To obtain one litre of oil you often need around 5–8 kg of olives, but the figure can vary a great deal. With an optimal yield of 15% by weight, 100 kg of olives produce 15 kg of oil, equal to about 16.4 litres assuming a density close to 0.915 kg/l.
The answer "five kilos" is useful only as an order of magnitude. Agronomic yield and mill yield depend on cultivar, ripeness, water in the fruit, health and equipment. To compare vintages you must use the same formula and distinguish kilograms from litres.
The yield formula
Percentage yield by weight = kilograms of oil divided by kilograms of olives, multiplied by 100. If the mill reports litres, convert them to kilograms by multiplying by the approximate density of the oil. Example: 18 litres × 0.915 = 16.47 kg; on 100 kg of olives the yield is about 16.5%.
From percentage to litres
| Yield by weight | Kg of olives per 1 kg of oil | Approx. litres from 100 kg of olives |
|---|---|---|
| 10% | 10.0 | 10.9 |
| 15% | 6.7 | 16.4 |
| 18% | 5.6 | 19.7 |
| 22% | 4.5 | 24.0 |
Why the yield changes
The amount of water in the olive alters the ratio. Cultivar, crop load, irrigation, ripeness, damage and extraction conditions also matter. A high yield alone does not prove quality: very ripe fruit may give more oil but offer less aromatic freshness or greater fragility.
How to compare two millings
Record the net weight of the olives, kilograms or litres of oil, date, cultivar, ripeness and mill. Compare consistent data and consider any oil left in the lines. The most useful value is your own farm's historical series, not a percentage found online that refers to different conditions.
Economic yield and quality
Optimising does not mean chasing the highest number. Harvesting earlier can reduce the litres but increase intensity and stability; delaying can do the opposite. The right decision balances price, desired profile, weather risk and the ability to process quickly.
A complete calculation
With 320 kg of olives and 52 litres of oil, the litres per quintal (100 kg) are 16.25. Converting: 52 × 0.915 = 47.58 kg; the yield by weight is 47.58 ÷ 320 × 100 = 14.87%. Writing both values avoids wrong comparisons between those who speak in litres and those who use kilograms.
Water in the fruit and apparent yield
After rain, olives can contain more water: the weight delivered grows without a corresponding increase in oil. A dry year may show higher percentages even with lower total production. That is why percentage yield and litres per hectare describe different phenomena and must be read together.
The role of the mill
Temperature, malaxation time, decanter settings and the characteristics of the paste change the share recovered. Pushing the process to extract a few more points can compromise aromas and product quality. A fair comparison keeps the equipment and conditions constant or clearly states what has changed.
Minimum harvest spreadsheet
Create columns for date, plot, cultivar, kg of olives, ripeness, hours before taking them to the mill, kg and litres of oil, yield, acidity if available and tasting notes. After three harvests the spreadsheet is worth more than any general average: it shows which choices work in your context.
Kilograms and litres: avoiding the first calculation mistake
Olives are normally weighed in kilograms, while oil may be reported in litres or in kilograms. The two units are not interchangeable because oil is less dense than water: a litre weighs roughly 0.915 kilograms, with small variations linked to temperature and composition. To calculate a yield by weight, first convert litres to kilograms. If from 100 kg of olives you obtain 16 litres, the oil weighs about 14.64 kg and the yield by weight is therefore close to 14.6%, not 16%.
Many mills use the expression litres per quintal because it is immediate for the producer, but technical comparisons require specifying the unit. Always write whether you are talking about litres, kilograms or percentage by weight. Even volume measured at different temperatures can vary slightly; for commercial decisions, the instruments and process documents are authoritative. A table with kg of olives, litres of oil, estimated kg and the formula applied removes ambiguity and lets you compare vintages and batches without confusing two indicators that are only apparently similar.
Prepare a spreadsheet with separate cells for kg of olives, litres, density used and yield. Lock the formula to prevent accidental changes and show both results. If you share the figure with others, add the unit to the column heading. A yield of 15 can mean 15 litres per quintal or 15% by weight: without a label the number is ambiguous. This simple structure prevents arguments and makes the year-end results comparable even years apart.
Why the yield changes from one batch to another
Cultivar, ripeness, water availability, crop load and health status influence the amount of oil in the fruit. One variety may accumulate lipids on a different timetable from another; ripe olives can offer more yield but a less green profile. After rain the weight of water in the fruit can increase the mass delivered without a proportional increase in oil, lowering the apparent yield. In a dry year the opposite can happen, even with a lower overall production per hectare.
The sample matters too. A small test taken from unrepresentative crates can over- or underestimate the whole harvest. If you want to predict the yield, take olives from different plants and areas and use the same method of analysis over time. Compare the estimate with the mill's real result, knowing that laboratory and plant do not have identical efficiency. Yield is therefore a useful measure, but it must be read together with total quantity, sensory quality and the value of the product. Chasing the highest number can lead to harvesting too late.
When you collect a sample to predict the yield, note where and how it was taken. Avoid fruit only from outer branches or from the most heavily laden plants. Mix representative areas and keep different plots separate. Then compare the forecast with the result and calculate the gap. After several trials you will know whether the method tends to over- or underestimate. An estimate becomes useful not when it is perfect, but when you know the margin of error and include it in your planning.
The role of the mill in the quantity obtained
Crushing, malaxation and decanter settings determine how much of the oil present is recovered. Paste, temperature, time and added water change the efficiency. A well-run plant seeks the best balance between yield and quality; pushing the parameters to gain a few points can penalise aromas and sensitive components. To compare two mills you need similar olives, equivalent timings and separate batches. Otherwise the difference may depend more on the raw material than on the machine.
