This study investigated the temporal variability of 20 agronomic, flour, dough, and bread-making quality traits in winter wheat across 28 growing seasons using a Polish multi-environment trial (MET) dataset. A two-stage linear mixed model framework, Hodrick–Prescott filtering, Mann-Kendall trend tests, and time-series regression were used to quantify long-term temporal patterns and their associations with April–September temperature and precipitation. Grain yield (GY) showed the strongest positive trend among the studied traits, increasing by 0.14 t ha−1 year−1, corresponding to a 62.1% increase over the study period (Kendall’s τ = 0.6190). In contrast, several technological quality traits declined significantly over time, including grain glassiness (GG; −2.16 %age points year−1, total decline 78.0%, τ = 0.6825), protein content (PC; −0.03 %age points year−1, total decline 10.5%, τ = −0.2698), wet gluten content (WG; −0.14 %age points year-¹, total decline 19.1%, τ = −0.3228), dough development (DD; −0.04 min year−1, total decline 44.7%, τ = −0.3810), dough stability (DS; −0.17 min year−1, total decline 56.1%, τ = −0.4974), quality number (QN; −3.31 units year−1, total decline 63.1%, τ = −0.5968), and loaf volume (LV; 9.28 cm³ 100 g−1 year−1, total decline 28.3%, τ = −0.4656). The average April–September temperature was significantly associated with temporal trends in GY, GG, WG, WA, QN, AL, and LV, whereas total precipitation was not significantly associated. However, the climate regression models explained only part of the observed temporal variation (R² = 0.11–0.45), indicating that additional factors, including cultivar turnover, genotype × environment interactions, and agronomic changes, also contributed to long-term variability. Overall, the results reveal a long-term divergence between yield improvement and technological quality traits in winter wheat under temperate conditions.

The objective of this study was to analyse the genetic structure of the population of Phytophthora infestans in Poland, focusing on determining whether seed tubers play a role in pathogen migration and on the role of sexual recombination. In total, 858 isolates were collected from 2016 to 2018, 2020 and 2021 from 10 locations in different regions. The isolates were described in terms of mating type, mitochondrial haplotype, resistance to metalaxyl, virulence and polymorphism at 12 simple-sequence repeat (SSR) loci. Both mating types were found and often occurred in the same field. Among 858 P. infestans isolates, 309 multilocus genotypes (MLGs) were identified. Almost 24% (n = 204) of the sampled isolates were classified to European P. infestans genotypes: EU13, EU34, EU41, EU36 and EU37. The remaining 654 isolates of P. infestans had MLGs that were unique to Poland and strongly suggested sexual recombination and oospores as a source of inoculum. In parentage analysis, each European P. infestans genotype tested as a potential parent was assigned a different parent-offspring probability. Probable progeny isolates were identified for genotypes EU13 and EU34, which have been present in the Polish P. infestans population since 2005 and 2002, respectively. Detection of 2-16 P. infestans isolates of Polish genotypes in the same year but in different locations indicates seed potatoes as a migration route for the pathogen. Our study highlights sexual recombination and seed potato-related migrations as factors affecting the P. infestans population structure in Poland, increasing the pathogen's genetic adaptability.

Organic production systems impose strong environmental constraints on silage maize, yet the relative contributions of genotype, environment and their interaction (G × E) to key performance traits remain insufficiently resolved. This study evaluated six maize cultivars across 11 organically managed environments (location × year combinations) in Poland, assessing weed infestation, plant height, fresh matter yield, dry matter content and dry matter yield. Genotype × environment interaction was explicitly analyzed using AMMI-based models, and cultivar adaptability and stability were evaluated using complementary indices. Environmental effects consistently dominated all traits, explaining 78–91% of total variation, while G × E interactions, though smaller, were significant and altered cultivar rankings. Weed infestation ranged widely across environments, from below 10% to over 90%, and was almost entirely environment-driven. Yield-related traits followed a strong precipitation gradient, with Pawłowice and Śrem showing the highest biomass potential. SM Perseus produced the greatest dry matter yields (13.53 t·ha−1), whereas SM Mieszko combined high dry matter content (37.73%) with outstanding stability. Mega-environment analysis identified distinct adaptive niches, confirming that no genotype performed consistently best across all conditions. These findings close a key knowledge gap regarding cultivar performance under organic management and demonstrate the necessity of multi-environment evaluation that integrates performance, stability and adaptability analyses to support site-specific cultivar recommendations that enhance biomass productivity and silage quality in ecologically managed maize systems.

