Sugar fell to 16.34 USd/Lbs on September 1, 2025, down 0.18% from the previous day. Over the past month, Sugar's price has risen 0.56%, but it is still 15.69% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Sugar - values, historical data, forecasts and news - updated on September of 2025.

Sugar Price Index in World decreased to 103.30 Index Points in July from 103.60 Index Points in June of 2025. This dataset includes a chart with historical data for World Sugar Price Index.

Dangote Sugar Refinery PLC stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

In 2024, the global sugar market increased by 2.9% to $118.2B, rising for the fourth year in a row after three years of decline. Over the period under review, consumption, however, continues to indicate a relatively flat trend pattern. Over the period under review, the global market reached the peak level at $126.7B in 2012; however, from 2013 to 2024, consumption stood at a somewhat lower figure.

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Raw Sugar Market Size 2025-2029

The raw sugar market size is forecast to increase by USD 152.7 million, at a CAGR of 2.3% between 2024 and 2029.

The market is witnessing significant growth, driven primarily by the increasing demand for raw sugar in various food and beverage applications. This trend is being fueled by the expanding food industry, particularly in emerging economies, where sugar consumption is on the rise. Additionally, the emergence of e-commerce platforms has facilitated easier access to raw sugar for consumers and manufacturers, further boosting market growth. However, the high production cost of raw sugar poses a significant challenge for market participants. Producers must navigate this obstacle through efficient production methods, cost optimization, and strategic pricing to remain competitive in the market.
Companies seeking to capitalize on market opportunities and navigate challenges effectively should focus on innovation, cost reduction, and supply chain optimization. By staying agile and responsive to market trends, they can position themselves for long-term success in the dynamic the market.

What will be the Size of the Raw Sugar Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, with various factors shaping its dynamics. Sugarcane and sugar beet supply and demand, production costs, and sustainability are key elements influencing market activities. Biofuel production from sugarcane bagasse and sugar beet residues adds complexity to the market. Sugarcane diseases and pests, as well as transportation challenges, can impact yields and prices. Sugarcane consumption is driven by various applications, including food and beverage industries, ethanol production, and pharmaceuticals. Organic sugar and fair trade sugar are gaining popularity, adding to the market's diversity. Sugarcane juice and molasses are used to produce syrups and other value-added products.

Sugarcane syrup and turbinado sugar cater to specific market segments. Sugarcane cultivation and harvesting techniques, as well as irrigation and fertilizer usage, influence production costs and quality. Sugarcane and sugar beet prices fluctuate based on supply and demand, with imports and exports playing a role in market equilibrium. Traceability and sustainability concerns are increasingly important, influencing consumer preferences and regulations. Sugarcane and sugar beet varieties, processing methods, and storage techniques also impact market trends. Overall, the market remains dynamic, with ongoing shifts in production, consumption, and market conditions.

How is this Raw Sugar Industry segmented?

The raw sugar industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Liquid sugar
  Crystallized sugar


Type

  Conventional
  Organic


Base

  Sugarcane-based
  Beet-based


Application

  Food & Beverage Industry
  Biofuel Production
  Pharmaceuticals
  Animal Feed
  Chemicals


End-use Industry

  Food Processing
  Beverage Production
  Ethanol Production
  Pharmaceutical & Personal Care
  Chemical Manufacturing


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    Egypt
    KSA
    Oman
    UAE


  APAC

    China
    India
    Japan


  South America

    Argentina
    Brazil


  Rest of World (ROW)

By Product Insights

The liquid sugar segment is estimated to witness significant growth during the forecast period.

Liquid sugar, derived from raw sugar through the addition of water, is a popular choice among manufacturers due to its convenience and versatility. The sweetener's ability to dissolve quickly and evenly makes it an ideal ingredient for large-scale production of beverages, including carbonated soft drinks, sports drinks, and juices. Additionally, it is widely used in the baking industry for creating cakes, cookies, and pastries. The consistency and stability of liquid sugar enable manufacturers to control the texture and flavor of their products effectively. The sugar beet industry and sugarcane industry serve as the primary sources for raw sugar production.

