Adaptation patterns of winter wheat cultivars in agro-ecological regions

Multi-environment trials are commonly used to assess cultivar adaptation patterns under different environmental conditions and to help make effective cultivar recommendations for growers. An example of a multi-environment trial system used for cultivar recommendations is the Polish Post-registration Variety Testing System. A common approach in cultivar recommendations is to evaluate the adaptability of cultivars across, or for, specific trial locations. However, the locations of the trials and the fields where a farmer will grow a crop are hardly ever in the same place. Therefore, it would be better to group the trial locations into regions and give recommendations for the whole region. The aim of this study is to evaluate the grain yield adaptation patterns of 62 modern winter wheat cultivars in six agro-ecological regions of Poland for two crop management intensities over five growing seasons. The analysis of the grain yield data was performed separately for each intensity using single-stage approaches in linear mixed models. We ascertained that winter wheat yield variability was in the main determined by agro-ecological region and their interactions, and to a small extent by the cultivar effect. Cultivars Sailor and Linus were widely adapted to all agro-ecological regions studied for both crop management intensities. It is highly probable that these two cultivars will obtain high yield in all agro-ecological regions as well as with both crop management intensities studied. We observed high compatibility rankings between locations for both crop management intensities. High compatibility of the cultivar rankings in the trial locations also provides high precision when determining regions

Four-way data analysis within the linear mixed modelling framework

Cultivars have to be evaluated under different crop management systems across agro-ecosystems and years using multi-environment trials (MET) before releasing them to the market. Frequently, data collected in METs are arranged according to cultivar (G), management (M), location, (L) and year (Y) combinations in a four-way G x M x L x Y data table that is highly unbalanced for cultivars across locations and time. Therefore, we present the restricted maximum likelihood method (REML) for linear mixed models (LMM) with a factor analytic variance-covariance matrix for assessing cultivar adaptation to crop management systems and environments based on unbalanced datasets. Such a multi-environmental trial system has been in operation in Poland for winter wheat (Triticum aestivum L.) in the form of the Post-registration Variety Testing System (PVTS). This study aimed to illustrate the use of LMM in the analysis of unbalanced four-way G x M x L x Y data. LMM analysis provided adjusted means of grain yield for 51 winter wheat cultivars bred in different regions in Europe, tested across 18 trial locations and seven consecutive cropping seasons in two crop management intensities. The application of the four-way LMM with a factor analytic variance-covariance matrix is a complementary and effective tool for evaluating the unbalanced G x M x L x Y table. Cultivars tested had different adaptive responses to the Polish agro-ecosystems separately for each of the crop management intensities. Wide adaptation in both crop management systems was exhibited by cultivars Mulan and Jenga bred in Germany

Changes in relationships between humic substances and soil structure following different mineral fertilization of Vitis vinif-era L. in Slovakia

The quantity and quality of soil organic matter (SOM) depending on many edaphic and envi-ronmental factors may change in response to agriculture related practices. The SOM humification process can be supported by the application of mineral fertilizers, but in the production vineyards, such information is lacking. NPK fertilizer alters the soil quality, so the aim of this study was to: (1.) assess the extent and dynamics of different NPK (Control—no fertilization; 1st NPK and 3rd NPK levels) rates to the soil with grass sward cover in a productive vineyard on changes in SOM, humic substances (HS) and soil structure, and (2.) identify relationships between SOM, HS and soil structure. Results showed that the share of humic acids in soil organic carbon decreased only in NPK1 compared to Control and NPK3 treatments. The color quotient of humic substances values in NPK1 and NPK3 increased by 4 and 5%, respectively, compared to Control. Over a period of 14 years, the content of soil organic carbon increased by 0.71, 0.69 and 0.53 g kg–1 year–1 in Control, NPK1 and NPK3, respectively. The content of HS increased linearly with slight differences due to NPK application. The vulnerability of the soil structure decreased due to fertilization—more at the higher NPK-level. The rate of formed soil crust was decreasing in the following order: Control > NPK1 > NPK3. In Control treatment, the relations between SOM, HS and soil structure were most abundant and with the greatest significance, while with the increasing level of NPK, these relations lost their significance

