Economic Aspects of Precision Agriculture Systems

The paper deals with an economic assessment of impacts of precision agriculture (PA) on crop production economy. Based on a questionnaire survey and a FADN agricultural product expense-to-revenue ratio survey, it analyses a set of agricultural businesses the structure of which essentially copies the composition of business forms in the Czech Republic’s agricultural sector. The economic assessment applies economic analysis methods based on cost calculations and a calculation formula that considers the commodity and species production structure. Based on an analysis of a number of scientific studies, it determines specific cost savings and makes a quantification of the effect of precision agriculture techniques on costs. In all the production areas, the greatest effect caused by application of precision agriculture techniques was quantified for winter wheat. Conversely, the lowest financial effects are shown in the analysed production areas for spring wheat. We also identified differences in the cost savings between spring and winter barley; the greater savings occur for winter barley. Financial effects in the form of reduced production costs were also found for other analysed crops cultivated by the businesses studied. The financial savings for the pea plant are almost comparable to those for winter barley. The greatest financial savings were achieved for sugar beet

Economic Aspects of Precision Agriculture Systems

The paper deals with an economic assessment of impacts of precision agriculture (PA) on crop production economy. Based on a questionnaire survey and a FADN agricultural product expense-to-revenue ratio survey, it analyses a set of agricultural businesses the structure of which essentially copies the composition of business forms in the Czech Republic’s agricultural sector. The economic assessment applies economic analysis methods based on cost calculations and a calculation formula that considers the commodity and species production structure. Based on an analysis of a number of scientific studies, it determines specific cost savings and makes a quantification of the effect of precision agriculture techniques on costs. In all the production areas, the greatest effect caused by application of precision agriculture techniques was quantified for winter wheat. Conversely, the lowest financial effects are shown in the analysed production areas for spring wheat. We also identified differences in the cost savings between spring and winter barley; the greater savings occur for winter barley. Financial effects in the form of reduced production costs were also found for other analysed crops cultivated by the businesses studied. The financial savings for the pea plant are almost comparable to those for winter barley. The greatest financial savings were achieved for sugar beet

Economic Aspects of Precision Agriculture Systems

The paper deals with an economic assessment of impacts of precision agriculture (PA) on crop production economy. Based on a questionnaire survey and a FADN agricultural product expense-to-revenue ratio survey, it analyses a set of agricultural businesses the structure of which essentially copies the composition of business forms in the Czech Republic’s agricultural sector. The economic assessment applies economic analysis methods based on cost calculations and a calculation formula that considers the commodity and species production structure. Based on an analysis of a number of scientific studies, it determines specific cost savings and makes a quantification of the effect of precision agriculture techniques on costs. In all the production areas, the greatest effect caused by application of precision agriculture techniques was quantified for winter wheat. Conversely, the lowest financial effects are shown in the analysed production areas for spring wheat. We also identified differences in the cost savings between spring and winter barley; the greater savings occur for winter barley. Financial effects in the form of reduced production costs were also found for other analysed crops cultivated by the businesses studied. The financial savings for the pea plant are almost comparable to those for winter barley. The greatest financial savings were achieved for sugar beet

Assessment and Prediction of Maize Production Considering Climate Change by Extreme Learning Machine in Czechia

Machine learning algorithms have been applied in the agriculture field to forecast crop productivity. Previous studies mainly focused on the whole crop growth period while different time windows on yield prediction were still unknown. The entire growth period was separated into each month to assess their corresponding predictive ability by taking maize production (silage and grain) in Czechia. We present a thorough assessment of county-level maize yield prediction in Czechia using a machine learning algorithm (extreme learning machine (ELM)) and an extensive set of weather data and maize yields from 2002 to 2018. Results show that sunshine in June and water deficit in July were vastly influential factors for silage maize yield. The two primary climate parameters for grain maize yield are minimum temperature in September and water deficit in May. The average absolute relative deviation (AARD), root mean square error (RMSE), and coefficient (R2) of the proposed models are 6.565–32.148%, 1.006–1.071%, 0.641–0.716, respectively. Based on the results, silage yield will decrease by 1.367 t/ha (3.826% loss), and grain yield will increase by 0.337 t/ha (5.394% increase) when the max temperature in May increases by 2 °C. In conclusion, ELM models show a great potential application for predicting maize yield