PLANT DENSITY, IRRIGATION AND NITROGEN MANAGEMENT: THREE MAJOR PRACTICES IN CLOSING YIELD GAPS FOR AGRICULTURAL SUSTAINABILITY IN NORTH-WEST CHINA
Xiuwei GUO, Manoj Kumar SHUKLA, Di WU, Shichao CHEN, Donghao LI, Taisheng DU
PLANT DENSITY, IRRIGATION AND NITROGEN MANAGEMENT: THREE MAJOR PRACTICES IN CLOSING YIELD GAPS FOR AGRICULTURAL SUSTAINABILITY IN NORTH-WEST CHINA
• A relative yield of 70% was obtained under both border and drip irrigation.
• Drip irrigation saved water and lowered yield variability compared to border irrigation.
• Drip irrigation led to accumulation of soil nitrogen and phosphorus in the root zone.
• Relative yield may increase 8% to 10% by optimizing field management.
• Plant density, irrigation and nitrogen are major factors closing yield gap in NW China.
Agriculture faces the dual challenges of food security and environmental sustainability. Here, we investigate current maize production at the field scale, analyze the yield gaps and impacting factors, and recommend measures for sustainably closing yield gaps. An experiment was conducted on a 3.9-ha maize seed production field in arid north-western China, managed with border and drip irrigation, respectively, in 2015 and 2016. The relative yield reached 70% in both years. However, drip irrigation saved 227 mm irrigation water during a drier growing season compared with traditional border irrigation, accounting for 44% of the maize evapotranspiration (ET). Yield variability under drip irrigation was 12.1%, lower than the 18.8% under border irrigation. Boundary line analysis indicates that a relative yield increase of 8% to 10% might be obtained by optimizing the yield-limiting factors. Plant density and soil available water content and available nitrogen were the three major factors involved. In conclusion, closing yield gaps with agricultural sustainability may be realized by optimizing agronomic, irrigation and fertilizer management, using water-saving irrigation methods and using site-specific management.
boundary line analysis / irrigation method / precision agriculture / spatial variability / yield gaps / yield-limiting factors
[1] |
Foley J A, Ramankutty N, Brauman K A, Cassidy E S, Gerber J S, Johnston M, Mueller N D, O’Connell C, Ray D K, West P C, Balzer C, Bennett E M, Carpenter S R, Hill J, Monfreda C, Polasky S, Rockström J, Sheehan J, Siebert S, Tilman D, Zaks D P M. Solutions for a cultivated planet. Nature, 2011, 478(7369): 337–342
CrossRef
Pubmed
Google scholar
|
[2] |
Mueller N D, Gerber J S, Johnston M, Ray D K, Ramankutty N, Foley J A. Closing yield gaps through nutrient and water management. Nature, 2012, 490(7419): 254–257
CrossRef
Pubmed
Google scholar
|
[3] |
Tilman D, Balzer C, Hill J, Befort B L. Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences of the United States of America, 2011, 108(50): 20260–20264
CrossRef
Pubmed
Google scholar
|
[4] |
Alexandratos N, Bruinsma J. World agriculture towards 2030/2050: the 2012 revision. Rome: FAO, 2012
|
[5] |
Food and Agriculture Organization of the United Nations (FAO). FAOSTAT statistics database. 2017. Avaible at FAO website on May 1, 2019
|
[6] |
Cassman K G, Dobermann A, Walters D T, Yang H S. Meeting cereal demand while protecting natural resources and improving environmental quality. Annual Review of Environment and Resources, 2003, 28(1): 315–358
CrossRef
Google scholar
|
[7] |
Long S P, Marshall-Colon A, Zhu X G. Meeting the global food demand of the future by engineering crop photosynthesis and yield potential. Cell, 2015, 161(1): 56–66
CrossRef
Pubmed
Google scholar
|
[8] |
van Ittersum M K, Cassman K G, Grassini P, Wolf J, Tittonell P, Hochman Z. Yield gap analysis with local to global relevance—a review. Field Crops Research, 2013, 143: 4–17
CrossRef
Google scholar
|
[9] |
Rosegrant M W, Ringler C, Zhu T J. Water for agriculture: maintaining food security under growing scarcity. Annual Review of Environment and Resources, 2009, 34(1): 205–222
CrossRef
Google scholar
|
[10] |
Lu C Q, Tian H Q. Global nitrogen and phosphorus fertilizer use for agriculture production in the past half century: shifted hot spots and nutrient imbalance. Earth System Science Data, 2017, 9(1): 181–192
CrossRef
Google scholar
|
[11] |
Yemefack M, Jetten V G, Rossiter D G. Developing a minimum data set for characterizing soil dynamics in shifting cultivation systems. Soil & Tillage Research, 2006, 86(1): 84–98
CrossRef
Google scholar
|
[12] |
