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Acta Agronomica Sinica ›› 2021, Vol. 47 ›› Issue (3): 530-545.doi: 10.3724/SP.J.1006.2021.03021

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY • Previous Articles     Next Articles

Construction of critical nitrogen dilution curve based on dry matter in diffe rent organs of summer maize and estimation of grain yield

SU Wen-Nan1,2, XIE Jun2, HAN Juan1,2, LIU Tie-Ning1,2, HAN Qing-Fang1,2,*()   

  1. 1College of Agronomy, Northwest A & F University / Key Laboratory of Crop Physio-ecology and Tillage Science in North-western Loess Plateau, Ministry of Agriculture and Rural Affairs / College of Agronomy, Northwest A&F University, Yangling 712100, Shaanxi, China
    2Institute of Water Saving Agriculture in Arid Areas of China / Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, Shaanxi, China
  • Received:2020-03-26 Accepted:2020-10-14 Online:2021-03-12 Published:2020-11-03
  • Contact: HAN Qing-Fang E-mail:hanqf88@nwafu.edu.cn
  • Supported by:
    study was supported by the National High-Tech Research and Development Programs of China “863 Program” for the 12th Five-Year Plants(2013AA102902);Special Fund for Agro-scientific Research in the Public Interest(201303104);National Natural Science Foundation of China(31601256)

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Abstract:

It is essential to accurate and dynamic diagnosis of plant nitrogen status at vegetative growth stage for the assessment of plant nitrogen demand and the prediction of crop yield as well as the optimization of nitrogen management in maize. Plant-based nitrogen diagnostic tool can be used to optimize nitrogen management in summer maize production. The aim of this study was to develop and verify critical nitrogen concentration dilution curves based on dry matter in different tissue of the plant, and to establish the relationship between relative yield (RY) nitrogen nutrition index (NNI), and accumulated nitrogen deficit (AND) at different growth stages in maize. We conducted a 4-year field study using four nitrogen application rates (0, 150, 225, and 300 kg N hm-2) and two maize cultivars (Zhengda 12 and Shaandan 609) to analyze the effects of nitrogen on dry matter at the vegetative growth stage, and based on leaf dry matter (LDM), stem dry matter (SDM), and plant dry matter (PDM), different critical nitrogen concentration dilution curves were developed. The results showed that the critical nitrogen concentration dilution curves based on LDM, SDM and PDM can well diagnose the nitrogen nutrition status of corn. The yield prediction results of three critical nitrogen concentration dilution curves showed that the relationship between RY and NNI, AND at different growth stages was highly significant, and the values of R 2 were all greater than 0.65, where R 2 was the largest at V12-VT, and the verification of the regression model showed reliable model performance during the V12-VT period, with R 2 values greater than 0.92 and RMSE values less than 10%, which confirmed the stability of the relationship between V12 and VT. Generally, under certain conditions, the critical nitrogen concentration dilution curve based on LDM and SDM can be used to replace the critical nitrogen concentration dilution curve based on PDM. The stable relationship between RY and NNI, RY and AND in V12-VT stage can well explain the change of RY under restricted and unrestricted nitrogen and estimate the yield of summer maize. This study provides the basis for nitrogen management of pre-anthesis to improve maize grain yield.

Key words: critical nitrogen dilution curve, maize, nitrogen nutrition index, accumulated nitrogen deficit

Table 1

Dry matter sampling period from 2014 to 2017"

项目Item V3 (M/D) V6 (M/D) V8 (M/D) V12 (M/D) VT (M/D) R6 (M/D)
2014 6/27 7/12 7/17 7/30 8/13 10/14
2015 6/29 7/15 7/20 8/2 8/17 10/15
2016 7/1 7/14 7/21 7/31 8/15 10/3
2017 6/29 7/13 7/21 8/4 8/13 10/14

Table 2

Nitrogen use efficiencies of ZD and SD from 2014 to 2017"

