Can Technological Development Compensate for the Unfavorable Impacts of Climate Change? Conclusions from 50 Years of Maize (Zea mays L.) Production in Hungary

L. Huzsvai,J. Zsembeli,E. Kovács,C. Juhász

Published 2020 in Atmosphere

ABSTRACT

The goals of our study were to evaluate the historical aspects of maize (Zea mays L.) production in Hungary, and to provide a prognosis for the yield for 2050 based on the trends of temperature, precipitation, and climatic water balance changes. Different climate zones for the period of 1970–2019 were investigated by means of correlation analyses, normality tests, time series analysis, and multiple linear regression analysis. Two well-distinguishable linear trends in the yields were found, the first representing large-scale farming, and the second starting with the change of the socio-economic system in 1989. The annual amount of precipitation showed high variations both spatially and temporally, although no significant change was identified for the last five decades. In the period 1990–2019, not only were higher temperatures characteristic, but the frequency of extreme high temperature values (Tmax > 30 °C) also increased. We quantified the heat stress, expressing it in heat stress units (HSU, °C) derived from the heat-sum of the daily maximum air temperature values above 30 °C. By 2050, the average increase in HSUs may reach 35 °C. Increasing HSU causes yield depression; according to our estimations, a 1 °C increase in HSU results in a 23 kg ha−1 yield depression of maize. Taking the unfavorable effect of heat stress and technological development into consideration, the average domestic yield of maize will be 8.2 t ha−1. Our study revealed that without taking technological development into consideration, prediction models may overestimate the adverse effect of climate change on crop production.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Atmosphere

  • Publication date

    2020-12-12

  • Fields of study

    Agricultural and Food Sciences, Environmental Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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