The aim of this study was to assess genotype by environment interaction for grain yield, plant height and thousand-grain weight in winter triticale cultivars by the additive main effects and multiplicative interaction (AMMI) model. The study comprised of ten winter triticale varieties i.e.: Algoso, Baltiko, Grenado, Magnat, Moderato, Pawo, Todan, Trimester, Trismart and Witon. Field trials were performed at seven locations in three years (21 environments) in a randomized complete block design, with two replicates at two levels of cultivation technology (standard – A1 and intensive – A2). Field experiments were carried out as part of Post Registration Variety Trials in Wielkopolska region. AMMI analyses revealed significant genotype and environmental effects as well as genotype by environmental interaction with respect to all three observed traits in both levels of cultivation intensity. The cultivars Algoso, Baltiko and Trimester are recommended for further inclusion in the breeding programs because of their stability and good average values of observed traits.

The objective of this study was to assess genotype by environment interaction for area under disease progress curve values in spring barley grown in South-West Poland by the additive main effects and multiplicative interaction model. The study comprised of 25 spring barley genotypes (five cultivars: Basza, Blask, Antek, Skarb and Rubinek as well as all possible 10 two-way mixtures and 10 three-way mixtures combinations), evaluated at two locations in 4 years (eight environments) in a randomized complete block design, with four replicates. Area under disease progress curve (AUDPC) value of the tested genotypes ranged from 75.3 to 614.3, with an average of 175.3. In the AMMI analyses, 13.43% of the AUDPC value variation was explained by environment, 37.85% by differences between genotypes, and 18.20% by genotype by environment interaction. The mixture Basza/Skarb is recommended for further inclusion in the breeding program due to its low average AUDPC value (98.8) and is stable (AMMI stability value = 6.65).

Barley powdery mildew is caused by the fungus Blumeria graminis f. sp. Hordei. Monoculture and the use of disease-resistant varieties on large-scale usually lead to the selection of new pathogen races able to overcome the resistance. The use of variety mixtures can significantly improve the control of the disease and provides stable yield among different environments. To assess the effects of the variety mixtures of spring barley on the intensity of powdery mildew infection, we conducted field trials during four growing seasons at two locations contrasting in soil and environmental conditions. The experiments were based on five varieties of spring barley (Basza, Blask, Skarb, Rubinek, Antek) sown in pure stands as well as in their mixtures. No fungicide and insecticides were used, only herbicide protection was implemented. Our studies have shown that in both locations the intensity of the disease was reduced in varieties grown in mixtures when compared to pure stands. This confirms that cultivation of genetically diversified varieties of spring barley in mixtures provides economically and environmentally sustainable tool which allows to control powdery mildew disease.

Contamination of ergot (Claviceps purpurea) in grains continues to be a problem in outcrossing plants like rye, especially in years of favorable infection (cold, rainy) conditions. The problem is not the yield loss, but the contamination of the grains by toxic alkaloids leading to strict critical values within the European Union. This study was conducted to (1) partition the variation of genotype, inoculation treatments and environment for ergot infection of 12 winter rye genotypes, (2) the effect of varying proportions of a non-adapted restorer gene on ergot, and to (3) reveal within the genotype the relative importance of male pollen fertility and female receptivity on the ergot reaction of single crosses bearing different restorer genes. In total, 12 rye genotypes and two factorial crossing designs with each of five female and four male lines differing in their restorer genes were tested by artificial infection in up to 16 environments in four European countries. High and significant genotypic variation regarding the ergot severity and pollen-fertility restoration were observed. Furthermore significant general combining ability and specific combining ability variances and interactions with environment were obtained. The pollen-fertility restoration of the male had by far the highest importance for ergot severity, the female component, however, also revealed a significant effect. In conclusion, selecting for superior restoration ability is the most promising way on the short term, but there are also possibilities to improve the maternal site in future breeding programs.

Integrated Pest Management (IPM) is a system that combines ready-made plant protection methods. IPM guidelines apply to all users of plant protection products and require the prioritization of preventative methods. Adherence to IPM principles contributes to the production of healthy and safe food. In Poland, the implementation of IPM into agricultural practice remains a solution to the problem. Furthermore, it is necessary to ensure education and implementation of IPM at the basic or implementation level. The IPM element, particularly emphasized in the 2009/128/EC Directive, is the use of so-called warning systems, tools that address the issue of plant protection application. In this regard, it is necessary to use decision support systems (DSSs). DSSs are digital solutions that integrate meteorological, global, and field data. They include the risk of disease and pest occurrence and the timing of the application. DSSs are not part of the farmer’s experience or presentation but support them in making sound decisions. DSS reduces costs, the side effects of plant protection, and energy consumption. Examples of such solutions in Poland include the eDWIN platform and OPWS, classified, among others, in cereal protection against fungi. The aim of this article is to present the role, capabilities, and limitations of decision support systems in modern agricultural production and their importance in the context of the Green Deal and digital agriculture.