Sugarcane cultivation, which includes irrigation, fertilization, and pest management, incurs significant production costs. Sugarcane diseases and pests pose challenges to the industry, affecting both yield and quality. Sugarcane bagasse and molasses are by-products used in biofuel production and ethanol manufacturing. Sugar beet cultivation, on the other hand, is practiced in regions with cooler climates. Sugarcan

This statistic depicts the average annual prices for sugar from 2014 through 2026*. In 2024, the average price for sugar stood at 0.45 nominal U.S. dollars per kilogram.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Sugar Index Poised for Volatility, Say Analysts

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The Australian sugar cane market reduced to $199.4B in 2024, with a decrease of -7.8% against the previous year. Overall, consumption, however, saw a mild expansion. As a result, consumption reached the peak level of $317.1B. From 2018 to 2024, the growth of the market remained at a lower figure.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is the Sugar Index a Sweet Spot for Investors?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Will the Sugar Index Sweeten Your Portfolio?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Sugar Futures Signal Potential Price Volatility for CRB Commodities Index

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This year, world sugar production is expected to rise by 3% to 193M tons. The growth will be encouraged by favorable weather conditions in most of the largest producing countries, as well as the providing exemptions on the neonicotinoid usage against plant diseases and blights in France, Germany and the UK. The drop in sugar production and shipments from Brazil will be offset by large volumes coming from Thailand, which will boost global exports by +2.6% y-o-y. The increased supply in the world market is to keep sugar prices relatively stable over the next two years.

The Asian sugar cane market stood at $467.9B in 2024, picking up by 2.1% against the previous year. Overall, consumption, however, saw a relatively flat trend pattern. Over the period under review, the market hit record highs at $478.2B in 2013; however, from 2014 to 2024, consumption stood at a somewhat lower figure.

Dangote Sugar Refinery PLC reported NGN151.51B in Stock for its fiscal quarter ending in September of 2024. Data for Dangote Sugar Refinery PLC | DANGSUGA - Stock including historical, tables and charts were last updated by Trading Economics this last September in 2025.

Overview
This study uses a case study approach to demonstrate the potential to estimate farm shares and price spreads in Australia using a relatively simple methodology developed by the United States Department of Agriculture Economic Research Service. In this instance, the methodology has been applied to Australian sugar price data.

Key Points
• The study demonstrates that data is available that allows an analysis of farm share and price spread for raw sugar exports and refined sugar sold at retail outlets. • The analysis shows that trends in farm shares of retail and export prices were relatively flat between 1984-85 and 2014-15. So too were trends in farm-to-retail and farm-to-export price spreads. • If it is assumed that the emergence of market power beyond the farm gate is likely to be reflected in changes in trends in farm share and price spread, then these results suggest that there has been no obvious change in market power within the sugar industry over this period.

According to Cognitive Market Research, the global Organic Sugar market size is USD 715.9 million in 2024. It will expand at a compound annual growth rate (CAGR) of 11.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 286.36 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 214.77 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 164.66 million in 2024 and will grow at a compound annual growth rate (CAGR) of 13.5 % from 2024 to 2031.
Latin America had a market share for more than 5% of the global revenue with a market size of USD 35.80 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 14.32 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.2% from 2024 to 2031.
The Sugarcane held the highest Organic Sugar market revenue share in 2024.

Market Dynamics of Organic Sugar Market

Key Drivers for Organic Sugar Market

Growing health consciousness to Increase the Demand Globally

As the health focus grows, customers are favoring herbal, minimally processed ingredients, leading to a surge in demand for organic sugar. Despite being calorically equivalent to conventional sugar, organic sugar is perceived as a healthier alternative due to its minimally processed nature. This trend displays a heightened focus on the health risks related to immoderate sugar consumption, prompting individuals to are looking for alternatives without sacrificing sweetness. The desire for organic sugar underscores a shift toward mindful eating conduct and a choice for transparency in meal alternatives. This purchaser conduct indicators a broader motion in the direction of holistic wellbeing and a deeper understanding of the impact of nutritional choices on normal health.

