IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v226y2019ics0378377419303282.html
   My bibliography  Save this article

Retrieval of photosynthetic capability for yield gap attribution in maize via model-data fusion

Author

Listed:
  • Hu, Shi
  • Mo, Xingguo
  • Huang, Farong

Abstract

Identifying the factors driving yield gaps between the attainable and actual yields achieved by farmers is essential for agricultural improvement and water resource management. In this study, the process-based VIP (Vegetation Interface Processes) eco-hydrological model was used to estimate the yield gap of spring maize in the Hutuo River Basin (HRB), North China. To describe the realistic crop growth and attainable yield pattern, the field-sampled grain yield and aboveground biomass were used to design a scheme to retrieve the intrinsic quantum efficiency (εact) for leaf photosynthesis of C4 crop, including the statistical relationships between the intrinsic quantum efficiency, vegetation index and grain yield. The actual yields were predicted with the retrieved intrinsic quantum efficiency pattern, while the attainable yields were predicted with the average of the top 5% intrinsic quantum efficiencies. The simulated actual yields are consistent with the census data at the county level (R2 of 0.37 to 0.74 and relative RMSE of 16–29%). The average yield gap in the basin is 5246 kg ha−1, being 55% of the attainable yield. It is revealed that soil organic matter (SOM) content and depth of soil layer are the principal limiting factors in more than 80% of farmland and results in 70% of the yield gap, while the effects of SOM content is dominant in flat piedmont. Water stress is also a critical factor limiting crop yield, especially for hilly farmlands with slopes greater than 8°. Improving fertilizer management and irrigation techniques in the HRB is therefore the primary task to narrow yield gaps attributable to basin management.