D’Hose T, Cougnon M, De Vliegher A, Vandecasteele B, Viaene N, Cornelis W, Van Bockstaele E, Reheul D. The positive relationship between soil quality and crop production: a case study on the effect of farm compost application. Applied Soil Ecology, 2014, 75: 189–198
CrossRef
Google scholar
|
[13] |
Yang W G, Zheng F L, Han Y, Wang Z L, Yi Y, Feng Z Z. Investigating spatial distribution of soil quality index and its impacts on corn yield in a cultivated catchment of the Chinese mollisol region. Soil Science Society of America Journal, 2016, 80(2): 317–327
CrossRef
Google scholar
|
[14] |
Chen G F, Cao H Z, Liang J, Ma W Q, Guo L F, Zhang S H, Jiang R F, Zhang H Y, Goulding K W T, Zhang F S. Factors affecting nitrogen use efficiency and grain yield of summer maize on smallholder farms in the North China Plain. Sustainability, 2018, 10(2): 363
CrossRef
Google scholar
|
[15] |
Li X, Zhang X, Niu J, Tong L, Kang S, Du T, Li S, Ding R. Irrigation water productivity is more influenced by agronomic practice factors than by climatic factors in Hexi Corridor, Northwest China. Scientific Reports, 2016, 6(1): 37971
CrossRef
Pubmed
Google scholar
|
[16] |
Li X L, Tong L, Niu J, Kang S Z, Du T S, Li S E, Ding R S. Spatio-temporal distribution of irrigation water productivity and its driving factors for cereal crops in Hexi Corridor, Northwest China. Agricultural Water Management, 2017, 179: 55–63
CrossRef
Google scholar
|
[17] |
Shen J B, Zhu Q C, Jiao X Q, Ying H, Wang H L, Wen X, Xu W, Li T Y, Cong W F, Liu X J, Hou Y, Cui Z L, Oenema O, Davies W J, Zhang F S. Agriculture Green Development: a model for China and the world. Frontiers of Agricultural Science and Engineering, 2020, 7(1): 5–13
CrossRef
Google scholar
|
[18] |
Evanylo G K, Sumner M E. Utilization of the boundary line approach in the development of soil nutrient norms for soybean production. Communications in Soil Science and Plant Analysis, 1987, 18(12): 1379–1401
CrossRef
Google scholar
|
[19] |
Schnug E, Heym J, Murphy D P. Boundary line determination technique (BOLIDES). In: Robert P C, Rust R H, Larson W E, eds. Site-specific management for agricultural systems. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 1995, 899–908
|
[20] |
Hajjarpoor A, Soltani A, Zeinali E, Kashiri H, Aynehband A, Vadez V. Using boundary line analysis to assess the on-farm crop yield gap of wheat. Field Crops Research, 2018, 225: 64–73
CrossRef
Google scholar
|
[21] |
Shatar T M, McBratney A B. Boundary-line analysis of field-scale yield response to soil properties. Journal of Agricultural Science, 2004, 142(5): 553–560
CrossRef
Google scholar
|
[22] |
Jiang X L, Tong L, Kang S Z, Li F S, Li D H, Qin Y H, Shi R C, Li J B. Planting density affected biomass and grain yield of maize for seed production in an arid region of Northwest China. Journal of Arid Land, 2018, 10(2): 292–303
CrossRef
Google scholar
|
[23] |
Walkley A. A critical examination of a rapid method for determining organic carbon in soils—effect of variations in digestion conditions and of inorganic soil constituents. Soil Science, 1947, 63(4): 251–264
CrossRef
Google scholar
|
[24] |
van den Berg M, Klamt E, van Reeuwijk L P, Sombroek W G. Pedotransfer functions for the estimation of moisture retention characteristics of Ferralsols and related soils. Geoderma, 1997, 78(3–4): 161–180
CrossRef
Google scholar
|
[25] |
R Core Team. R: A Language and Environment for Statistical Computing (Version 3.5.2). Vienna, Austria: R Foundation for Statistical Computing,2018
|
[26] |
Bartier P M, Keller C P. Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW). Computers & Geosciences, 1996, 22(7): 795–799
CrossRef
Google scholar
|
[27] |
Qin S J, Li S E, Kang S Z, Du T S, Tong L, Ding R S. Can the drip irrigation under film mulch reduce crop evapotranspiration and save water under the sufficient irrigation condition? Agricultural Water Management, 2016, 177: 128–137
CrossRef
Google scholar
|
[28] |
He Q S, Li S E, Kang S Z, Yang H B, Qin S J. Simulation of water balance in a maize field under film-mulching drip irrigation. Agricultural Water Management, 2018, 210: 252–260
CrossRef
Google scholar
|
[29] |
Magdoff F R, Ross D, Amadon J. A soil test for nitrogen availability to corn. Soil Science Society of America Journal, 1984, 48(6): 1301–1304
CrossRef
Google scholar
|
[30] |
Di Matteo J A, Ferreyra J M, Cerrudo A A, Echarte L, Andrade F H. Yield potential and yield stability of Argentine maize hybrids over 45 years of breeding. Field Crops Research, 2016, 197: 107–116
