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By:

Rajendra Joshi

3 December 2024 at 9:20:26 am

Centre pushes for early sugarcane crushing

Mills seek special subsidy Kolhapur: Despite an estimated 30-40 lakh tonnes of sugar being available in excess of domestic demand, the Centre is stepping up efforts to keep sugar prices under control. The Union Food Ministry has urged Maharashtra, Uttar Pradesh and Karnataka to advance the 2026-27 sugarcane crushing season so that fresh sugar reaches the market before the existing stock is exhausted. Sugar mills, however, say an early start will come at a cost. They are seeking special...

Centre pushes for early sugarcane crushing

Mills seek special subsidy Kolhapur: Despite an estimated 30-40 lakh tonnes of sugar being available in excess of domestic demand, the Centre is stepping up efforts to keep sugar prices under control. The Union Food Ministry has urged Maharashtra, Uttar Pradesh and Karnataka to advance the 2026-27 sugarcane crushing season so that fresh sugar reaches the market before the existing stock is exhausted. Sugar mills, however, say an early start will come at a cost. They are seeking special financial assistance to compensate for the likely fall in sugar recovery and the reduction in cane weight that could result from crushing in October. India produced around 280 lakh tonnes of sugar last season. The season began with stocks of nearly 50 lakh tonnes, while annual domestic consumption is estimated at around 280 lakh tonnes. With about 35 lakh tonnes expected to remain in stock by September 30, the Centre wants the new season’s production to start flowing into the market without waiting for the traditional crushing cycle. Maharashtra, Uttar Pradesh and Karnataka account for nearly 80 per cent of India’s sugar production. The Union Food Ministry has therefore written to the chief ministers of the three states, asking them to bring forward the start of the 2026-27 crushing season. The push comes against the backdrop of a sharp movement in sugar prices. Ex-mill prices had earlier climbed to around Rs 68 per kg, pushing retail prices close to Rs 80 per kg. Following a series of measures by the Centre, ex-mill prices have since declined to around Rs 41 per kg. Yet, the government is looking at further measures to bring prices down and ensure that stocks move into the market. One such measure has been the approval of imports of one million tonnes of raw sugar. Since initial applications covered only around eight lakh tonnes, the Centre has invited applications for the remaining quota. It has also reduced the permissible stockholding limit for traders from 400 tonnes to 200 tonnes. The next major point of discussion will be the meeting convened by Union Food and Public Distribution Secretary Sanjeev Chopra with the sugar industry in New Delhi on September 8. The secretaries of Maharashtra, Uttar Pradesh and Karnataka have also been invited. West Indian Sugar Mills Association (WISMA) president B. B. Thombre said the Centre was pushing for crushing to begin around the middle of October. Traditionally, most mills in Maharashtra begin operations around November 15, largely because sugarcane harvesting labour becomes available only after Diwali. The industry is, however, willing to explore an early start between October 20 and 25. But early crushing could have significant implications. According to Thombre, sugar recovery could fall by around 1.5 percentage points, while the weight of sugarcane supplied by farmers could decline by 10-15 per cent. The industry will therefore seek special assistance for cane crushed between October 15 and November 15. At the September 8 meeting, it plans to demand a subsidy of Rs 500 per tonne for sugar mills and Rs 300 per tonne directly for sugarcane farmers.

AI in Sperm Sorting: An Unbiased Decision for A Better Outcome

Artificial Intelligence or AI is revolutionising fertility treatments of the future. The inclusion of AI enhances the accuracy, efficiency, and objectivity of sperm selection, hence potentially improving fertility outcomes by leaps and bounds. Traditionally, sperm sorting through manual methods is subjective to judgments. Processes like centrifugation and swim-up methods are used to separate sperm based on motility and morphology. Although they are effective, they have their limitations, leading to human errors that affect the success rates of fertility treatment. For instance, studies have shown that traditional sperm sorting techniques can have variability in success rates, with reported live birth rates ranging between 15 per cent to 25 per cent per cycle depending on the method and quality of sperm. Hence the introduction of AI helps in maintaining consistency in evaluations of sperm, using the same data set for every sample which leads to better judgments.


Automation and Standardisation- Automation of sperm selection and also introduction of AI in the process have improved the results in ART. AI-assisted sperm selection improves the accuracy in choosing high-quality sperm for fertilisation purposes, and also, pregnancy and live birth rates might be improved. Technologies like Intracytoplasmic Morphologically Selected Sperm Injection along with AI ensure the chances of pregnancies increase by about 10-20 per cent compared to the standard procedures. AI and Automation will decrease time taken to analyze sperm and increase opportunities to select better sperm with DNA integrity for better development and higher success rates in embryo selection. These processes ensure that the sperm selection process follows consistent criteria, reducing variability in outcomes caused by human error.


Analysing Complex Data for Better Outcomes- AI plays a crucial in improving IVF outcomes by analysing complex data and providing tailored recommendations. AI-driven tools and models such as those on SpOvum.ai point towards an opportunity to optimise ovarian stimulation decisions by assessing patient characteristics and follicle growth patterns. A study revealed that the use of AI in IVF improved egg yield and reduced medication costs. AI enables fertility specialists to make data-driven choices, improving overall IVF success rates and streamlining treatment processes.


Reducing Human Error- AI models can continuously learn and refine their performance by being trained on newer data. This adaptability ensures the technology remains unbiased and up-to-date with the latest scientific insights into sperm quality and fertility success rates. Studies have shown that AI-driven sperm sorting can decrease human-related errors by up to 25 per cent, improving sperm selection quality in terms of morphology and motility.


Reduction of Sperm Damage- The new AI-driven sperm sorting techniques also include microfluidic systems that are known to exhibit several advantages over the most commonly used conventional method, which is centrifugation. Traditional centrifugation methods, such as density gradient centrifugation, also cause severe oxidative stress and DNA fragmentation of the sperm because of the very high mechanical forces involved. The AI-infused microfluidic sorting minimises this damage significantly by involving gentler processes that mimic the natural pathway of sperm selection. The studies show that the process of microfluidic sorting decreases DNA fragmentation in sperm, which gives improved opportunities for success for IVF. For example, DNA fragmentation is 20 percent lower in sperm sorted using microfluidic processes than in traditional processing methods.


AI is bound to play an increasingly definitive role in fertility treatments, which will improve the outcomes for couples experiencing infertility.


(The author is a Co-Founder & CEO at SpOvum® Technologies. Views personal.)

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