How machines are learning to recommend the right crop season

How machines are learning to recommend the right crop season


Agricultural productivity in India is lower than in some other countries. Wheat yield, for instance, is roughly 2.7 tonnes a hectare in India, compared with 6 tonnes in China.

Technological aids such as drones and sensors are helping step up agricultural output, but artificial intelligence (machine learning) can prove to be an even bigger game changer, especially in determining which crops to grow next for improved yields and profits.

‘ML-based crop recommendation systems’ is the next big thing in agriculture today. With over 145 million small farms in India, most under 1.1 hectares, farmers need clear, data-based guidance to choose the right crops for better income and resilience against climate change.

In this, two independent researches have concluded that the ‘random forest’ ML model has the highest prediction accuracy. The ‘random forest’ model combines multiple ‘decision trees’ — ML algorithms that use tree-like structures to make predictions.

The first study is by scientists Steven Sam and Silima Marshal D’Abreo of the Brunel University, London. They examined 12,389 data points of 19 crops in 15 Indian States during 2011-14.

“We combined environmental and economic input parameters to develop and evaluate the accuracy of two machine-learning models (‘random forest’ and ‘support vector machines’) for recommending high-yield and profitable crops to farmers,” the authors say in a yet-to-be-peer-reviewed paper.

They concluded that ‘random forest based on lag variables’ (past values of a data point used to predict the future) is the most accurate.

Diverse conditions

The researchers tested two computer-based models to see how well they could suggest the right crops. One method showed high accuracy but wasn’t realistic because it didn’t consider how crop conditions change over time.

To balance accuracy with real-world usefulness, the researchers introduced ‘lag variables’, which improved the model’s performance. In the end, the model using the random forest method with the time-aware approach worked best for crop recommendations in India.

The study highlights that an examination of both market and environmental factors produces better advice for farmers. It also suggests that future improvements should include more data like market demand, prices and returns, to make the recommendations even more suited to India’s diverse farming conditions.

Another research paper, titled ‘Crop recommendation system using machine learning’, by researchers at the Prakasam Engineering College in Kandukur, Andhra Pradesh, has also concluded that the random forest model is the best, with accuracy of 99.3 per cent.

“The system successfully recommends optimal crops across 22 different crop categories, contributing to improved agricultural productivity and sustainable farming practices,” say the authors of the paper, Dr M Lakshma Rao and his student Soprala Naveena.

“The crop recommendation system represents a successful integration of machine learning technology with agricultural science, creating a tool that bridges the gap between sophisticated analytical capabilities and practical agricultural applications,” they say, adding that the system “serves as a proof of concept for the broader potential of artificial intelligence and machine learning to support sustainable, productive and equitable agricultural systems”.

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Published on June 29, 2025



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Pale blue-green dot

Pale blue-green dot


Astronomer Carl Sagan famously had Voyager-1 turn briefly and snap a picture of the earth — a ‘pale blue dot — from 3.7 billion miles away.

Back in the Archean eon (3.8-1.9 billion years ago), that image would have been a ‘pale green dot’ — there was little or no atmosphere on earth, and the oceans were green, as a group of Japanese scientists have deduced.

There were only single-celled organisms in the oceans, making food from the iron dissolved in the water — a process that released oxygen and led to ‘the great oxidation event’ about 2.4 billion years ago.

Iron deposits from this period, known as banded iron formations, show layers of oxidised and unoxidised iron, recording this key environmental shift.

Japanese researchers studying the greenish waters around the volcanic island of Iwo Jima found similarities to ancient oceans. The green of the water is due to oxidised iron and supports blue-green algae — primitive bacteria that can use both green and white light for photosynthesis.

In the future, sulphur from volcanic activity could see purple bacteria proliferating. And if oxidised iron enters the oceans, you may have rolling waves of red.

An unprepossessing sight, for sure!

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Published on June 15, 2025



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Chemistry for everyone

Chemistry for everyone


The 75th edition of the Yusuf Hamied Chemistry Camp at IIT-Bombay was designed specifically for visually impaired students

Indian Institute of Technology, Bombay, recently hosted the 75th edition of the Yusuf Hamied Chemistry Camp, designed specifically for 59 visually impaired students from government schools in Mumbai, Nashik, Pune and Solapur. The landmark event reaffirmed a powerful message: chemistry is for everyone.

Supported by the Royal Society of Chemistry (RSC) and funded by Dr Yusuf Hamied, the camp provided a first-of-its-kind, hands-on opportunity for blind students to explore the wonders of chemistry through the senses of touch and smell. This year’s camp — developed under the leadership of Dr Swetavalli Raghavan, Head of Innovation Strategy and Government Affairs at RSC — featured a brand new module developed by Prof C Subramaniam of IIT-Bombay.

