South Dakota Soybean Processors (SDSYA) Depreciation & Amortization (CF) (2009 - 2026)
South Dakota Soybean Processors (SDSYA) posted Depreciation & Amortization (CF) of $7.58 million for Q2 2026, up 281.5% from $1.99 million a year earlier.
South Dakota Soybean Processors (SDSYA) Depreciation & Amortization (CF) (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Depreciation & Amortization (CF) at South Dakota Soybean Processors was $15.44 million, up 106.7% year-over-year; for FY2025, it was $9.84 million, up 50.9% from FY2024.
- Annual Depreciation & Amortization (CF) has increased for 13 consecutive years, with a five-year compound annual growth rate of 14.9% (FY2020 to FY2025).
- In prior years, South Dakota Soybean Processors' Depreciation & Amortization (CF) was $6.52 million in FY2024 (+11.8%), $5.83 million in FY2023 (+4.9%), $5.56 million in FY2022 (+9.2%) and $5.09 million in FY2021 (+3.7%).
- The Q2 2026 figure stands as the highest quarterly Depreciation & Amortization (CF) in data going back to Q3 2010.
- The strongest year-over-year quarter for Depreciation & Amortization (CF) in the past five years was Q2 2026, with growth of 281.5%; the weakest was Q4 2023, with a decline of 45.6%.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Dep. & Amort. (Qtr) |
|---|---|---|---|---|---|
| 1 | Archer-Daniels-Midland | 32.98 Bn | 29.75 Bn | 1.89 Bn | 295.00 Mn |
| 2 | Tyson Foods | 21.20 Bn | 17.56 Bn | 921.00 Mn | 329.00 Mn |
| 3 | Bunge Global | 19.10 Bn | 17.51 Bn | 1.33 Bn | 248.00 Mn |
| 4 | Jbs | 13.72 Bn | -1.87 Bn | 2.41 Bn | 660.38 Mn |
| 5 | Darling Ingredients | 7.99 Bn | 7.57 Bn | 477.54 Mn | 135.67 Mn |
| 6 | Smithfield Foods | 7.58 Bn | 2.40 Bn | 313.00 Mn | 86.00 Mn |
| 7 | Pilgrims Pride | 6.72 Bn | 4.22 Bn | 333.67 Mn | 123.22 Mn |
| 8 | Ingredion | 5.73 Bn | 1.83 Bn | 399.00 Mn | 55.00 Mn |
| 9 | Scotts Miracle-Gro | 3.79 Bn | 3.79 Bn | - | - |
| 10 | South Dakota Soybean Processors | 228.39 Mn | 543.31 Mn | 36.40 Mn | 7.58 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.58 Mn |
| Mar 31, 2026 | 7.81 Mn |
| Dec 31, 2025 | 3.88 Mn |
| Sep 30, 2025 | 1.99 Mn |
| Jun 30, 2025 | 1.99 Mn |
| Mar 31, 2025 | 1.98 Mn |
| Dec 31, 2024 | 1.98 Mn |
| Sep 30, 2024 | 1.52 Mn |
| Jun 30, 2024 | 1.52 Mn |
| Mar 31, 2024 | 1.50 Mn |
| Dec 31, 2023 | 1.52 Mn |
| Sep 30, 2023 | 1.46 Mn |
| Jun 30, 2023 | 1.44 Mn |
| Mar 31, 2023 | 1.42 Mn |
| Dec 31, 2022 | 2.80 Mn |
| Jun 30, 2022 | 1.38 Mn |
| Mar 31, 2022 | 1.39 Mn |
| Dec 31, 2021 | 1.31 Mn |
| Sep 30, 2021 | 1.26 Mn |
| Jun 30, 2021 | 1.26 Mn |
South Dakota Soybean Processors Depreciation & Amortization (CF) API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=depreciation-and-amortization-cf&ticker=SDSYA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "depreciation-and-amortization-cf", "ticker": "SDSYA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=depreciation-and-amortization-cf&ticker=SDSYA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();