hybrid and in the inbred varieties, respectively (Tables 3 and 4). Similarly, the number of spikelets per panicle increased by 27.0% in the inbred varieties but only by 9.9% in the hybrid varieties (Tables 3 and 4). The relatively higher number of panicles and number of spikelets per panicle in inbred varieties were attributed to an increase in number of tillers at higher planting density27. Thus, a higher planting density compensated for the negative effect of a reduced N application rate for inbred rice but not for super hybrid rice, in which case, high yield was attributed to an increase in the number of spikelets per panicle and to a greater biomass production. These factors did not apply to ordinary hybrids or inbred cultivars20–22. In contrast, these advantages were not observed at high planting density combined with reduced nitrogen application rate. Hybrid and super hybrid rice cultivars often achieve high yields under optimum growing conditions, especially at high N input. Thus, hybrid and super hybrid rice may perform better than inbred rice only at high N application rate20,28–30. Here, hybrids did not show any advantage over inbred varieties with respect to number of panicles per square meter, number of spikelets per panicle, or biomass production at low N input rate combined with high planting density. Hybrids had higher grain weight than inbred varieties but this discrepancy did not compensate for the detrimental treatment effects of reduced N rate.

Hybrid rice is well adapted to high N fertilizer conditions and requires large amounts of N fertilizer to produce high yields. Consequently, farmers tend to apply substantial quantities of N fertilizer aiming to ensure high grain yields. However, heavy N fertilizer application may result in low NUE because of ammonia volatilization, denitrification, surface runoff, and leaching into the soil floodwater system31,32. Numerous improvements in N fertilizer management practice have been developed to increase NUE in rice production. High planting density at low N input rates is widely regarded as a sustainable strategy to improve NUE. Nevertheless, few studies have focused on the relative differences in NUE between inbred and hybrid varieties sown at high density and reduced nitrogen application rate.

The response of NUE to high planting density at low nitrogen input rate observed in the experiments reported herein were consistent with previously reported results18,19,27. Compared with high N application rate, AE, RE and PFP increased by 24.6%, 28.0% and 33.3% in inbred varieties, and by 32.2%, 29.3% and 35.0% in hybrid varieties, respectively, under low N application rate (Table 5 and Table 6). Therefore, this type of management practice effectively improved NUE in both hybrids and inbred cultivars. Moreover, inbred varieties showed higher NAE, NRE, and PFP than hybrid rice varieties across nitrogen treatments. To the best of our knowledge, this study is the first to compare NUE between inbred and hybrid rice varieties planted at high density and low N input rate. Enhanced NUE in inbred varieties was attributed to their comparatively lower N requirements for growth and yield formation than those of hybrid varieties. NUE was negatively correlated with N application rate33. Excessive N fertilizer application resulted in high soil residual nitrate levels34. Increased soil residual-nitrate may increase the risk of nitrate leaching and low NUE. High planting density at reduced nitrogen application rate enabled inbred rice varieties to achieve both high grain yield and high NUE.

Conclusions

Our study demonstrated that a higher number of panicles and of spikelets per square meter largely explained the comparatively higher yield of inbred rice varieties cultivated under high planting density combined with reduced nitrogen input rate. Furthermore, inbred varieties showed higher nitrogen absorption efficiency, nitrogen recovery rate, and partial factor productivity than hybrids under all nitrogen treatments. Increasing planting density may compensate for the negative effects of a reduced nitrogen application rate in inbred varieties. Thus, high planting density combined with reduced nitrogen application rate is better suited for rice production if inbred, rather than hybrid varieties, is used.

Methods

Site description

Field experiments were conducted in the experimental farm at Yangtze University, Jingzhou, in 2017 and in Hangzhou, Zhejiang Province in 2018. Before transplanting and fertilizing, five soil cores were collected diagonally from the 0–20 cm soil layer in the rice paddy at the two sites, and basic soil properties were analyzed after Lu35. The soil at the Jingzhou site was calcareous alluvial with pH 6.8, 18.5 g kg−1 organic matter, 110.5 mg kg−1 alkali-hydrolysable N, 25.0 mg kg−1 available P, and 105.5 mg kg−1 available K. The soil at the Hangzhou site was a sandy loam with pH 7.0, 7.1 g kg−1 organic matter, 237 mg kg−1 alkali-hydrolyzable N, 17.1 mg kg−1 available P, and 139 mg kg−1 available K.

Urea at 50%, 20%, 20%, and 10% was applied at transplanting, tillering, panicle initiation (PI), and heading, respectively. There were two split potassium applications in the form of KCl. The rate was 40 kg K2O ha-1 and 50% was applied as a basal dressing and 50% was applied as broadcast at PI. Phosphorus and zinc were broadcast as basal fertilizer in the forms of calcium superphosphate at a rate of 30 kg P2O5 ha−1 and zinc sulfate at a rate of 5 kg ZnSO4 ha−1. Crop management followed standard cultural practices. Insects were intensively controlled with pesticides to avoid biomass and yield losses.

Experimental design

Treatments were arranged in a split-split plot design with N treatment as the main plot, planting density as the subplot, and varieties as sub-subplot. Three replications were included each year. Each plot was 30 m2. Hybrid varieties Zhongzheyou8 (ZZY-8) and C-liangyouhuazhan (C-LYHZ), and inbred varieties Huanghuazhan (HHZ) and Yangdao 6 (YD-6) were grown at Hangzhou. Hybrid varieties Y-liangyou900 (Y-LY900) and Quanliangyouhuazhan (QLYSM), and inbred varieties Huanghuazhan (HHZ) and Yuenongsimiao (YNSM) were grown at Jingzhou. These varieties are extensively planted in southern China. Varietal specifications are listed in Table 7.