Suggested Citation

  • Hu, Shi & Mo, Xingguo & Huang, Farong, 2019. "Retrieval of photosynthetic capability for yield gap attribution in maize via model-data fusion," Agricultural Water Management, Elsevier, vol. 226(C).
    • Handle: RePEc:eee:agiwat:v:226:y:2019:i:c:s0378377419303282
    DOI: 10.1016/j.agwat.2019.105783
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377419303282
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2019.105783?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Qianyu & Xia, Jianyang & Shi, Zheng & Huang, Kun & Du, Zhenggang & Lin, Guanghui & Luo, Yiqi, 2016. "Variation of parameters in a Flux-Based Ecosystem Model across 12 sites of terrestrial ecosystems in the conterminous USA," Ecological Modelling, Elsevier, vol. 336(C), pages 57-69.
    2. Neumann, Kathleen & Verburg, Peter H. & Stehfest, Elke & Müller, Christoph, 2010. "The yield gap of global grain production: A spatial analysis," Agricultural Systems, Elsevier, vol. 103(5), pages 316-326, June.
    3. Jing Wang & Enli Wang & Xiaoguang Yang & Fusuo Zhang & Hong Yin, 2012. "Increased yield potential of wheat-maize cropping system in the North China Plain by climate change adaptation," Climatic Change, Springer, vol. 113(3), pages 825-840, August.
    4. Duchemin, B. & Hadria, R. & Erraki, S. & Boulet, G. & Maisongrande, P. & Chehbouni, A. & Escadafal, R. & Ezzahar, J. & Hoedjes, J.C.B. & Kharrou, M.H. & Khabba, S. & Mougenot, B. & Olioso, A. & Rodrig, 2006. "Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices," Agricultural Water Management, Elsevier, vol. 79(1), pages 1-27, January.
    5. Chen, Chao & Wang, Enli & Yu, Qiang, 2010. "Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1175-1184, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wan, Wei & Liu, Zhong & Li, Kejiang & Wang, Guiman & Wu, Hanqing & Wang, Qingyun, 2021. "Drought monitoring of the maize planting areas in Northeast and North China Plain," Agricultural Water Management, Elsevier, vol. 245(C).
    2. Wang, Chunyu & Li, Sien & Wu, Mousong & Zhang, Wenxin & Guo, Zhenyu & Huang, Siyu & Yang, Danni, 2023. "Co-regulation of temperature and moisture in the irrigated agricultural ecosystem productivity," Agricultural Water Management, Elsevier, vol. 275(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luo, Jianmei & Shen, Yanjun & Qi, Yongqing & Zhang, Yucui & Xiao, Dengpan, 2018. "Evaluating water conservation effects due to cropping system optimization on the Beijing-Tianjin-Hebei plain, China," Agricultural Systems, Elsevier, vol. 159(C), pages 32-41.
    2. Shengli Liu & Wenbin Wu & Xiaoguang Yang & Peng Yang & Jing Sun, 2020. "Exploring drought dynamics and its impacts on maize yield in the Huang-Huai-Hai farming region of China," Climatic Change, Springer, vol. 163(1), pages 415-430, November.
    3. Zhong, Honglin & Sun, Laixiang & Fischer, Günther & Tian, Zhan & Liang, Zhuoran, 2019. "Optimizing regional cropping systems with a dynamic adaptation strategy for water sustainable agriculture in the Hebei Plain," Agricultural Systems, Elsevier, vol. 173(C), pages 94-106.
    4. Chen, Qiaomin & Liu, Yujie & Ge, Quansheng & Pan, Tao, 2018. "Impacts of historic climate variability and land use change on winter wheat climatic productivity in the North China Plain during 1980–2010," Land Use Policy, Elsevier, vol. 76(C), pages 1-9.
    5. Fei, Li & Meijun, Zhou & Jiaqi, Shao & Zehui, Chen & Xiaoli, Wei & Jiuchun, Yang, 2020. "Maize, wheat and rice production potential changes in China under the background of climate change," Agricultural Systems, Elsevier, vol. 182(C).
    6. Bai, Huiqing & Wang, Jing & Fang, Quanxiao & Huang, Binxiang, 2020. "Does a trade-off between yield and efficiency reduce water and nitrogen inputs of winter wheat in the North China Plain?," Agricultural Water Management, Elsevier, vol. 233(C).
    7. Al Zayed, Islam Sabry & Elagib, Nadir Ahmed & Ribbe, Lars & Heinrich, Jürgen, 2016. "Satellite-based evapotranspiration over Gezira Irrigation Scheme, Sudan: A comparative study," Agricultural Water Management, Elsevier, vol. 177(C), pages 66-76.
    8. Małgorzata Jagła & Piotr Szulc & Katarzyna Ambroży-Deręgowska & Iwona Mejza & Joanna Kobus-Cisowska, 2019. "Yielding of two types of maize cultivars in relation to selected agrotechnical factors," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 65(8), pages 416-423.
    9. Westhoek, Henk & Ingram, John & van Berkum, Siemen & Hajer, Maarten, 2015. "The European food system and natural resources: Impacts and Options," 148th Seminar, November 30-December 1, 2015, The Hague, The Netherlands 229279, European Association of Agricultural Economists.
    10. Hisham Eldardiry & Emad Habib & David M. Borrok, 2020. "Accounting for Inter-Annual and Seasonal Variability in Assessment of Water Supply Stress: Perspectives from a humid region in the USA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2517-2534, June.
    11. Gonçalves, Ivo Zution & Mekonnen, Mesfin M. & Neale, Christopher M.U. & Campos, Isidro & Neale, Michael R., 2020. "Temporal and spatial variations of irrigation water use for commercial corn fields in Central Nebraska," Agricultural Water Management, Elsevier, vol. 228(C).
    12. Dietrich, Jan Philipp & Schmitz, Christoph & Müller, Christoph & Fader, Marianela & Lotze-Campen, Hermann & Popp, Alexander, 2012. "Measuring agricultural land-use intensity – A global analysis using a model-assisted approach," Ecological Modelling, Elsevier, vol. 232(C), pages 109-118.
    13. El-Naggar, A.G. & Hedley, C.B. & Horne, D. & Roudier, P. & Clothier, B.E., 2020. "Soil sensing technology improves application of irrigation water," Agricultural Water Management, Elsevier, vol. 228(C).
    14. Xu, Ying & Findlay, Christopher, 2019. "Farmers’ constraints, governmental support and climate change adaptation: Evidence from Guangdong Province, China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), October.
    15. Bispo, R.C. & Hernandez, F.B.T. & Gonçalves, I.Z. & Neale, C.M.U. & Teixeira, A.H.C., 2022. "Remote sensing based evapotranspiration modeling for sugarcane in Brazil using a hybrid approach," Agricultural Water Management, Elsevier, vol. 271(C).
    16. Ying Xu & Christopher Findlay, 2019. "Farmers’ constraints, governmental support and climate change adaptation: evidence from Guangdong Province, China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), pages 866-880, October.
    17. Xiao, Dengpan & Shen, Yanjun & Qi, Yongqing & Moiwo, Juana P. & Min, Leilei & Zhang, Yucui & Guo, Ying & Pei, Hongwei, 2017. "Impact of alternative cropping systems on groundwater use and grain yields in the North China Plain Region," Agricultural Systems, Elsevier, vol. 153(C), pages 109-117.
    18. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).
    19. Lijun Yin & Yaxin Liao & Xiao Mou, 2024. "Delayed Sowing Can Improve Potassium Utilization Efficiency and Grain Potassium Concentration in Winter Wheat," Agriculture, MDPI, vol. 14(5), pages 1-16, April.
    20. Elfarkh, Jamal & Simonneaux, Vincent & Jarlan, Lionel & Ezzahar, Jamal & Boulet, Gilles & Chakir, Adnane & Er-Raki, Salah, 2022. "Evapotranspiration estimates in a traditional irrigated area in semi-arid Mediterranean. Comparison of four remote sensing-based models," Agricultural Water Management, Elsevier, vol. 270(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:226:y:2019:i:c:s0378377419303282. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.