Effect of long-term climate signatures on regional and local potato yield in Finland

• Published in: Smart Agricultural Technology
• Main Authors: Kedar Surendranath Ghag, Amirhossein Ahrari, Anandharuban Panchanathan, Syed M.T. Mustafa, Toni Liedes, Björn Klöve, Ali Torabi Haghighi
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2024
• Subjects: Agriculture; Potato yield; Climate variability; Rainfall; Temperature effects; Growing degree days; Agriculture (General); S1-972; Agricultural industries; HD9000-9495; Northern Finland
• Online Access: https://doi.org/10.1016/j.atech.2024.100411; https://doaj.org/article/0846e3456891444795459a3539f2e736

This research study investigates the impact of air temperature and precipitation on annual potato crop yield in Finland region and a local area in northern Finland. For this, the annual crop yield data of regional and local case study area is processed using Z-score normalization technique. Classification of computed z-score values was carried out into different classes ranging between the most beneficial crop yield year and the most vulnerable crop yield year. Later, the detection of feasible potato cropping season at monthly and daily scale was carried out using different weather parameters. Further, long-term trend analysis using Mann-Kendall's approach at annual, seasonal, and monthly scales was carried out using 60 years of dataset of both case study areas. Then after, the comparative analysis of annual crop yield and the characteristics obtained within climate data using different statistical approaches at annual, seasonal, and monthly scale. Finally, multivariate analysis was carried out to find most influential climate variables obtained using different statistical signatures. The results shows that, over the 100 years of period the annual potato crop yield of regional case study area shows a rising trend with declining area under potato crop. Classification approach found 16 % annual yield scored lowest Z-score while, 18% the highest. Likewise, 20 years of data for the local case study area found that 25 % of the dataset scored the highest Z-score and 15 % of the dataset values scored the lowest. Long-term trend analysis of air temperature shows significant increasing trend annually, seasonally and for monthly during the months between July-September. Whereas, similar procedure with the precipitation data showed increasing trend only at annual scale with the precipitation data analysis. During the comparative analysis between the annual crop yield data based on z-score classification and different statistical results obtained from weather parameters such as variation of precipitation and temperature ...