The multifaceted nature of agricultural management and environmental factors complicates the production of winter oilseed rape (Brassica napus L.). This study evaluated 25 varieties (21 hybrids and four populations) in three growing seasons (2020/21, 2021/22 and 2022/23) in Poland. The focus was on yield, fat content, and resistance to Sclerotinia sclerotiorum. The analyses revealed significant variability among the varieties, with the hybrids performing better consistently in terms of yield and fat content. The level of resistance to Sclerotinia was similar in hybrid and population varieties. Furthermore, DK Excited was found to be the highest-yielding variety, while Duke had the highest fat content. Derrick was the most resistant to S. sclerotiorum. Advocat and Dynamic were identified as the best varieties. In the analysed series of field trials, yield was found to be affected by high temperatures and a lack of rainfall in March, June, and July. For fat content, a lack of rainfall in July was the main limiting factor.

Lodging is one of the main factors influencing yield reduction in both organic and conventional systems. In the organic system, lodging is mainly controlled by selecting varieties with increased resistance to lodging, by regulating sowing density, or by cultivation of varieties of appropriate height. The present study aimed to compare ten varieties tested in the years 2020–2022 in organic trials in terms of plant height and resistance to lodging in two growth phases (milk and harvest). Depending on the analyzed trait, a linear or cumulative link linear mixed model was fitted on plot data. The analyses showed that variety Farmer was the most resistant to lodging in the two growth phases, whereas varieties KWS Vermont and Rubaszek were less resistant to lodging in two growth phases than Farmer, but only at the milk phase, the differences were significant. Furthermore, Radek was the tallest among the tested varieties, whereas Farmer was classified as mid-tall. According to Wricke’s ecovalence coefficient, Bente was the most stable, while Farmer ranked third. Therefore, varieties that are the most resistant to lodging and are the most stable in terms of height, should be promoted for cultivation.

Lodging is one of the main factors influencing yield reduction in both organic and conventional systems. In the organic system, lodging is mainly controlled by selecting varieties with increased resistance to lodging, by regulating sowing density, or by cultivation of varieties of appropriate height. The present study aimed to compare ten varieties tested in the years 2020-2022 in organic trials in terms of plant height and resistance to lodging in two growth phases (milk and harvest). Depending on the analyzed trait, a linear or cumulative link linear mixed model was fitted on plot data. The analyses showed that variety Farmer was the most resistant to lodging in the two growth phases, whereas varieties KWS Vermont and Rubaszek were less resistant to lodging in two growth phases than Farmer, but only at the milk phase, the differences were significant. Furthermore, Radek was the tallest among the tested varieties, whereas Farmer was classified as mid-tall. According to Wricke's ecovalence coefficient, Bente was the most stable, while Farmer ranked third. Therefore, varieties that are the most resistant to lodging and are the most stable in terms of height, should be promoted for cultivation.

In the next few years, the demand for organic crops, including barley, will grow. Barley is one of the world’s most important crops cultivated for food and feed. With the forecasted increase in cropped area, there is a need for stable, well-adapted and high-yielding varieties. The aim of this study was to assess the yield stability of ten varieties tested in the Polish organic post-registration trials in the years 2020–2022. For this purpose, we fitted a linear mixed model on plot data. Additionally, for each variety, we calculated the probability of the yield falling to a certain threshold. It is shown that the Bente variety was the highest-yielding among the tested varieties. The Pilote variety was the most stable in terms of Shukla’s stability variance. Furthermore, for the three highest-yielding varieties, the lowest values of the simultaneous selection index and the probability of falling below a certain threshold were obtained. We can, therefore, conclude that the highest-yielding varieties should be promoted for cultivation. Moreover, new varieties suitable for organic farming can be bred from the highest-yielding and most stable varieties.