施氮量
Nitrogen rate		 品种
Cultivar		 氮肥偏生产力
Partial factor productivity nitrogen
(PFPN, kg kg-1)		 氮肥回收效率
Recovery efficiency of nitrogen
(REN, %)		 氮素利用效率
Nitrogen utilization efficiency
(NutE, kg kg-1)		 氮素吸收效率
Nitrogen uptake efficiency
(NupE, kg kg-1)
2014 2015 2016 2017 2014 2015 2016 2017 2014 2015 2016 2017 2014 2015 2016 2017
N0 ZD 79.1 a 78.4 a 71.0 a 72.6 a 69.5 a 76.6 a 79.9 a 98.0 a
SD 73.0 b 69.9 b 61.2 b 63.3 b 62.1 b 64.6 b 66.8 b 76.9 b
N150 ZD 62.7 a 67.9 a 64.9 a 70.1 a 36.2 a 44.9 a 45.3 a 39.5 a 60.9 a 59.0 a 51.4 a 57.6 a 35.6 a 36.9 a 37.3 a 40.4 a
SD 54.3 b 55.4 b 56.9 b 58.3 b 29.8 b 36.6 b 34.4 b 39.3 a 57.6 b 52.7 b 49.2 b 49.1 b 30.8 b 30.1 b 31.7 b 32.0 b
N225 ZD 46.7 a 49.2 a 50.8 a 50.8 a 40.7 a 43.5 a 38.0 a 39.3 a 54.9 a 54.5 a 54.9 a 53.9 a 30.7 a 30.3 a 30.5 a 24.3 a
SD 39.7 b 40.8 b 43.5 b 44.3 b 38.1 b 36.9 b 34.4 b 37.7 a 48.9 b 49.5 b 49.0 b 48.9 b 26.1 b 25.2 b 25.7 b 20.7 b
N300 ZD 34.0 a 35.7 a 37.6 a 36.7 a 35.4 a 35.9 a 37.0 a 32.6 a 49.4 a 50.2 a 48.2 a 49.8 a 24.4 a 23.7 a 24.5 a 18.4 a
SD 30.3 b 30.8 b 32.4 b 32.8 b 34.7 a 34.2 a 32.6 b 34.2 a 45.3 a 45.1 b 44.2 b 44.3 b 21.8 b 20.5 b 20.8 b 15.6 b
方差分析 品种Cultivar (C) ** ** ** ** ** ** ** ns ** ** ** ** ** ** ** **
ANOVA 氮肥Nitrogen rate (N) ** ** ** ** ** ** ns ns ** ** ** ** ** ** ** **
品种×氮肥C×N ** ** ns ** ns ** ns ns * ** ns ** ns ** ** **

Fig. 1

Comparison of critical N dilution curves of two maize hybrids on different bases (leaf dry matter basis, stem dry matter basis, and plant dry matter basis) with varied nitrogen rates SD: Shaandan 609; ZD: Zhengda 12; Nc: critical value of shoot nitrogen concentration; LDM: leaf dry matter basis; SDM: stem dry matter basis; PDM: plant dry matter. Shaandan 609 is marked by “○”, Zhengda 12 is marked by “●”; “──” means the curves of Shaandan 609, “- - -” means the curves of Zhengda 12. ** indicates significant difference at P < 0.01."

Table 3

Calibration of critical N dilution curve basis on leaf dry matter, stem dry matter and plant dry matter in maize"

参数
Parameter		 正大12 Zhengda 12 陕单609 Shaandan 609
RMSE n-RMSE RMSE n-RMSE
叶片Leaf 0.043 1.799 0.032 1.354
茎Stem 0.192 16.733 0.048 3.549
植株Plant 0.148 9.135 0.088 4.996

Fig. 2

Validation of the N c dilution curve using data from experiments performed from 2016 to 2017 The symbols (○) and (×) represent non-N-limiting and N-limiting values from 2016 to 2017, respectively. The solid curved lines a, b, and c represent the Nc dilution curves of the leaf, stem, and plant of Shandan 609, respectively, and the solid curved lines d, e, and f represent the Nc dilution curves of the leaf, stem, and plant of Zhengda 12, respectively. The dotted lines on either side represent the curves for the minimum limits, which are developed using data from N-limiting (◇) and non-N-limiting (△) treatments from 2014 to 2015. Nmin and Nmax are minimum and maximum of nitrogen concentration; LDM: leaf dry matter basis; SDM: stem dry matter basis, PDM: plant dry matter. ** indicates significant difference at P < 0.01."

