Terhi Suojala-Ahlfors, Anu Koivisto, Eero Liski, Anna-Kaisa Jaakkonen, Tiina Mattila

Time trends of field vegetable yields and yield gaps in northern latitudes using a Bayesian approach

Introduction

Time trends of field vegetable yields and yield gaps in northern latitudes using a bayesian approach. Explore time trends and yield gaps of field vegetables (carrot, onion, white cabbage) in Finland using a Bayesian approach. Uncover regional variations for sustainable production.

Abstract

Open-field production of horticultural crops has high economic value in Finland. Profitable production requires sufficiently high yields and good product quality. This study’s objective was to assess the temporal and regional variation in the yield of three field vegetables (carrot, onion, and white cabbage) in Finland. Second, our aim was to quantify the yield gap of these species in their main production regions. The analysis was based on comprehensive statistical data (2012–2021) modelled using a Bayesian approach. Time trends varied between plant species and regions. In carrot, the yield tended to remain similar. In onion, some statistically significant increasing regional time trends were found, whereas in white cabbage the significant time trends were mostly negative, indicating a decreasing yield. The yield gap was largest in onion, but its economic value was highest in carrot. To ensure profitable and sustainable production, it is necessary to reduce the yield variation and yield gaps. More efforts are needed to adapt to climate change and control production risks.

Review

This study, "Time trends of field vegetable yields and yield gaps in northern latitudes using a Bayesian approach," addresses a highly pertinent topic in agricultural science, particularly for regions like Finland where open-field horticultural crops hold significant economic value. The research focuses on assessing temporal and regional yield variations and quantifying yield gaps for key vegetables (carrot, onion, white cabbage). Utilizing a robust Bayesian modeling approach on comprehensive statistical data from 2012–2021, the study offers valuable insights into the dynamics of vegetable production under northern climatic conditions, contributing significantly to understanding the challenges and opportunities for profitable and sustainable agriculture in these areas. The methodology, based on extensive statistical data and a Bayesian approach, appears well-suited to analyze complex time trends and regional variations, providing a nuanced understanding of yield dynamics. The findings reveal distinct species-specific trends: carrot yields tended to remain similar, onion showed some statistically significant regional increases, while white cabbage exhibited mostly negative trends, indicating declining yields. Furthermore, the quantification of yield gaps is crucial, showing the largest gap in onion but the highest economic value of this gap in carrot. These differentiated results underscore the necessity for tailored strategies for each crop. The implications of this research are substantial, particularly for agricultural practitioners, policymakers, and researchers aiming to enhance food security and economic viability in northern horticulture. The identified need to reduce yield variation and gaps, adapt to climate change, and control production risks highlights critical areas for future intervention and research. This study provides a strong foundation by clearly mapping out current yield performances and potential improvements. Future work could potentially delve deeper into the *drivers* behind these varying trends, such as specific climate parameters, pest/disease pressures, or management practices, to inform more targeted and effective mitigation and adaptation strategies.

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