Limoneira (LMNR) Operating Expenses (2010 - 2026)
Limoneira's Operating Expenses was $46.77 million in fiscal Q3 2026 (quarter ended Jul 31, 2026), down 2.8% from $48.11 million a year earlier but up 2.5% from the prior quarter.
Powered by 
Analysis
Limoneira (LMNR) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Limoneira's Operating Expenses was $175.05 million through Jul 31, 2026, up 1.3% year-over-year; for FY2025 (ended Oct 31, 2025), it was $180.13 million, down 8.9% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of -0.4% (FY2020 to FY2025).
- In earlier fiscal years, Operating Expenses was $197.68 million in FY2024 (+16.9%), $169.12 million in FY2023 (-7.3%), $182.4 million in FY2022 (+5.8%) and $172.36 million in FY2021 (-6.1%).
- Quarterly Operating Expenses has moved between $12.02 million (fiscal Q1 2023) and $54.31 million (fiscal Q3 2024) over five years.
- Compared with a year earlier, Operating Expenses was higher in two of the last eight quarters, with an average decline of 6.8%.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q1 2024 (growth of 295.1%); the worst was fiscal Q1 2023 (a decline of 75.4%).
- Per Business Quant data, LMNR's Operating Expenses in the three fiscal quarters before Q3 2026 was $45.62 million (Q2 2026), $28.76 million (Q1 2026) and $53.91 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Archer-Daniels-Midland | 38.28 Bn | 34.57 Bn | 1.94 Bn | 1.04 Bn |
| 2 | Bunge Global | 20.79 Bn | 18.30 Bn | 1.68 Bn | 606.00 Mn |
| 3 | Tyson Foods | 17.93 Bn | 14.29 Bn | 921.00 Mn | 559.00 Mn |
| 4 | Jbs | 12.60 Bn | -20.51 Bn | 2.59 Bn | 1.99 Bn |
| 5 | Darling Ingredients | 9.52 Bn | 9.12 Bn | 503.37 Mn | 1.52 Bn |
| 6 | Smithfield Foods | 7.49 Bn | 2.44 Bn | 478.00 Mn | 191.00 Mn |
| 7 | Pilgrims Pride | 6.49 Bn | 4.32 Bn | 339.75 Mn | 273.80 Mn |
| 8 | Ingredion | 6.09 Bn | 2.26 Bn | 426.00 Mn | 45.00 Mn |
| 9 | Seaboard | 3.89 Bn | -931.52 Mn | 221.00 Mn | 121.00 Mn |
| 10 | Limoneira | 219.76 Mn | 238.16 Mn | 6.56 Mn | 46.77 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 46.77 Mn |
| Apr 30, 2026 | 45.62 Mn |
| Jan 31, 2026 | 28.76 Mn |
| Oct 31, 2025 | 53.91 Mn |
| Jul 31, 2025 | 48.11 Mn |
| Apr 30, 2025 | 38.46 Mn |
| Jan 31, 2025 | 39.65 Mn |
| Oct 31, 2024 | 46.61 Mn |
| Jul 31, 2024 | 54.31 Mn |
| Apr 30, 2024 | 49.28 Mn |
| Jan 31, 2024 | 47.48 Mn |
| Oct 31, 2023 | 51.12 Mn |
| Jul 31, 2023 | 54.05 Mn |
| Apr 30, 2023 | 51.93 Mn |
| Jan 31, 2023 | 12.02 Mn |
| Oct 31, 2022 | 41.55 Mn |
| Jul 31, 2022 | 47.86 Mn |
| Apr 30, 2022 | 44.16 Mn |
| Jan 31, 2022 | 48.83 Mn |
| Oct 31, 2021 | 39.95 Mn |
API Access
Limoneira Operating Expenses 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=operating-expenses&ticker=LMNR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LMNR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=LMNR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();