Meeting the nutritional needs of a dynamically developing global society is a major challenge. Despite the modernisation of agriculture, huge losses in the quality and quantity of crops occur each year, mainly due to weed species, which are the most important biotic limitation to agricultural production. Globally, approximately 1800 weed species cause a 31.5% reduction in plant production, which translates to USD 32 billion per year in economic losses. However, when the same herbicides are frequently applied, plants develop segetal immune mechanisms. There are currently around 380 herbicide-resistant weed biotypes worldwide. Due to the negative influence of herbicides on ecosystems and the legal regulations that limit the use of chemical crop protection products, it is necessary to develop a new method of weed control. Bioherbicides, based on living organisms or their secondary metabolites, seem to be an ideal solution. The biocontrol market is worth around EUR 550 million in Europe and EUR 1.6 billion worldwide, with an estimated 15% growth expected by 2025. Despite numerous studies that have demonstrated the effectiveness of microbial bioherbicides, only 25 mould-based bioherbicides are currently available to growers. Due to the high specificity and selectivity of biological crop protection products, as well as their low production costs and non-toxicity to the environment and human health, they would appear to be a safe alternative to chemical pesticides.

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.

The objective of this study was to determine the effects on quality of incorporating raspberry and cranberry pomaces into American-style muffins prepared under various baking conditions. The different baking conditions did not affect the texture or microstructure of the control muffins. The enhanced samples baked at 140 °C for 30 min were characterized by a harder texture than the control muffins and by a distributed protein matrix and distorted starch granules, while those baked at 240 °C for 15 min had a moist texture and showed incomplete starch gelatinization. The mean percent recovery of ellagic acid, flavonols, tocopherols, tocotrienols, and anthocyanins after baking were 156, 53, 48, 43, and 22 %, respectively. Lower baking temperature was better for ellagic acid and tocotrienols, but worse for flavonols, tocopherols, and anthocyanins. It seems that, for the enhanced samples, the intermediate baking conditions (180 °C for 20 min) guarantee the best microstructure and texture and the appropriate retention of phytochemicals in muffins.

The negative impact of chemical pesticides on the environment and human health has contributed to the introduction of legal regulations that ensure the reduction in the use of agrochemicals in favor of biological products. The existing review of the literature, including our research, clearly shows that the ideal biocontrol agents are Trichoderma fungi. The production of antibiotics, lytic enzymes degrading the cell walls of plant pathogens, or inducing a defense response in plants are just some of the features supporting the wide use of these microorganisms in sustainable agriculture. It is estimated that currently about 60% of biofungicides used to eliminate fungal pathogens are produced based on Trichoderma sp. strains.