CrossRef
Google scholar
|
[31] |
Doorenbos J, Kassam A H. FAO Irrigation and Drainage Paper 33: Yield response to water. Rome: FAO, 1979
|
[32] |
Panda R K, Behera S K, Kashyap P S. Effective management of irrigation water for maize under stressed conditions. Agricultural Water Management, 2004, 66(3): 181–203
CrossRef
Google scholar
|
[33] |
Cassel D K, Nielsen D R. Field capacity and available water capacity. In: Klute A, eds. Methods of soil analysis: Part 1—physical and mineralogical methods. Madison, WI: Soil Science Society of America, American Society of Agronomy, 1986, 901–926
|
[34] |
Bhattarai S P, Su N H, Midmore D J. Oxygation unlocks yield potentials of crops in oxygen-limited soil environments. Advances in Agronomy, 2005, 88: 313–377
CrossRef
Google scholar
|
[35] |
Perego A, Basile A, Bonfante A, De Mascellis R, Terribile F, Brenna S, Acutis M. Nitrate leaching under maize cropping systems in Po Valley (Italy). Agriculture, Ecosystems & Environment, 2012, 147: 57–65
CrossRef
Google scholar
|
[36] |
Farooq M, Hussain M, Wakeel A, Siddique K H M. Salt stress in maize: effects, resistance mechanisms, and management. A review. Agronomy for Sustainable Development, 2015, 35(2): 461–481
CrossRef
Google scholar
|
[37] |
Jones J B. Plant nutrition and soil fertility manual. 2nd eds. New York: CRC Press, 2012
|
[38] |
Mallarino A P, Oyarzabal E S, Hinz P N. Interpreting within-field relationships between crop yields and soil and plant variables using factor analysis. Precision Agriculture, 1999, 1(1): 15–25
CrossRef
Google scholar
|
[39] |
Adamsen F J. Irrigation method and water quality effect on peanut yield and grade. Agronomy Journal, 1989, 81(4): 589–593
CrossRef
Google scholar
|
[40] |
Camp C R, 0. Subsurface drip irrigation: a review. Transactions of the ASAE. American Society of Agricultural Engineers, 1998, 41(5): 1353–1367
CrossRef
Google scholar
|
[41] |
Playán E, Faci J M, Serreta A. Modeling microtopography in basin irrigation. Journal of Irrigation and Drainage Engineering, 1996, 122(6): 339–347
CrossRef
Google scholar
|
[42] |
Battikhi A M, Abu-Hammad A H. Comparison between the efficiencies of surface and pressurized irrigation systems in Jordan. Irrigation and Drainage Systems, 1994, 8(2): 109–121
CrossRef
Google scholar
|
[43] |
Lecina S, Playán E, Isidoro D, Dechmi F, Causapé J, Faci J M. Irrigation evaluation and simulation at the Irrigation District V of Bardenas (Spain). Agricultural Water Management, 2005, 73(3): 223–245
CrossRef
Google scholar
|
[44] |
Socolow R H. Nitrogen management and the future of food: lessons from the management of energy and carbon. Proceedings of the National Academy of Sciences of the United States of America, 1999, 96(11): 6001–6008
CrossRef
Pubmed
Google scholar
|
[45] |
Song Z W, Feng X M, Lal R, Fan M M, Ren J, Qi H, Qian C R, Guo J R, Cai H G, Cao T H, Yu Y, Hao Y B, Huang X M, Deng A X, Zheng C Y, Zhang J, Zhang W J. Optimized agronomic management as a double-win option for higher maize productivity and less global warming intensity: a case study of Northeastern China. Advances in Agronomy, 2019, 157: 251–292
CrossRef
Google scholar
|
[46] |
Forcella F, Benech Arnold R L, Sanchez R, Ghersa C M. Modeling seedling emergence. Field Crops Research, 2000, 67(2): 123–139
CrossRef
Google scholar
|
[47] |
Letey J. Relationship between soil physical properties and crop production. Advances in Soil Science, 1958, 1: 277–294
CrossRef
Google scholar
|
[48] |
Nelson S D, Terry R E. The effects of soil physical properties and irrigation method on denitrification. Soil Science, 1996, 161(4): 242–249
CrossRef
Google scholar
|
[49] |
El-Hendawy S E, Schmidhalter U. Optimum coupling combinations between irrigation frequency and rate for drip-irrigated maize grown on sandy soil. Agricultural Water Management, 2010, 97(3): 439–448
CrossRef
Google scholar
|
[50] |
Khosla R, Fleming K, Delgado J A, Shaver T M, Westfall D G. Use of site-specific management zones to improve nitrogen management for precision agriculture. Journal of Soil and Water Conservation, 2002, 57(6): 513–518
|
[51] |
Balafoutis A, Beck B, Fountas S, Vangeyte J, van der Wal T, Soto I, Gómez-Barbero M, Barnes A, Eory V. Precision agriculture technologies positively contributing to GHG emissions mitigation, farm productivity and economics. Sustainability, 2017, 9(8): 1339
CrossRef
Google scholar
|
/
〈 | 〉 |