Fig. 3

Relationships between relative yield (RY) and the nitrogen nutrition index (NNI), relative yield (RY) and the accumulated nitrogen deficit (AND) of two maize hybrids with varied N rates on the base of leaf dry matter N dilution curves V3, V6, V8, V12, VT and R6 represent the third, sixth, eighth, twelfth leaf stages, tasseling and physiological maturity stages, respectively. SD: Shaandan 609; ZD: Zhengda 12; Shaandan 609 is marked by “△”, Zhengda 12 is marked by “◇”; “──” means the curves of Shandan 609, “……” means the curves of Zhengda 12. ** indicates significant difference at P < 0.01."

Fig. 4

Relationships between relative yield (RY) and the nitrogen nutrition index (NNI), relative yield (RY) and the accumulated nitrogen deficit (AND) of two maize hybrids with varied N rates on the bases of stem dry matter N dilution curves Abbreviations and symbols are the same as those given in Fig. 3. ** indicates significant difference at P < 0.01."

Fig. 5

Relationships between relative yield (RY) and the nitrogen nutrition index (NNI), relative yield (RY) and the accumulated nitrogen deficit (AND) of two maize hybrids with varied N rates on the bases of plant dry matter N dilution curves Abbreviations and symbols are the same as those given in Fig. 3. ** indicates significant difference at P < 0.01."

Table 4

Values of RMSE, n-RMSE and R2 for prediction of relative yield (RY) from nitrogen nutrition index (NNI), and accumulated nitrogen deficit (AND), respectively, at different growth stages using data obtained in 2016 and 2017"

部位
Organ or plant		 品种
Cultivar		 参数
Parameter		 氮亏缺Accumulated nitrogen deficit (AND) 氮营养指数Nitrogen nutrition index (NNI)
V3 V6 V8 V12 VT V3 V6 V8 V12 VT
叶片
Leaf		 正大12 RMSE 0.08 0.08 0.09 0.03 0.05 0.08 0.12 0.08 0.05 0.05
Zhengda 12 n-RMSE 9.10 9.04 10.41 3.51 5.23 8.85 13.65 8.39 5.72 5.31
R2 0.90 0.89 0.86 0.98 0.96 0.90 0.76 0.91 0.95 0.96
陕单609 RMSE 0.11 0.06 0.08 0.05 0.05 0.08 0.07 0.07 0.03 0.05
Shaandan 609 n-RMSE 12.40 6.86 8.69 5.81 5.40 8.80 8.12 7.90 2.82 5.11
R2 0.83 0.93 0.88 0.95 0.95 0.88 0.90 0.90 0.98 0.96
茎
Stem		 正大12 RMSE 0.11 0.10 0.10 0.06 0.06 0.08 0.10 0.06 0.06 0.06
Zhengda 12 n-RMSE 11.83 10.66 10.96 7.16 6.67 8.81 11.40 6.46 6.79 6.49
R2 0.83 0.85 0.84 0.93 0.94 0.90 0.82 0.94 0.94 0.94
陕单609 RMSE 0.10 0.10 0.06 0.04 0.04 0.06 0.08 0.05 0.04 0.03
Shaandan 609 n-RMSE 11.00 11.12 6.35 3.92 4.18 6.46 9.14 5.57 4.74 3.16
R2 0.87 0.81 0.94 0.97 0.97 0.93 0.87 0.95 0.96 0.98
植株
Plant		 正大12 RMSE 0.15 0.09 0.07 0.06 0.04 0.10 0.09 0.06 0.06 0.04
Zhengda 12 n-RMSE 17.09 9.87 7.81 6.11 4.63 10.70 9.97 7.03 6.57 4.38
R2 0.65 0.88 0.92 0.95 0.97 0.86 0.88 0.94 0.94 0.97
陕单609 RMSE 0.12 0.10 0.08 0.04 0.07 0.08 0.09 0.04 0.03 0.04
Shaandan 609 n-RMSE 13.47 11.25 8.32 4.65 7.85 9.24 9.42 4.91 3.03 4.93
R2 0.80 0.86 0.92 0.97 0.93 0.91 0.90 0.97 0.99 0.97