Long-Term Yield Variability of Triticale (×Triticosecale Wittmack) Tested Using a CART Model

Triticale is a promising food crop that combines the yield potential and grain quality of wheat with the disease and environmental tolerance of rye. The objective of this study was to evaluate the impact of genotype, environment and crop management on spring and winter triticale yield variability, using data from 31 locations across the whole of Poland, from 2009 to 2017, with the Classification and Regression Tree (CART) analysis. It was found that CART is able to detect differences in spring and winter triticale successful growth. The yield variability of spring triticale was more dependent on the soil quality than winter triticale because of a shorter cycle duration, which increases sensitivity to nutrient supply and weather conditions. Spring triticale also needs to be sown as soon as possible to ensure a successful establishment. A strong dependence of yield variability on the availability of water for the winter triticale was observed. When growing winter triticale in Poland, with periodic excess water especially during autumn and early spring, the use of fungicides and growth regulators should be taken into account

Soil Electrical Conductivity and Satellite-Derived Vegetation Indices for Evaluation of Phosphorus, Potassium and Magnesium Content, pH, and Delineation of Within-Field Management Zones

The optimization of soil sampling is very important in precision agriculture. The main aim of this study was to evaluate the relationships between selected spectral indices (NDWI—normalized difference water index and NDVI—normalized difference vegetation index) and apparent soil electrical conductivity (EC) with soil nutrient content (phosphorus, potassium, and magnesium) and pH. Moreover, the usefulness of these variables for the delineation of within-field management zones was assessed. The study was conducted in 2021 in central Poland at three maize fields with a total area approximately 100 ha. The analyses were performed based on 47 management zones, which were used for soil sampling. Significant positive correlations were observed between the NDVI for the bare soil and all the studied nutrient contents in the soil and pH. A very strong positive correlation was observed between the soil EC and the potassium content and a moderate correlation was found with the magnesium content. A multiple-regression analysis proved that the soil nutrient content, especially potassium and phosphorus, was strongly related to the EC and NDVI. The novelty of this study is that it proves the relationships between soil and the crop attributes, EC and NDVI, which can be measured at field scale relatively simply, and the crucial soil nutrients, phosphorus and potassium. This allows the results to be used for optimized variable-rate fertilization

Soil Electrical Conductivity and Satellite-Derived Vegetation Indices for Evaluation of Phosphorus, Potassium and Magnesium Content, pH, and Delineation of Within-Field Management Zones

The optimization of soil sampling is very important in precision agriculture. The main aim of this study was to evaluate the relationships between selected spectral indices (NDWI—normalized difference water index and NDVI—normalized difference vegetation index) and apparent soil electrical conductivity (EC) with soil nutrient content (phosphorus, potassium, and magnesium) and pH. Moreover, the usefulness of these variables for the delineation of within-field management zones was assessed. The study was conducted in 2021 in central Poland at three maize fields with a total area approximately 100 ha. The analyses were performed based on 47 management zones, which were used for soil sampling. Significant positive correlations were observed between the NDVI for the bare soil and all the studied nutrient contents in the soil and pH. A very strong positive correlation was observed between the soil EC and the potassium content and a moderate correlation was found with the magnesium content. A multiple-regression analysis proved that the soil nutrient content, especially potassium and phosphorus, was strongly related to the EC and NDVI. The novelty of this study is that it proves the relationships between soil and the crop attributes, EC and NDVI, which can be measured at field scale relatively simply, and the crucial soil nutrients, phosphorus and potassium. This allows the results to be used for optimized variable-rate fertilization

Analysis of the Impact of Environmental and Agronomic Variables on Agronomic Parameters in Soybean Cultivation Based on Long-Term Data

