Predicting Maize Theoretical Methane Yield in Combination with Ground and UAV Remote Data Using Machine Learning.

The accurate, timely, and non-destructive estimation of maize total-above ground biomass (TAB) and theoretical biochemical methane potential (TBMP) under different phenological stages is a substantial part of agricultural remote sensing. The assimilation of UAV and machine learning (ML) data may be successfully applied in predicting maize TAB and TBMP; however, in the Nordic-Baltic region, these technologies are not fully exploited. Therefore, in this study, during the maize growing period, we tracked unmanned aerial vehicle (UAV) based multispectral bands (blue, red, green, red edge, and infrared) at the main phenological stages. In the next step, we calculated UAV-based vegetation indices, which were combined with field measurements and different ML models, including generalized linear, random forest, as well as support vector machines. The results showed that the best ML predictions were obtained during the maize blister (R2)-Dough (R4) growth period when the prediction models managed to explain 88-95% of TAB and 88-97% TBMP variation. However, for the practical usage of farmers, the earliest suitable timing for adequate TAB and TBMP prediction in the Nordic-Baltic area is stage V7-V10. We conclude that UAV techniques in combination with ML models were successfully applied for maize TAB and TBMP estimation, but similar research should be continued for further improvements.

Oilseed Rape, Wheat, and Barley Grain Contamination as Affected by Different Glyphosate Usage.

Glyphosate is one of the most widely used herbicides, but is still in the spotlight due to its controversial impact on the environment and human health. The main purpose of this study was to explore the effects of different glyphosate usages on harvested grain/seed contamination. Two field experiments of different glyphosate usage were carried out in Central Lithuania during 2015-2021. The first experiment was a pre-harvest application, with two timings, the first according to the label (14-10 days), and the other applied 4-2 days before harvest (off-label), performed in winter wheat and spring barley in 2015 and 2016. The second experiment consisted of glyphosate applications at label rate (1.44 kg ha-1) and double dose rate (2.88 kg ha-1) at two application timings (pre-emergence of crop and at pre-harvest), conducted in spring wheat and spring oilseed rape in 2019-2021. The results suggest that pre-emergence application at both dose rates did not affect the harvested spring wheat grain or spring oilseed rape seeds-no residues were found. The use of glyphosate at pre-harvest, despite the dosage and application timing, led to glyphosate's, as well as its metabolite, aminomethosphonic acid's, occurrence in grain/seeds, but the amounts did not reach the maximum residue levels according to Regulation (EC) No. 293/2013. The grain storage test showed that glyphosate residues remain in grain/seeds at steady concentrations for longer than one year. A one year study of glyphosate distribution within main and secondary products showed that glyphosate residues were mainly concentrated in wheat bran and oilseed rape meal, while no residues found in cold-pressed oil and wheat white flour, when glyphosate used at pre-harvest at the label rate.