Table 5

Prediction models for estimation of relative yield (RY) from nitrogen nutrition index (NNI) and accumulated nitrogen deficit (AND) at V12 and VT stage using pooled data of four years"

处理
Treatment		 生育时期
Growth stage		 R2 回归方程
Regression equation (RY-AND)		 R2 回归方程
Regression equation (RY-NNI)
ZD leaf V12 0.94 RY = 1.081-0.026AND if AND > 3.5 and RY = 0.99 AND ≤ 3.5 0.96 RY = -0.01+NNI if NNI<0.95 and RY = 0.99 NNI ≥ 0.95
VT 0.95 RY = 1.138-0.028AND if AND > 5.3 and RY = 0.99 AND ≤ 5.3 0.96 RY = -0.033+1.1NNI if NNI<0.93 and RY = 0.99 NNI ≥ 0.93
SD leaf V12 0.98 RY = 1.010-0.019AND if AND > 0.5 and RY = 1 AND ≤ 0.5 0.98 RY = 0.284+0.688NNI if NNI<1.04 and RY = 1 NNI ≥ 1.04
VT 0.98 RY = 0.997-0.017AND if AND > 0.4 and RY = 0.99 AND ≤ 0.4 0.98 RY = 0.271+0.705NNI if NNI<1.02 and RY = 0.99 NNI ≥ 1.02
ZD stem V12 0.97 RY = 1.079-0.023AND if AND > 3.6 and RY = 0.99 AND ≤ 3.6 0.97 RY = 0.418+0.615NNI if NNI<0.93 and RY = 0.99 NNI ≥ 0.93
VT 0.98 RY = 1.182-0.024AND if AND > 8 and RY = 0.99 AND ≤ 8 0.98 RY = 0.414+0.678NNI if NNI<0.85 and RY = 0.99 NNI ≥ 0.85
SD stem V12 0.98 RY = 1.014-0.016AND if AND > 1.5 and RY = 0.99 AND ≤ 1.5 0.98 RY = 0.494+0.506NNI if NNI<1 and RY = 1 NNI ≥ 1
VT 0.98 RY = 1.006-0.01AND if AND > 1.6 and RY = 0.99 AND ≤ 1.6 0.99 RY = 0.565+0.405NNI if NNI < 1.05 and RY = 0.99 NNI ≥ 1.05
ZD plant V12 0.97 RY = 1.148-0.015AND if AND > 10.5 and RY = 0.99 AND ≤ 10.5 0.97 RY = 0.188+0.881NNI if NNI < 0.91 and RY = 0.99 NNI ≥ 0.91
VT 0.98 RY = 1.072-0.01AND if AND > 8.2 and RY = 0.99 AND ≤ 8.2 0.98 RY = 0.139+0.886NNI if NNI < 0.96 and RY = 0.99 NNI ≥ 0.96
SD plant V12 0.98 RY = 1.048-0.01AND if AND > 4.8 and RY = 1 AND ≤ 4.8 0.99 RY = 0.351+0.669NNI if NNI < 0.97 and RY = 1 NNI ≥ 0.97
VT 0.98 RY = 1.013-0.005AND if AND > -4.6 and RY = 0.99 AND ≤ -4.6 0.98 RY = 0.412+0.556NNI if NNI < 1.06 and RY = 1 NNI ≥ 1.06

Table 6

Comparison of parameters of critical N dilution curves based on different organs and other model parameters"