Soybean (Glycine max (L.) Merr.) is a species of relatively little economic importance in Central and Eastern Europe, including Poland. Due to its popularity for the production of soybean oil, livestock feed, and human food, soybeans are a widely cultivated agricultural crop in the world. The aim of the presented research is to determine the most important agronomic and environmental variables in soybean production in Central and Eastern Europe. This work used a dataset from the Polish Post-Registration Variety Testing System in multi-environmental trials from the years 2012–2021. Variables classified for crop management included doses of mineral fertilizers (N, P, and K) and herbicides, sowing, and the type of previous crops. The environment was also included in the analysis through soil and weather characteristics using climatic water balance (CWB). The analysis was performed using multiple linear regression models and regression trees. It found that the variability of the soybean yield depended mainly on water available to plants and physical soil properties. This means that environmental variables have a stronger effect in comparison to crop management variables. The effect of the nutrients applied in the fields was relatively weak and only important in the case of phosphorus. Other variables which characterize crop management (including sowing date, previous crop, and plant protection using pesticides) have a weak effect on grain yield and yield-related traits variability. As there are not many studies on soybean cultivation in Poland, this work might be used as an introduction to research on soybean management in a hemiboreal climate

The Analysis of Wheat Yield Variability Based on Experimental Data from 2008–2018 to Understand the Yield Gap

Among European countries, Poland has the largest gap in the grain yield of winter wheat, and thus the greatest potential to reduce this yield gap. This paper aims to recognize the main reasons for winter wheat yield variability and shed the light on possible reasons for this gap. We used long-term datasets (2008–2018) from individual commercial farms obtained by the Laboratory of Economics of Seed and Plant Breeding of Plant Breeding and Acclimatization Institute (IHAR)-National Research Institute (Poland) and the experimental fields with high, close to potential yield, in the Polish Post-Registration Variety Testing System in multi-environmental trials. We took into account environment, management and genetic variables. Environment was considered through soil class representing soil fertility. For the crop management, the rates of mineral fertilization, the use of pesticides and the type of pre-crop were considered. Genotype was represented by the independent variable year of cultivar registration or year of starting its cultivation in Poland. The analysis was performed using the CART (Classification and Regression Trees). The winter wheat yield variability was mostly dependent on the amount of nitrogen fertilization applied, soil quality, and type of pre-crop. Genetic variable was also important, which means that plant breeding has successfully increased genetic yield potential especially during the last several years. In general, changes to management practices are needed to lower the variability of winter wheat yield and possibly to close the yield gap in Poland

The Analysis of Wheat Yield Variability Based on Experimental Data from 2008–2018 to Understand the Yield Gap

Among European countries, Poland has the largest gap in the grain yield of winter wheat, and thus the greatest potential to reduce this yield gap. This paper aims to recognize the main reasons for winter wheat yield variability and shed the light on possible reasons for this gap. We used long-term datasets (2008–2018) from individual commercial farms obtained by the Laboratory of Economics of Seed and Plant Breeding of Plant Breeding and Acclimatization Institute (IHAR)-National Research Institute (Poland) and the experimental fields with high, close to potential yield, in the Polish Post-Registration Variety Testing System in multi-environmental trials. We took into account environment, management and genetic variables. Environment was considered through soil class representing soil fertility. For the crop management, the rates of mineral fertilization, the use of pesticides and the type of pre-crop were considered. Genotype was represented by the independent variable year of cultivar registration or year of starting its cultivation in Poland. The analysis was performed using the CART (Classification and Regression Trees). The winter wheat yield variability was mostly dependent on the amount of nitrogen fertilization applied, soil quality, and type of pre-crop. Genetic variable was also important, which means that plant breeding has successfully increased genetic yield potential especially during the last several years. In general, changes to management practices are needed to lower the variability of winter wheat yield and possibly to close the yield gap in Poland