Economic Model and Viability of Agroecosystems for Soybean

A multifaceted field experiment for soybean was carried out in Croatia to assess the influence of tillage (TS) on selected economic indicators, that is, gross margin (GM), rate of profitability (ROP), cost-effectiveness (E), and productivity (P), and to provide a regression model for production planning. The investigated TS comprised the following parameters: CT - plowing (depth of 30 cm), DT - discing (depth of 8–12 cm), LT - soil loosening (depth of 35 cm), and no-tillage (NT). Randomized complete block design (RCBD) was used, with four replications. Experimental plot for a given TS measured 540 m². Economic indicators were calculated based on the established economic formulae and standard evaluation criteria. The SAS software version 9.3 and Microsoft Excel 2016 were used for statistical analysis. GM was in the following range: NT (+12.9 %) > DT (+7.1 %) > LT (-15.4 %), with a significant difference concerning the CT (€278.60 ha-1). ROP on the LT was lower (-14.5 %) and higher on NT (+21.4 %) significantly compared to CT. The production of one ton of soybeans on the NT took 1.75 working hours, which was significantly less compared to other TS. The results with the regression model highlight the varying economic viability of the TS, with notable differences in input costs, profitability, and efficiency, thereby offering valuable insights for sustainable and economically optimized soybean production.

Authors

Institutions

Publication Details

Journal
Poljoprivreda
Published
2025-12-19
DOI
https://doi.org/10.18047/poljo.31.2.8
Citations
1
Primary Topic
Soybean genetics and cultivation
Type
article
Field-Weighted Citation Impact
1.75
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Economic Model and Viability of Agroecosystems for Soybean

Boris Ravnjak, Miro Stošić, Tomislav Vinković, Monika Tkalec-Kojić et al.
1 citations
Poljoprivreda
Soybean genetics and cultivation
1.75
article

Economic Model and Viability of Agroecosystems for Soybean

Boris Ravnjak, Miro Stošić, Tomislav Vinković, Monika Tkalec-Kojić, Ljubica Ranogajec, Brigita Popović
article en
1 citations

Abstract

A multifaceted field experiment for soybean was carried out in Croatia to assess the influence of tillage (TS) on selected economic indicators, that is, gross margin (GM), rate of profitability (ROP), cost-effectiveness (E), and productivity (P), and to provide a regression model for production planning. The investigated TS comprised the following parameters: CT - plowing (depth of 30 cm), DT - discing (depth of 8–12 cm), LT - soil loosening (depth of 35 cm), and no-tillage (NT). Randomized complete block design (RCBD) was used, with four replications. Experimental plot for a given TS measured 540 m². Economic indicators were calculated based on the established economic formulae and standard evaluation criteria. The SAS software version 9.3 and Microsoft Excel 2016 were used for statistical analysis. GM was in the following range: NT (+12.9 %) > DT (+7.1 %) > LT (-15.4 %), with a significant difference concerning the CT (€278.60 ha-1). ROP on the LT was lower (-14.5 %) and higher on NT (+21.4 %) significantly compared to CT. The production of one ton of soybeans on the NT took 1.75 working hours, which was significantly less compared to other TS. The results with the regression model highlight the varying economic viability of the TS, with notable differences in input costs, profitability, and efficiency, thereby offering valuable insights for sustainable and economically optimized soybean production.

PoljoprivredaVol. 31(2)
University of Osijek (HR)
Openalex Percentile: Top 10%
Soybean genetics and cultivation
1.75
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.