Climate-driven changes have raised concerns about their long-term impacts on the yield resilience of cereal crops. This issue is critical in Poland as it affects major cereal crops like winter triticale, spring wheat, winter wheat, spring barley, and winter barley. This study investigates how soil nutrient profiles, fertilization practices, and crop management conditions influence the yield resilience of key cereal crops over a thirteen-year period (2009–2022) in the context of changing climate expressed as varying Climatic Water Balance. Data from 47 locations provided by the Research Centre for Cultivar Testing were analyzed to assess the combined effects of agronomic practices and climate-related water availability on crop performance. Yield outcomes under moderate and enhanced management practices were contrasted using Classification and Regression Trees to evaluate the relationships between yield variations and agronomic factors, including soil pH, nitrogen, phosphorus, potassium fertilization, and levels of phosphorus, potassium, and magnesium in the soil. The study found a downward trend in Climatic Water Balance, highlighting the increasing influence of climate change on regional water resources. Crop yields responded positively to increased agricultural inputs, especially nitrogen. Optimal soil pH and medium phosphorus levels were identified as crucial for maximizing yield. The findings underscore the importance of tailored nutrient management and adaptive strategies to mitigate the adverse effects of climate variability on cereal production. The results provide insights for field crop research and practical approaches to sustain cereal production in changing climatic conditions.

Starch content serves as a crucial indicator of the quality and palatability of potato tubers. It has become a common practice to evaluate the polysaccharide content directly in tubers freshly harvested from the field. This study aims to develop models that can predict starch content prior to the harvesting of potato tubers. Very early potato varieties were cultivated in the northern and northwestern regions of Poland. The research involved constructing multiple linear regression (MLR) and artificial neural network (ANN-MLP) models, drawing on data from eight years of field trials. The independent variables included factors such as sunshine duration, average daily air temperatures, precipitation, soil nutrient levels, and phytophenological data. The NSM demonstrated a higher accuracy in predicting the dependent variable compared to the RSM, with MAPE errors of 7.258% and 9.825%, respectively. This study confirms that artificial neural networks are an effective tool for predicting starch content in very early potato varieties, making them valuable for monitoring potato quality.

Leaf rust and net blotch are two important fungal diseases of barley. Leaf rust is the most important rust disease of barley, whereas net blotch can result in significant yield losses and cause the deterioration of crop quality. The best and the most environmentally friendly method to control diseases is to cultivate resistant varieties. The aim of the current study was to identify barley varieties with an improved resistance to leaf rust and net blotch in Polish organic post-registration trials conducted in the years 2020–2022. For this purpose, the cumulative link mixed model with several variance components was applied to model resistance to leaf rust and net blotch. It was found that the reference variety Radek was the most resistant to leaf rust, whereas variety Avatar outperformed the reference variety in terms of resistance to net blotch, although the difference between the two varieties was non-significant. In the present study, the use of the cumulative link mixed model framework made it possible to calculate cumulative probabilities or the probability of a given score for each variety and disease, which might be useful for plant breeders and crop experts. Both, the method of analysis and resistant varieties may be used in the breeding process to derive new resistant varieties suitable for the organic farming system.

Vacuum impregnation (VI) is a process that allows modification or enrichment of porous food products with vitamins, minerals, functional ingredients, etc. There are many factors that hamper mass transfer during VI, e.g. low porosity, composition of the matrix, processing pressure and time, etc. The objective of this study was to evaluate the effect of starch on blocking mass transport during VI, and the potential of ultrasound as a factor enhancing mass transfer. The effectiveness of VI was evaluated on the basis of the ascorbic acid content (AAC), a marker compound introduced from the solution. It was found that starch can hinder the mass transfer but ultrasound intensifies the flow of the impregnating solution (16-67% increase in AAC). The quantitative effects, however, depended on the application stage. This may be explained by the different types of cavitation (stable or transient) dominant at different pressures. Importantly, the negative effects of VI on the analyzed quality parameters analyzed (e.g., color, texture, structure-forming compound content) were not stated. The results indicated that the effectiveness of VI in low-porous and starch-rich materials may be increased by applying ultrasound, but more research is required to analyze the stability of the compound introduced during preservation processes.

The soybean crop (Glycine max) is known for its high oil and protein content, making it a valuable resource for animal feed and a crucial ingredient in vegan and vegetarian food products. Soybean is a thermophilic short-day plant, demanding specific climatic conditions for successful cultivation. In an effort to expand soybean cultivation to northern regions, a variety of trials were conducted. The aim of this study was to determine the most suitable soybean varieties for cultivation in Northern Poland. The field trials were conducted in nine locations, in the years 2020–2022. Yield, fat content, and protein content were the observed characteristics. Results for 13 varieties had been collected and were analysed using the AMMI model. The genotype–environment interaction provides information that supports estimations of the stability of certain varieties. AMMI-adjusted means, WTOP3, WAAS and GSI indices were calculated in order to assess the suitability of those varieties for cultivation in Northern Poland. It was shown that the Amiata variety had the highest mean yield among the tested varieties, whilst the Erica variety was the most stable. The Abelina variety had the lowest value of the GSI index. For fat content, the Ambella variety had the highest mean and the lowest values of the GSI index, whereas the ES Comandor variety was the most stable. For protein content, the Nessie PZO variety had the highest mean, the Aurelina variety was the most stable and had the lowest values of the GSI index. Thus, the Abelina, Ambella, and Aurelina varieties are the most favourable varieties for cultivation in that region.