部位
Organ		 作物
Crop		 地点
Site		 a b 参考文献
Reference
植株 玉米Maize 关中平原Guanzhong Plain 2.25 0.27 Li Z P et al.[29]
Plant 黄淮海平原Huanghuaihai Plain 3.34 0.396 Liang X G et al.[38]
华北平原North China Plain 2.72 0.27 Yue S C et al.[37]
本试验This study 2.47 0.24
2.33 0.26
叶片 玉米Maize 黄淮海平原Huanghuaihai Plain 3.45 0.22 Zhao B et al.[10]
Leaf 水稻Rice 长江中下游平原the Middle-Lower Yangtze Plains 3.76 0.22 Wang X L[44]
小麦Wheat 长江中下游平原the Middle-Lower Yangtze Plains 3.06 0.15 Yao X et al.[23]
关中平原Guanzhong Plain 3.96 0.14 Qiang S C et al.[45]
本试验This study 2.64 0.20
2.61 0.21
茎 小麦Wheat 长江中下游平原the Middle-Lower Yangtze Plains 2.50 0.44 Wang X L [44]
Stem 水稻Rice 长江中下游平原the Middle-Lower Yangtze Plains 2.26 0.32 Ata-Ul-Karim S T et al.[22]
本试验This study 1.58 0.39
1.83 0.34
[1] Erisman J W, Sutton M A, Galloway J, Klimont Z, Winiwarter W. How a century of ammonia synthesis changed the world. Nat Geosci, 2008,1:636-639.
[2] 王西娜, 王朝辉, 李生秀. 施氮量对夏季玉米产量及土壤水氮动态的影响. 生态学报, 2007,27(1):197-204.
Wang X N, Wang Z H, Li S X. The effect of nitrogen fertilizer rate on summer maize yield and soil water nitrogen dynamics. Acta Ecol Sin, 2007,27(1):197-204 (in Chinese with English abstract).
[3] Ramanantenasoa M M J, Génermont S, Gilliot J M, Makowski D. Metamodeling methods for estimating ammonia volatilization from nitrogen fertilizer and manure applications. J Environ Manag, 2019,236:195-205.
[4] Galloway J N, Cowling E B. Reactive nitrogen and the world: 200 years of change. Ambio, 2002,3:64-71.
[5] 宁芳, 张元红, 温鹏飞, 王瑞, 王倩, 董朝阳, 贾广灿, 李军. 不同降水状况下旱地玉米生长与产量对施氮量的响应. 作物学报, 2019,45:777-791.
Ning F, Zhang Y H, Wen P F, Wang R, Wang Q, Dong Z Y, Jia G C, Li J. Responses of maize growth and yield to nitrogen application in dryland under different precipitation conditions. Acta Agron Sin, 2019,45:777-791 (in Chinese with English abstract).
[6] Zhao B, Ata-Ul-Karim S T, Liu Z D, Zhang J Y, Xiao J F, Liu Z G, Qin A Z, Ning D F, Yang Q X, Zhang Y H, Duan A W. Simple assessment of nitrogen nutrition index in summer maize by using chlorophyll meter readings. Front Plant Sci, 2018,9:11.
doi: 10.3389/fpls.2018.00011 pmid: 29403521
[7] Zhao B, Liu Z D, Ata-Ul-Karim S T, Xiao J F, Liu Z G, Qi A Z, Ning D F, Nan J Q, Duan A W. Rapid and nondestructive estimation of the nitrogen nutrition index in winter barley using chlorophyll measurements. Field Crops Res, 2016,185:59-68.
[8] Justes E, Mary B, Meynard J M, Machet J M, Thelier-Huche L. Determination of A critical nitrogen dilution curve for winter-wheat Crops. Ann Bot, 1994,74:397-407.
[9] Ata-Ul-Karim S T, Yao X, Liu X J, Cao W X, Zhu Y. Development of critical nitrogen dilution curve ofjaponica rice in Yangtze River Reaches. Field Crops Res, 2013,149:149-158.
[10] Zhao B, Ata-Ul-Karim S T, Liu Z, Ning D F, Xiao J F, Liu Z G, Qin A Z, Nan J Q, Duan A W. Development of a critical nitrogen dilution curve based on leaf dry matter for summer maize. Field Crops Res, 2017,208:60-68.