Table 7.

Rice varieties used in this study.

Variety Group Year of release Female parent Male parent
Huanghuazhan (HHZ) Inbred 2005 Huangxianzhan Fenghuazhan
Yuenongsimiao (YNSM) Inbred 2011 Huanghuazhan Yuetai13
Yangdao6 (YD-6) Inbred 1997 Yangdao4 Yan3021
Yliangyou900 (Y-LY900) Hybrid 2015 Y58S R900
Cliangyouhuazhan (CLYHZ) Hybrid 2015 C815S Huazhan
Quanliangyousimiao (QLYSM) Hybrid 2017 Quan211S Wushansimiao
Zhongzheyou8 (ZZY-8) Hybrid 2006 ZhongzheA T-8
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Nitrogen application rates and planting densities for inbred and hybrid varieties at Jingzhou and Hangzhou are listed in Table 8. Pre-geminated seeds were sown in a seedbed on 10 May in 2017 and on 13 May in 2018. 25-d old seedlings were transplanted on 5 June 2017 and on 7 June 2018.

Table 8.

Nitrogen rates (N) and planting densities (D) for inbred and hybrid rice varieties at Jingzhou(2017) and Hangzhou(2018).

Site Variety N (kg N ha−1) D (plants m−2)
N0 N1 N2 N3 D1 D2 D3
Jingzhou Inbred 0 135 180 225 74.0 83.2 95.2
Hybrid 0 180 225 270 37.0 41.6 47.6
Hangzhou Inbred 0 120 165 210 60.4 78.0 95.6
Hybrid 0 165 195 225 27.0 36.0 45.0
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Crop management

Urea at 50%, 20%, 20%, and 10% was applied at transplanting, tillering, panicle initiation (PI), and grain filling, respectively. There were two split potassium applications using KCl at a rate of 40 kg K2O ha−1; 50% was applied as a basal dressing and 50% was applied as broadcast at PI. Phosphorus and zinc were broadcast as basal fertilizer as calcium superphosphate at a rate of 30 kg P2O5 ha−1, and zinc sulfate at a rate of 5 kg ZnSO4 ha−1. Crop management followed standard cultural practices. Insects were intensively controlled with pesticides to avoid biomass or yield losses.

Sampling and measurements

At tillering, plant samples were separated into straw and leaves. Then, at flowering and maturity, plant samples were separated into straw, leaves, and panicles for dry weight determination after oven-drying to constant weight at 70 °C. At maturity, twelve hills were diagonally sampled over a 5-m2 harvest area on each plot. Three border lines were excluded to avoid border effects. Plants were hand-threshed after counting the panicles. Filled and unfilled spikelets were separated by submersion in tap water. Three 30 g of filled grain and 3 g of unfilled spikelet subsamples were removed to count the spikelets. Filled and unfilled spikelets were identified and separated after oven-drying to constant weight at 70 °C. Spikelets per panicle and grain filling percentage (100 × filled spikelet number / total spikelet number) were calculated. Grain yield was determined from a 5-m2 area in the middle of each subplot and adjusted to a moisture content of 0.14 g H2O g−1 fresh weight.

Dried leaf, stem, and panicle samples were collected at heading and straw and filled- and unfilled spikelets collected at maturity were pulverized and their N content was measured with a Skalar SAN Plus segmented flow analyzer (Skalar Inc., Breda, The Netherlands). Nitrogen content of was determined by the Kjeldahl method and N uptake in each organ was determined by multiplying its dry weight by its N content. Total N uptake at heading was estimated as the sum of leaf, stem, and panicle N uptake, and total N uptake at maturity was estimated as the sum of straw, filled-, and unfilled spikelet N-uptake.

Nitrogen agronomic efficiency (NAE) was calculated by the following formula: NAE (kg kg–1) = [(grain yield with N treatments - grain yield without N) / amount of N fertilizer applied].

Nitrogen recovery efficiency (NRE) was calculated by the following formula: NRE (%) = [(sum of N content in all aboveground components under N treatment - sum of N content in all aboveground components without N) / amount of N fertilizer applied].

Partial factor productivity (PFP) of applied N was calculated by the following formula: N fertilizer (PFP, kg kg–1) = [grain yield / amount of N fertilizer applied].

Data analysis

Data shown are means subjected to ANOVA for significant differences subsequently separated by the least significant difference (LSD) test at 0.05 and 0.01 levels of significance. ANOVA was also performed on the N application rate, planting density, and their interactive effects. A path analysis of grain yield and yield components was also performed. The statistical software used for these analyses was SPSS v. 17.0 (IBM Corp., Armonk, NY, USA).

Acknowledgements

This work was funded by the National Key Research and Development Program of China (Nos. 2016YFD0300108 and 2018YFD0301306) and the Yangtze University Excellent Doctoral Dissertation Development Program.

Author contributions

J.L,W.D. and Y.B. initiated and designed the research, K.L., J.L. and Y.Z. performed the experiments, J.L., K.L and Y.B. analyzed the data and wrote the manuscript, W.D., C.G., H.L. and X.H. revised and edited the manuscript, and provided advice on the experiments.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Jian Lu, Danying Wang and Ke Liu.

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