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Correspondent

21 August 2024 at 3:50:16 pm

Arid State

Maharashtra has finally put an official number on a crisis that farmers have been experiencing for weeks. The state government has declared 265 of its 358 talukas drought-affected, activating the first stage of its drought-management framework. The scale of the distress should make this more than another seasonal relief exercise. It is a reminder that water stress is no longer an episodic crisis but a recurring governance challenge. The state received 798.2 mm of rain against a normal 970.9...

Arid State

Maharashtra has finally put an official number on a crisis that farmers have been experiencing for weeks. The state government has declared 265 of its 358 talukas drought-affected, activating the first stage of its drought-management framework. The scale of the distress should make this more than another seasonal relief exercise. It is a reminder that water stress is no longer an episodic crisis but a recurring governance challenge. The state received 798.2 mm of rain against a normal 970.9 mm between June 1 and September 26, a deficit of 18 percent. The first drought trigger is activated when rainfall falls more than 25 percent below normal and is accompanied by a prolonged dry spell of 21 days. Though the aggregate state deficit is lower than that threshold, the taluka-level assessment has established the conditions required for intervention. Except for five districts, rainfall has been deficient across the state. The government has ordered a stay on the recovery of agriculture-related loans and restructuring of crop loans, while extending concessions on electricity bills for agricultural pumps. Employment Guarantee Scheme norms are to be relaxed; food grains provided to farmers and arrangements made for drinking water and fodder. Crop-loss surveys will determine the eventual financial assistance. While these measures can cushion the shock, they cannot solve the problem. Maharashtra has lived with drought long enough for drought relief to have become an administrative routine. The more difficult question is why the state repeatedly finds itself having to mobilise the same machinery. Tankers, fodder camps, loan restructuring and employment guarantees are indispensable when the rains fail. But they are essentially the politics and economics of response, not resilience. The state has considerable experience in watershed development, farm ponds, check dams, groundwater recharge and other forms of water conservation. Yet the effectiveness of such interventions depends less on announcing them than on where they are built, whether they are maintained and whether groundwater extraction is regulated. Large-scale water-conservation works announced as part of the present relief package must therefore be judged by measurable outcomes rather than expenditure. There is a larger agricultural question. A state with highly variable rainfall cannot indefinitely expand water-intensive cropping patterns in regions whose hydrology cannot support them. Crop choices, irrigation efficiency and groundwater management have to become part of drought policy rather than being treated as separate subjects. The present declaration should consequently be viewed as both relief and warning. While the relief is urgent, the warning is structural. The state government cannot control the monsoon but it can decide how much water it captures when the rains arrive, how efficiently it uses what it stores and how resilient its farmers are when the skies fail. A drought code can declare an emergency. But only sustained water management can prevent the emergency from becoming routine.

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

Writer: Dr. Ramnath Babu T J
Dr. Ramnath Babu T J
Nov 7, 2024
3 min read

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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