The quality of potatoes intended for consumption or food processing depends primarily on their variety and chemical composition, which can be modified by growing conditions, place of cultivation, type of soil, amount of rainfall, as well as fertilization and plant protection products. This study aims to investigate the content of biologically active compounds in new varieties of potatoes with purple and yellow flesh, harvested in different cultivation locations. The content of the basic chemical composition and biologically active compounds in the raw material depended primarily on their variety, and to a lesser extent on the place of cultivation. Higher levels of kynurenic acid (KYNA), phenolic acids, and amino acids were found in potatoes of the new variety with purple-fleshed Provita compared to potatoes with yellow-fleshed Ismena. Potatoes with purple-flesh were characterized by over 40% lower amount of total glycoalcaloids (TGA). Most of the determined biologically active compounds, i.e. anthocyanins, phenolic acids, KYNA, and TGA varied depending on the place of origin of the potatoes, at the level of 40–66%. The biggest differences were found in the content of flavonols and amino acids, in the case of these substances the differences between potatoes from different places of cultivation ranged from 88% to 99%.

Interest in organic agriculture worldwide is growing and is mainly supported by a strong consumer interest. In the literature, a lot of attention has been paid to comparing organic and conventional systems, on studying the yield gap between the two systems and, how to reduce it. In the present work, based on the results from Polish organic and conventional series of field trials carried out in 2019-2021, organic and conventional systems were compared in terms of potato tuber yield. Moreover, we propose a Bayesian approach to the variety x environment x system data set and describe Bayesian counterparts of two stability measures. Using this methodology, we identify the most stable and highest tuber yielding varieties in the Polish potato organic and conventional series of field trials. It is shown that the tuber yield in the organic system was approx. 44% lower than the tuber yield in the conventional system. Moreover, varieties Tajfun and Otolia were the most stable and highest yielding varieties in the organic system, whereas in the conventional system, the variety Jurek was the most stable and highest yielding variety among the tested varieties. In the present work, the use of the Bayesian approach allowed us to calculate the probability that the mean of a given variety in given system exceeds the mean of control varieties in that system.

We assess the genetic gain and genetic correlation in maize yield using German and Polish official variety trials. The random coefficient models were fitted to assess the genetic correlation. Official variety testing is performed in many countries by statutory agencies in order to identify the best candidates and make decisions on the addition to the national list. Neighbouring countries can have similarities in agroecological conditions, so it is worthwhile to consider a joint analysis of data from national list trials to assess the similarity in performance of those varieties tested in both countries. Here, maize yield data from official German and Poland variety trials for cultivation and use (VCU) were analysed for the period from 1987 to 2017. Several statistical models that incorporate environmental covariates were fitted. The best fitting model was used to compute estimates of genotype main effects for each country. It is demonstrated that a model with random genotype-by-country effects can be used to borrow strength across countries. The genetic correlation between cultivars from the two countries equalled 0.89. The analysis based on agroecological zones showed high correlation between zones in the two countries. The results also showed that 22 agroecological zones in Germany can be merged into five zones, whereas the six zones in Poland had very high correlation and can be considered as a single zone for maize. The 43 common varieties which were tested in both countries performed equally in both countries. The mean performances of these common varieties in both countries were highly correlated.

The aim of the study was to evaluate the dependence of potato crops on the level of irrigation in three mesoregions of Poland. The field experiments were carried out in 2009–2011 according to an obligatory methodology for evaluation of crop cultivars. Three factors were tested: two cultivation practices (with irrigation and without irrigation as control), five potato cultivars, and three locations (Masłowice, Szczecin-Dąbie, and Węgrzce). The study was conducted in randomized blocks in triplicate. The study included the same nutrition across locations and protection against potato blight. Irrigation was applied according to the criterion of optimal soil moisture at a humidity decrease below 70% of the field water capacity. At the time of harvest, total and commercial yields of tubers were determined. Detailed analysis of the dependent variables, total and marketable yield, and the independent variables for the second harvest date, confirmed confidence in the achieved results. The coefficients of variation for total and marketable yield, on the second harvest date, were 23% and 25%, respectively, which means high stability for the results. Irrigation of potato plantations contributed to an increase in the total yield of tubers in the first harvest term by 3.22 t·ha−1 and by 7.23 t·ha−1 -in the second term; and the commercial yield of tubers by 3.45 t·ha−1 in the first term and by 7.42 t·ha−1 -in the second term of tuber harvest. The highest watering efficiency in the first harvest time, 60 days after planting, was distinguished by the “Miłek” variety, and in the second harvest date by the “Denar” variety.