[11] Wang X L, Ye T Y, Ata-Ul-Karim S T, Zhu Y, Liu L L, Cao W X, Tang L. Development of a critical nitrogen dilution curve based on leaf area duration in wheat. Front Plant Sci, 2017,8:1517.
pmid: 28928757
[12] 付江鹏, 贺正, 贾彪, 刘慧芳, 李振洲, 刘志. 滴灌玉米临界氮稀释曲线与氮素营养诊断研究. 作物学报, 2020,46:290-299.
Fu J P, He Z, Jia B, Liu H F, Li Z Z, Liu Z. Critical nitrogen dilution curve and nitrogen nutrition diagnosis of maize with drip irrigation. Acta Agron Sin, 2020,46:290-299 (in Chinese with English abstract).
[13] Ata-Ul-Karim S T, Liu X J, Lu Z Z, Yuan Z F, Zhu Y, Cao W X. In-season estimation of rice grain yield using critical nitrogen dilution curve. Field Crops Res, 2016,195:1-8.
[14] Ata-Ul-Karim S T, Liu X J, Lu Z Z, Zheng H B, Cao W X, Zhu Y. Estimation of nitrogen fertilizer requirement for rice crop using critical nitrogen dilution curve. Field Crops Res, 2017,201:32-40.
[15] 岳松华, 刘春雨, 黄玉芳, 叶优良. 豫中地区冬小麦临界氮稀释曲线与氮营养指数模型的建立. 作物学报, 2016,42:909-916.
Yue S H, Liu C Y, Huang Y F, Ye Y L. Simulating critical nitrogen dilution curve and modeling nitrogen nutrition index in winter wheat in central Henan area. Acta Agron Sin, 2016,42:909-916 (in Chinese with English abstract).
[16] Yao Y K, Miao Y X, Cao Q, Wang H Y, Gnyp M L, Bareth G, Khosla R, Yang W, Liu F Y, Liu C. In-season estimation of rice nitrogen status with an active crop canopy sensor. IEEE J-Stars, 2014,7:4403-4413.
[17] Ziadi N, Bélanger G, Claessens A, Lefebvre L, Cambouris A N, Tremblay N, Nolin M C, Parent L E. Determination of a critical nitrogen dilution curve for spring wheat. Agron J, 2010,102:241-250.
[18] Lemaire G, Jeuffroy M H, Gastal F. Diagnosis tool for plant and crop N status in vegetative stage: Theory and practices for crop N management. Eur J Agron, 2008,28:614-624.
[19] Zhang K, Yuan Z F, Yang T C, Lu Z Z, Cao Q, Tian Y C, Zhu Y, Cao W X, Liu X J. Chlorophyll meter-based nitrogen fertilizer optimization algorithm and nitrogen nutrition index for in-season fertilization of paddy rice. Agron J, 2020,112:1-13.
[20] Ziadi N, Brassard M, Bélanger G, Claessens A, Tremblay N, Cambouris A, Nolin M, Parent L E. Chlorophyll measurements and nitrogen nutrition index for the evaluation of corn nitrogen status. Agron J, 2008,100:271-273.
[21] Ata-Ul-Karim S T, Yao X, Liu X J, Cao W X, Zhu Y. Determination of critical nitrogen dilution curve based on stem dry matter in rice. PLoS One, 2014,9:e104540.
doi: 10.1371/journal.pone.0104540 pmid: 25127042
[22] Ata-Ul-Karim S T, Zhu Y, Liu X J, Cao Q, Tian Y C, Cao W X. Comparison of different critical nitrogen dilution curves for nitrogen diagnosis in rice. Sci Rep, 2017,7:42679.
doi: 10.1038/srep42679 pmid: 28262685
[23] Yao X, Zhao B, Tian Y C, Liu X J, Ni J, Cao W X, Zhu Y. Using leaf dry matter to quantify the critical nitrogen dilution curve for winter wheat cultivated in eastern China. Field Crops Res, 2014,159:33-42.
