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Effect and economic benefit of precision seeding and laser land leveling for winter wheat in the middle of China

Lookup NU author(s): Dr Glyn Jones, Professor Zhenhong Li



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


© 2021 The Authors. Rapid socio-economic changes in China, such as land conversion and urbanization, are creating new scopes for the application of precision agriculture (PA).An experiment to assess the economic benefits of two precision agriculture methods was applied for one year – precision seeding and precision seeding with land leveling. Whilst the results for this were positive, of itself it did not provide evidence of longer terms gains. The costs of land leveling are accrued in a single year but the benefits could carry over into subsequent years. Thus, in this case if the PA method provides carry over benefits to future years, the economic assessment would incorrectly assign all the costs to a single year of benefits i.e.the benefit-cost ratio would be underestimated. To gauge whether there was carry over benefits in future years we looked at NDVI and GUI as proxies for future year benefits. For the single year experiment, our results showed that: (1) Winter wheat yield was increased 23.2% through the integration of precision seeding and laser leveling technologies.(2) Both the single technology and the integrated technologies significant reduced the concentration of soil ammonium nitrogen at the depths of 60 cm; (3) The benefit/cost ratio's of the treatments exceeded that of the baseline by approximately 10% which translated to an increase of several hundred US$ per hectare. The NDVI analysis showed that the effect of laser land leveling could last to the next two years. When considering the multi-year impact of land leveling, the benefit/cost ratio of PSLL will increase to 23.5% and 22.9% with and without laser land leveling subsidies. Making clear the economic benefits of using PA technologies will likely promote application of the technologies in the region.

Publication metadata

Author(s): Chen J, Zhao C, Jones G, Yang H, Li Z, Yang G, Chen L, Wu Y

Publication type: Article

Publication status: Published

Journal: Artificial Intelligence in Agriculture

Year: 2022

Volume: 6

Pages: 1-9

Print publication date: 01/01/2022

Online publication date: 27/11/2021

Acceptance date: 25/11/2021

Date deposited: 16/02/2022

ISSN (electronic): 2589-7217

Publisher: KeAi Communications Co.


DOI: 10.1016/j.aiia.2021.11.003


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