Ask whether the reported yield is expressed by weight or by volume and whether it includes any dregs. Check the calibration of the weighbridges and the correct assignment of the batch. If a lot is very small, find out about the plant's technical minimum and whether truly separate processing is possible. Keep the documents and note the parameters available. A producer who records only the final litres loses decisive information: waiting hours, ripeness and extraction conditions help explain why the same grove produces different results.
If you want to compare process settings, agree a controlled trial with the mill and check that the batches are truly comparable. Measure not only quantity, but profile and stability. A higher yield may include more water or impurities if the measurement is taken straight away; the figure after clarification may change. Ask when the volume was measured and at what temperature. The details are not for disputing, but for making the comparison technical and repeatable.
Conversion examples for different quantities
With 250 kg of olives and 35 litres of oil, the litres per quintal are 14. Converting the volume to weight, 35 × 0.915 gives about 32.03 kg; divided by 250 and multiplied by one hundred it produces a yield by weight close to 12.8%. With 500 kg and 90 litres, the litres per quintal are 18 and the yield by weight is about 16.5%. Showing both results makes the difference between the two ways of talking about yield obvious.
The inverse calculation serves for a prudent estimate. If you expect 400 kg of olives and assume 14 litres per quintal, the expected volume is about 56 litres. Do not use it as a promise: prepare containers with a margin and update the forecast when you know the ripeness and a yield test. For an estimate in kilograms of oil, multiply the kg of olives by the percentage by weight. Noting the formula and assumptions prevents a number copied from the previous year from becoming a certainty without context.
To estimate containers and sales, use three assumptions: cautious, central and high. With 400 kg, for example, apply three realistic historical values instead of a single average. Prepare enough capacity for the high scenario without planning revenue as if it were certain. Update after the first batches and separate the production forecast from the sale price. This approach avoids both insufficient containers and economic expectations built on an exceptional yield not yet verified.
High yield does not automatically mean high quality
Waiting for maximum oil accumulation can reduce some economic risks, but it exposes the fruit to over-ripening, dropping and bad weather. An oil obtained earlier may have a lower yield and greater sensory or commercial value. The right comparison considers revenue per hectare, quality, harvesting costs and product positioning, not only litres per quintal. Even a very aromatic batch can turn out unprofitable if harvest losses or processing times are excessive.
First define the product you want to obtain: green monovarietal, balanced blend, everyday oil or premium batch. Then set an acceptable yield threshold and a ripeness window. Taste the first batches and adjust the calendar if necessary. Selling quality requires consistency between story and bottle; boasting only a high yield does not communicate freshness. In family consumption the same principle applies: fewer litres of a clean, well-stored oil can be preferable to a larger quantity that quickly loses aroma.
Link yield to quality with a two-axis sheet. On one, record litres per quintal; on the other, assign consistent notes for fruitiness, cleanliness, balance and persistence. The aim is not to turn tasting into an absolute score, but to see whether the growth in litres coincides with the loss of the profile you are seeking. The best point may lie before the quantitative maximum. This information guides the next harvest better than a ranking based only on percentage.
The minimum record for truly understanding results
Create a row for each batch with date, plot, cultivar, kg of olives, ripeness, hours between harvest and crushing, mill, litres and kilograms of oil. Add the yield in both forms, malaxation temperature and duration if available, filtration and tasting notes. Also record recent rain and anomalies. A sheet built like this lets you filter the data and compare consistent situations, instead of remembering only the best year or the most surprising value.
After the harvest calculate weighted averages, not simple averages between batches of different sizes. If 50 kg yield a lot and 500 kg yield less, the two figures do not carry the same weight in the total. Also link yield to production per plant or per hectare when you have the acreage. Re-examine the sensory notes some months later to assess stability. Over time the record shows which choices increase real value. The initial question "how many olives for a litre" thus becomes a forecast based on your own data and not on a generic average.
At the end of the season calculate total oil, weighted yield and production per hectare, then compare with costs and sales. Keep the small batches too: they may have a low yield but high value. Discuss the results with the agronomist and the miller, distinguishing what depends on field, vintage and process. Choose a single experiment for the next harvest. A tidy record turns the question about the kilograms needed into a management tool and not an arithmetic curiosity.
In summary
To obtain one litre of oil you often need around 5–8 kg of olives, but the figure can vary a great deal. With a yield of 15% by weight, 100 kg of olives produce 15 kg of oil, equal to about 16.4 litres assuming a density close to 0.915 kg/l.
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FAQ
How many kg of olives for a litre?
Often 5–8 kg, but the variability is wide and depends on the real yield.
How do I convert kg of oil into litres?
Divide the kg by an approximate density close to 0.915 kg/l; for commercial data use the declared value.
Does a high yield mean better oil?
No. It is a quantitative figure, not a sensory or chemical judgement.
Is yield calculated in litres or kg?
The most rigorous percentage uses weights; litres must be converted.
How many litres of oil do you get from 100 kg of olives?
It depends on the yield. With 15% by weight you obtain 15 kg of oil, that is about 16.4 litres using an approximate density of 0.915 kg per litre.
Why is the density of the oil needed in the yield calculation?
Percentage yield compares weights, while the mill may report litres. Density lets you convert the volume into kilograms and compare consistent data.
Does rain increase olive yield?
It can increase the water contained in the fruit and therefore alter the apparent yield on the weight of the olives. That is why two lots are not comparable without knowing the conditions.
Which cultivar gives the most oil?
There are varietal differences, but ripeness, vintage, irrigation, health and technology have a large effect. The cultivar alone does not let you predict the real yield.
Does early harvesting always reduce the yield?
It often produces fewer litres per quintal, but it is not an absolute rule. The aim may be a greener, more structured profile rather than maximum quantity.
How do you compare the yield of two mills?
Use the same lot or comparable lots, record net weights, units of measurement and processing conditions. A comparison without these data can be misleading.