[24] Huang S Y, Miao Y X, Cao Q, Yao Y K, Zhao G M, Yu W F, Shen J N, Yu K, Bareth G. A new critical nitrogen dilution curve for rice nitrogen status diagnosis in Northeast China. Pedosphere, 2018,28:814-822.
[25] Zhao B, Yao X, Tian Y C, Liu X J, Ata-Ul-Karim S T, Ni J, Cao W X, Zhu Y. New critical nitrogen curve based on leaf area index for winter wheat. Agron J, 2014,106:379-383.
[26] Zhao B, Ata-Ui-Karim S T, Yao X, Tian Y C, Cao W X, Zhu Y Liu X J. A new curve of critical nitrogen concentration based on spike dry matter for winter wheat in Eastern China. PLoS One, 2016,11:e164545.
[27] Zhao Z G, Wang E L, Wang Z M, Zang H Z, Liu Y P, Angus J F. A reappraisal of the critical nitrogen concentration of wheat and its implications on crop modeling. Field Crops Res, 2014,164:65-73.
[28] 强生才, 张富仓, 向友珍, 张燕, 闫世程, 邢英英. 关中平原不同降雨年型夏玉米临界氮稀释曲线模拟及验证. 农业工程学报, 2015,31(17):168-175.
Qiang S C, Zhang F C, Xiang Y Z, Zhang Y, Yan S C, Xing Y Y. Simulation and validation of critical nitrogen dilution curve for summer maize in Guanzhong Plain during different rainfall years. Trans CSAE, 2015,31(17):168-175 (in Chinese with English abstract).
[29] 李正鹏, 冯浩, 宋明丹. 关中平原冬小麦临界氮浓度稀释曲线和氮营养指数研究. 农业机械学报, 2015,46(10):177-183.
Li Z P, Feng H, Song M D. Development and validation of critical nitrogen content curve for maize in Guanzhong area. Trans CSAM, 2015,46(10):135-141 (in Chinese with English abstract).
[30] Bremner J M, Mulvancy C S. Nitrogen-total. In: Page A L, Miller R H, Keeney D R, eds. Methods of Soil Analysis. Madison: American Society of Agronomy, 1982. pp 595-624.
[31] Yang J, Greenwood D J, Rowell D L, Wadsworth G A, Burns I G. Statistical methods for evaluating a crop nitrogen simulation model, N_ABLE. Agric Syst, 2000,64:37-53.
[32] Jamieson P D, Porter J R, Wilson D R. A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crops Res, 1991,27:337-350.
[33] He Z Y, Qiu X L, Ata-Ul-Karim S T, Li Y D, Liu X J, Cao Q, Zhu Y, Cao W X, Tang L. Development of a critical nitrogen dilution curve of double cropping rice in south China. Front Plant Sci, 2017,8:638.
doi: 10.3389/fpls.2017.00638 pmid: 28503181
[34] Zhao B, Niu X L, Ata-Ul-Karim S T, Wang L G, Duan A W, Liu Z D, Lemaire G. Determination of the post-anthesis nitrogen status using ear critical nitrogen dilution curve and its implications for nitrogen management in maize and wheat. Eur J Agron, 2020,113:125967.
[35] Song L G, Wang S, Ye W J. Establishment and application of critical nitrogen dilution curve for rice based on leaf dry matter. Agron J, 2020,10:367.
[36] 梁效贵, 张经廷, 周丽丽, 李旭辉, 周顺利. 华北地区夏玉米临界氮稀释曲线和氮营养指数研究. 作物学报, 2013,39:292-299.
Liang X G, Zhang J T, Zhou L L, Li X H, Zhou S L. Critical nitrogen dilution curve and nitrogen nutrition index for summer maize in north China plain. Acta Agron Sin, 2013,39:292-299 (in Chinese with English abstract).
[37] Yue S C, Sun F L, Meng Q F, Zhao R F, Li F, Chen X P, Zhang F S, Cui Z L. Validation of a critical nitrogen curve for summer maize in the North China Plain. Pedosphere, 2014,24:76-83.