Government support for organic farming to Propel Market Growth

Governments global are championing natural farming thru subsidies and incentives, fostering the enlargement of organic sugar production. These supportive measures not only sell environmentally sustainable practices but also decorate accessibility to Organic Sugar for purchasers. By incentivizing farmers to undertake natural methods, governments stimulate elevated yields and force down production prices, in the long run making Organic Sugar less expensive and widespread. Such governmental aid displays a commitment to fostering agricultural practices that prioritize environmental stewardship and public health. Moreover, it signifies the popularity of the developing consumer demand for organic merchandise and the importance of assisting farmers in transitioning to more sustainable farming techniques. This concerted effort aligns with international tasks aimed toward fostering a greater resilient and sustainable meal gadget.

Restraint Factor for the Organic Sugar Market

Higher price point to Limit the Sales

The higher rate of Organic Sugar, stemming from decreased yields in natural farming, gives an assignment for a few purchasers, in particular those in price-touchy markets. While the blessings of Organic Sugar are identified, the top-class pricing can deter finances-conscious individuals from choosing it over traditional sugar. This price disparity displays the additional expenses worried in natural farming practices, along with certification, exertions-in depth strategies, and smaller yields in step with acre. Despite the better fee point, patron call for Organic Sugar keeps on to upward thrust, pushed by health and environmental worries. To deal with affordability limitations, projects inclusive of authorities subsidies and extended performance in natural farming techniques are important. Efforts to bridge the charge hole could make Organic Sugar extra available and assist the transition to sustainable agricultural practices on a broader scale.

Impact of Covid-19 on the Organic Sugar Market

The organic sugar marketplace faced both demanding situations and opportunities amid the COVID-19 pandemic. Initially, disruptions in supply chains and hard work shortages affected production and distribution, leading...

In 2024, the Europe sugar market decreased by -16.2% to $17.5B for the first time since 2020, thus ending a three-year rising trend. In general, consumption continues to indicate a pronounced downturn. Over the period under review, the market attained the maximum level at $22.8B in 2012; however, from 2013 to 2024, consumption remained at a lower figure.

In 2020, the Polish government had plans to introduce a sugar tax. As of January 1st, 2021, the new tax officially came into effect. As a result, ** percent of Poles noticed increases in the prices of sweetened beverages. According to the source, almost ** percent of those aged 18 to 29 were aware of higher prices.

The Latin American sugar market expanded slightly to $14.9B in 2024, picking up by 2% against the previous year. Over the period under review, consumption recorded a abrupt descent. The level of consumption peaked at $28.8B in 2012; however, from 2013 to 2024, consumption failed to regain momentum.

Sugar manufacturers have faced volatile commodity prices and fluctuating weather patterns over the past five years. Over this timeframe, strong export growth has helped industry revenue weather these challenges. Advanced infrastructure, like private sugarcane railway systems and strategically located bulk sugar terminals, has maximised the efficiency of transporting Australian sugar to international markets. These advantages, coupled with economies of scale from large-scale production, have made Australian sugar more competitive globally, helping to boost export volumes. Manufacturers have diversified income streams by using bagasse, a byproduct of sugar production, as a sustainable energy source, which has contributed to an improvement in industry profitability. Recently, India’s partial lifting of its export caps on sugar, imposed to prevent a spike in the country’s domestic sugar prices, has increased global supply, driving down world sugar prices. Domestic consumer preferences have shifted as awareness of health risks associated with sugar consumption has grown, leading more individuals to seek healthier alternatives. This shift has subdued domestic demand, contributing to a forecast 3.8% decline in industry revenue in 2025-26 to $3.9 billion. Overall, industry revenue is expected to climb at an annualised 2.3% over the five years through 2025-26. Over the past decade, major players have consolidated their dominance in the industry. Wilmar Sugar, Mackay Sugar, MSF Sugar, Tully Sugar and Bundaberg Sugar collectively control 95.1% of the market share. These companies have leveraged their size to negotiate more favourable shipping rates, strengthening their competitive position. Fluctuations in global demand and supply and domestic sugarcane production will continue to influence sugar manufacturers' performance. Output from the two largest global sugar producers, Brazil and India, is forecast to have the most significant influence on global supply and sugar prices. Australian manufacturers are well-positioned to expand their international presence, leveraging production capacity and efficient logistics to enhance their competitiveness in international markets and maintain exports. Industry revenue is forecast to remain relatively stable over the five years through 2030-31, at $3.9 billion.