Yield forecasting is a rational and scientific way of predicting future occurrences in agriculture—the level of production effects. Its main purpose is reducing the risk in the decision-making process affecting the yield in terms of quantity and quality. The aim of the following study was to generate a linear and non-linear model to forecast the tuber yield of three very early potato cultivars: Arielle, Riviera, and Viviana. In order to achieve the set goal of the study, data from the period 2010–2017 were collected, coming from official varietal experiments carried out in northern and northwestern Poland. The linear model has been created based on multiple linear regression analysis (MLR), while the non-linear model has been built using artificial neural networks (ANN). The created models can predict the yield of very early potato varieties on 20th June. Agronomic, phytophenological, and meteorological data were used to prepare the models, and the correctness of their operation was verified on the basis of separate sets of data not participating in the construction of the models. For the proper validation of the model, six forecast error metrics were used: i.e., global relative approximation error (RAE), root mean square error (RMS), mean absolute error (MAE), and mean absolute percentage error (MAPE). As a result of the conducted analyses, the forecast error results for most models did not exceed 15% of MAPE. The predictive neural model NY1 was characterized by better values of quality measures and ex post forecast errors than the regression model RY1.

Field trials conducted in multiple years across several locations play an essential role in plant breeding and variety testing. Usually, the analysis of the series of field trials is performed using a two-stage approach, where each combination of year and site is treated as environment. In variety testing based on the results from the analysis, the best varieties are recommended for cultivation. Under a Bayesian approach, the variety recommendation process can be treated as a formal decision theoretic problem. In the present study, we describe Bayesian counterparts of two stability measures and compare the varieties in terms of the posterior expected utility. Using the described methodology, we identify the most stable and highest tuber yielding varieties in the Polish potato series of field trials conducted from 2016 to 2018. It is shown that variety Arielle was the highest yielding, the third most stable variety and was the second best variety in terms of the posterior expected utility. In the present work, application of the Bayesian approach allowed us to incorporate the prior knowledge about the tested varieties and offered a possibility of treating the variety recommendation process as a formal decision process.

The yield and yield quality of sugar from the sugar beet (Beta vulgaris L.) and are determined by genotype, environment and crop management. This study was aimed at analyzing the stability of white sugar yield and the adaptation of cultivars based on 36 modern sugar beet cultivars under different environmental conditions. The compatibility of sugar beet cultivars' rankings between the three growing seasons and between the 11 examined locations was assessed. In addition, an attempt was made to group environments to create mega-environments. From among the 11 examined locations, four mega-environments were distinguished on the basis of the compatibility of the white sugar yield rankings. The assessment of the adaptation of cultivars and the determination of mega-environments was carried out using GGE (genotype main effects plus genotype environment interaction effects) biplots and confirmed by the Spearman rank correlation test performed for cultivars between locations. The cultivars studied were characterized by a high stability of white sugar yield in the considered growing seasons. The high compliance of the sugar yield rankings between the years contributes to a more effective recommendation of cultivars.

Potato is one the of world’s most important crops. It is grown primarily for human consumption but is also used to feed cattle and to produce alcohol and starch. In modern industry, potatoes are a major source of starch. Unpredictable growing conditions strongly influence the cultivation of starch potatoes. One of the best methods for dealing with unpredictable stresses, including those caused by climate change, is cultivation of stable and high yielding cultivars. In the present work, tuber yield and starch yield from a Polish post-registration series of field trials conducted in the years 2013–2016 were analyzed using three different linear mixed models, which can be associated with three different stability measures. It is shown that cultivar Pokusa was the highest yielding and the most stable cultivar in terms of tuber yield, while cultivar Kuras was the most stable and the highest starch yielding cultivar. Moreover, using mixed model factorial regression, it is shown that temperatures in June and August and total precipitation in August had significant influence on tuber yield in the analyzed series of field trials.