[38] Liang X G, Zhang Z L, Zhou L L, Shen S, Gao Z, Zhang L, Lin S, Pan Y Q, Zhou S L. Localization of maize critical N curve and estimation of NNI by Chlorophyll. Int J Plant Prod, 2018,12:85-94.
[39] Novoa R, Loomis R. Nitrogen and plant production. Plant Soil, 1981,58:177-204.
[40] 侯有良, Brien L O, 钟改荣. 小麦不同器官氮素累积分布动态规律的研究. 作物学报, 2001,27:493-499.
Hou Y L, Brien L O, Zhong G R. Study on the dynamic change of the distribution and accumulation of nitrogen in different plant parts of wheat. Acta Agron Sin, 2001,27:493-499 (in Chinese with English abstract).
[41] Sinclair T R, Horie T. Leaf nitrogen, photosynthesis and crop radiation use efficiency: a review. Crop Sci, 1989,29:90-98.
[42] 安志超, 黄玉芳, 汪洋, 赵亚南, 岳松华, 师海斌, 叶优良. 植物营养与肥料学报, 2019,25:123-133.
An Z C, Huang Y F, Wang Y, Zhao Y N, Yue S H, Shi H B, Ye Y L. Critical nitrogen concentration dilution model and nitrogen nutrition diagnosis in summer maize with different nitrogen efficiencies. J Plant Nutr Fert, 2019,25:123-133 (in Chinese with English abstract).
[43] Chen Y L, Xiao C X, Chen X C, Li Q, Zhang J, Chen F J, Yuan L X, Mi G H. Characterization of the plant traits contributed to high grain yield and high grain nitrogen concentration in maize. Field Crops Res, 2014,159:1-9.
[44] 王晓玲. 长江中下游稻麦两熟区冬小麦植株器官临界氮浓度模型构建及氮素诊断调控研究. 南京农业大学博士学位论文, 江苏南京, 2017.
Wang X L. Study on Construction Critical Nitrogen Concentration Dilution Models Based on Plant Organs and Diagnosis and Regulation of Wheat in the Middle and Lower Reaches of the Yangtze River. PhD Dissertation of Graduate School of Nanjing Agricultural University, Nanjing, Jiangsu, China, 2017 (in Chinese with English abstract).
[45] 强生才, 张富仓, 田建柯, 吴悠, 闫世程, 范军亮. 基于叶片干物质的冬小麦临界氮浓度稀释曲线模拟研究. 农业机械学报, 2015,46(11):121-128.
Qiang S C, Zhang F C, Tian J K, Wu Y, Yan S C, Fan J L. Deve lopment of critical nitrogen dilution curve in winter wheat based on leaf dry matter. Trans CSAM, 2015,46(11):121-128 (in Chinese with English abstract).
[46] Stockle C O, Debaeke P. Modeling crop nitrogen requirements: a critical analysis. Eur J Agron, 1997,7:161-169.
[47] 刘朋召, 师祖姣, 宁芳, 王瑞, 王小利, 李军. 不同降雨状况下渭北旱地春玉米临界氮稀释曲线与氮素营养诊断. 作物学报, 2020,46:1225-1237.
Liu P Z, Shi Z J, Ning F, Wang R, Wang X L, Li J. Critical nitrogen dilution curves and nitrogen nutrition diagnosis of spring maize under different precipitation patterns in Weibei dryland. Acta Agron Sin, 2020,46:1225-1237 (in Chinese with English abstract).
[48] Yuan Z F, Ata-Ul-Karim S T, Cao Q, Lu Z Z, Cao W X, Zhu Y, Liu X J. Indicators for diagnosing nitrogen status of rice based on chlorophyll meter readings. Field Crops Res, 2016,185:12-20.
[49] Zhao B, Duan A W, Ata-Ul-Karim S T, Liu Z D, Chen Z F, Gong Z H, Zhang J Y, Xiao J F, Liu Z G, Qin A Z, Ning D F. Exploring new spectral bands and vegetation indices for estimating nitrogen nutrition index of summer maize. Eur J Agron, 2018,93:113-125.
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