Potato Research

The European Association for Potato Research (EAPR) publishes a journal, Potato Research, which includes original scientific contributions on both fundamental and applied research on potatoes, review articles and topics of general interest. It also contains Association news and reports on section meetings (including abstracts of papers presented).
A volume of the Journal (usually approximately 450 pages), consists of four issues, published in the same year. Submission of manuscripts is exclusively online via a web-based electronic submission and tracking system available at https://www.editorialmanager.com/potr

EAPR Members have online access to Potato Research (use the EAPR member login page)
A list of addresses of editors of ‘Potato Research’
Contents of ‘Potato Research’ can be found at Springerlink
Instructions for authors
Any comments regarding the publication and distribution of Potato Research should be addressed to EAPR

Springer Link

https://link.springer.com/journal/11540

Latest Issues

Comparing Forecasting Models for Potato Production: Evaluating T-ARMA, ARIMA-ARCH, Weibull and Score-Driven Approaches in Major Global Producers
9th April, 2025
This study examines trends in potato production across five major global producers (China, India, Russia, Ukraine and the US) using annual data from 1961 to 2022. We evaluate the T-ARMA, ARIMA-ARCH, Weibull and score-driven models to forecast production from 2023 to 2030. The results identify the T-ARMA model as optimal for China and India (validation MAE: 1,668 thousand tonnes and 3,277 thousand tonnes, respectively), while the ARIMA-ARCH and Weibull models perform best for Russia (MAE: 1,405 thousand tonnes) and the US (MAE: 547 thousand tonnes), respectively. Projections indicate a marginal decline in China (from 96,073 to 96,066 thousand tonnes; − 0.007%) and India (from 55,701 to 55,698 thousand tonnes; − 0.005%), contrasted by robust growth in Russia (from 20,026 to 26,284 thousand tonnes; + 31.2%). Ukraine’s production remains stable at approximately 21,103 thousand tonnes annually, while the US experiences a slight decline (from 18,054 to 18,053 thousand tonnes; − 0.005%). These forecasts, derived from regionally tailored models, offer actionable insights for policymakers to strengthen food security, optimize supply chains and prioritize agricultural innovation.
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Comprehensive Survey of Common Potato Viruses in Eastern Anatolia Region of Turkey: New Isolates and Phylogenetic Insights
9th April, 2025
Potatoes (Solanum tuberosum L.) are a vital crop in Turkey, contributing significantly to the country’s economy. However, they are susceptible to various viral infections, causing substantial yield losses if left unmanaged. This study aimed to conduct a comprehensive survey of economically significant viruses affecting potatoes in the Eastern Anatolia Region, Turkey, including the identification of new isolates and the inference of their phylogenetic relationships. A total of 1130 fresh leaf samples, including asymptomatic and symptomatic plant samples, were tested using the multiplex RT-PCR (m-RT-PCR) method to determine the prevalence of five viral pathogens. The test results revealed the presence of four viral pathogens, with an overall infection incidence of 37.08%. PVY was found in 35% of the samples, PVS in 8.5%, PVX in 1.8%, and PLRV in 1%. However, PVA was not detected. In addition, 74 of the 98 samples tested were positive for PVY + PVS, 13 for PVY + PVX, 2 for PVY + PLRV, 8 for PVY + PVS + PVX, and 1 for PVY + PVS + PLRV. From each sample that tested positive, two isolates were selected, and the complete coat protein (CP) gene regions of these isolates were cloned and sequenced. The sequences of the new potato virus isolates were deposited in the GenBank. Nucleic acid sequence comparisons revealed a consensus of over 99% among all available isolates and those from other regions of the world. However, this similarity is not specific to any particular host or region. In support of the similarities in nucleic acid, phylogenetic analyses also provided information on the evolutionary relatedness of these isolates from various origins and hosts. This finding suggests that the genetic makeup of these isolates is highly conserved across different populations and environments. This study, conducted in the Eastern Anatolia Region of Turkey, is the first comprehensive report on the presence and molecular phylogeny of four viral pathogens of economic importance in potato crops.
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Optimising Processing Technologies for Coloured-Skinned Potato Wedges: Analysis of Bioactive Compounds, Structural Integrity, and Sensory Properties
7th April, 2025
The study aimed to optimise the process for developing low-fat potato wedges from coloured potatoes. The process involved high-temperature, short-time blanching (85 ℃ for 3 min) of sliced potatoes followed by low-temperature, long-time blanching (65 ℃ for 2, 4, 6, and 8 min). Blanching for 8 min was identified as the optimal time, based on FTIR, XRD, and oil uptake analysis. This blanching time was then used in the production of frozen potato wedges. Among the tested varieties, all demonstrated higher values of total anthocyanins, phenols, and flavonoid content compared to Lady Rosetta (control). Textural and sensory analysis revealed Kufri Neelkanth as the most suitable variety for wedges production due to its superior texture and sensory attributes.
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Effect of Application of Signaling Compounds on the Remobilization of Assimilates and the Leaf Senescence Induction Process in Potatoes (Solanum tuberosum L.)
4th April, 2025
Understanding the role of signaling compounds in the regulation of leaf senescence and assimilate remobilization is crucial to optimize potato (Solanum tuberosum L.) yield and quality. This study investigates the effects of different signaling compounds on these processes through two field experiments conducted in 2021 and 2022. The objectives were to determine how the foliar applications of these compounds influence physiological traits and yield under varying planting dates and application frequencies. In 2021, treatments included the frequency of foliar application (one, two, or three times during the bulking stage of the tubers) as the main plot and signaling compounds (control, potassium silicate (PSi), monopotassium phosphate (MPPh), nitric oxide, hydrogen peroxide, EDTA, and ethephon) as subplots. In 2022, the main plots were the planting dates (Early: April 27, Optimal: May 28, late: 28 June), and the subplots were signaling compounds (control, PSi, MPPh, EDTA). The results showed that spraying of MPPh and PSi significantly increased tuber yield, tuber dry matter, tuber starch content, leaf electrolyte leakage, and leaf hydrogen peroxide levels in both years, while decreasing leaf chlorophyll content, SPAD values, and ascorbate peroxidase (APX) activity. Regarding the number of foliar applications assessed in the first experiment, applying the treatments twice increased tuber dry matter, tuber starch content, and leaf hydrogen peroxide levels, while reducing chlorophyll content. Analysis of planting dates revealed that planting at conventional and later dates increased tuber yield, tuber specific gravity, tuber starch content, and APX activity, but decreased the frying evaluation index. This study highlights the importance of signaling compounds, particularly MPPh and PSi, as practical tools to improve potato yield and quality.
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Drone RGB Imagery Color and Texture Information Have Varied Importance in Predicting Potato Aboveground Biomass in Different Growth Stages
31st March, 2025
Accurately monitoring the crop aboveground biomass (AGB) is critical for yield forecasting. Despite the advances in high-resolution RGB imagery using drone technologies, inconsistency remains regarding the use of color vegetation indices (VIs) and texture information in modeling AGB in different growth stages and under measurement conditions. Therefore, this study evaluated the performance of multiple VIs and texture information and their combinations for estimating potato AGB across multiple growth stages. Texture information included a gray-level co-occurrence matrix (GLCM) and a multi-scale Gabor wavelet texture. The Gaussian Process Regression (GPR) model with four different kernel functions was employed to establish AGB estimation models using VIs, GLCM-based texture, Gabor-based texture, and their combinations. For the tuber formation stage, VIs combined with GLCM-based texture significantly reduced the prediction error of the model (rRMSE = 0.20). For the tuber bulking and starch accumulation stages, GLCM-based texture combined with Gabor-based texture produced the lowest prediction errors (rRMSE = 0.15 and 0.13), positively affecting the model for different years and various conditions (low–high AGB values and over- and underestimation). For multiple growth stages, the two texture features combined with GPR produced the lowest prediction errors (rRMSE = 0.16). This study demonstrated that VIs combined with multiple texture features could further improve the performance of AGB estimation at different stages.
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Latest Issues

Comparing Forecasting Models for Potato Production: Evaluating T-ARMA, ARIMA-ARCH, Weibull and Score-Driven Approaches in Major Global Producers

Comprehensive Survey of Common Potato Viruses in Eastern Anatolia Region of Turkey: New Isolates and Phylogenetic Insights

Optimising Processing Technologies for Coloured-Skinned Potato Wedges: Analysis of Bioactive Compounds, Structural Integrity, and Sensory Properties

Effect of Application of Signaling Compounds on the Remobilization of Assimilates and the Leaf Senescence Induction Process in Potatoes (Solanum tuberosum L.)

Drone RGB Imagery Color and Texture Information Have Varied Importance in Predicting Potato Aboveground Biomass in Different Growth Stages

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