“Given that chemistry is about colour and visual perception, designing the experiments to convey concepts with clarity was intellectually stimulating and provided a unique peek into the day-to-day lives of these children,” says Subramaniam.

The camp focused on fun, sensory-based experiments — tactile molecular models, scent-based chemical identification, concepts in physical chemistry such as levitating magnets, and safe experiments that allowed students to feel textures and temperature changes during reactions, says a press release from IIT-Bombay.

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Published on June 15, 2025



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How best can India, and the world, deal with China’s chokehold on magnets?

How best can India, and the world, deal with China’s chokehold on magnets?


STRONG PULL: China holds nine-tenth of the world’s reserves of neodymium, key to making rare earth magnets
| Photo Credit:
Nelson Ching

When Masato Sagawa revolutionised industry by inventing a strange concoction of elements — neodymium, iron and boron — that could be powdered and sintered into an alloy of exceptional magnetic properties, little could he have foreseen that he was putting the world in the stranglehold of China.

By a quirk of fate, China not only has about nine-tenths of the neodymium discovered on planet earth, but also large swathes of sparsely inhabited land in the Inner Mongolia region, where it refines neodymium without facing as much as a murmur of protest over the environmentally hazardous process.

And today, China is flexing its biceps by placing export restrictions on neodymium. Magnets are at the core of everything from motors to transformers; China holds the cards.

“It is a global problem,” says Dr D Prabhu, scientist at Hyderabad-based International Advanced Research Centre for Powder Metallurgy and New Materials (ARCI), who has worked extensively on magnets.

Sobering challenges

On the quest for alternatives to magnets from China, Prabhu drove home a sobering reality. “All the leading scientists of the world,” he said, “are of the view that for at least the next two decades, there is nothing that comes even close to neodymium-iron-boron (NIB) magnets.”

The expert reeled out some discouraging numbers. NIB has ‘maximum energy product’ — a measure of the magnetic energy a material can store — of 35-52 MGOe (mega gauss oersted); the next best is samarium-cobalt, with 17-26 MGOe.

The common ferrite magnets have 3-5 MGOe. (The more familiar ‘tesla’ unit of magnetism measures the strength of a magnetic field at a given point.)

What about samarium-iron-nitride (SmFeN)? There are tomes of scientific literature extolling SmFeN’s virtues, with some even talking of it as a replacement for NIB. Mouthwateringly, samarium is available in sufficient quantities in India.

Sorry, says Prabhu. Indeed, SmFeN has MGOe numbers that can rival NIB’s, but it is impossible to produce through the conventional sintering process — the material decomposes at high temperature. Yes, one can make ‘bonded magnets’ with SmFeN, using materials like resin, but their MGOe numbers are much lower.

Despite these disheartening scenarios, India (and the world) may still have ways to counter China’s dominance over powerful magnets.

Way forward

Here’s what lies within the realm of possibility.

One, finding more neodymium is the world’s best hope. Australia has begun digging for it. With large uninhabited areas, it can possibly do its own refining, too. But that is just hope — and a long-term option.

Two, finding a way to make SmFeN magnets with high MGOe. Technologists are working furiously on this. In a paper published in Materialia, a group of American scientists (including three of Indian origin) say they have developed an SmFeN magnet with MGOe of 23.4, using metals such as aluminium, copper, iron and zinc as binders, instead of resin. The magnet, they add, displays high coercivity, which measures its resistance to de-magnetisation.

This option, too, is still in the labs; it must cross the ‘valley of death’ to the industry. Not an option for Monday morning.

Yet, the industry can switch to SmFeN bonded magnets wherever possible. SmFeN magnets with MGOe of around 25 are hitting the market.

A February 2025 market research found that these magnets are good for applications in certain areas of electric vehicles, robotics, consumer electronics and wind turbines. That said, it should be noted that SmFeN manufacturing technologies are heavily patented, and India needs to develop its own process. Some experts have called for a ‘national mission on magnets’.

Three, reducing the quantity of neodymium needed per magnet, by inventing processes that slash wastage — such as ‘near net-shaped’ magnets. While permanent magnets are typically made by magnetising blocks of material and then cutting and machining them to the desired size, near net-shaped magnets are made directly to the desired shape, cutting wastage of material.

In fact, such a process has been developed and patented by Sagawa, who has licensed it to ARCI. The ARCI is putting up a first-of-its-kind pilot project in Hyderabad. A team of ARCI scientists, including Prabhu, are in Japan for training. The project could start next month, and the first magnet is likely to roll out in six months.

Four, developing products such as EV motors that can work with indigenous magnets.

One example is a motor developed by Chennai startup Viridian Ingini Propulsion. The ‘permanent magnet-assisted synchronous reluctance motor’, a kind of hybrid motor, uses ferrite magnets that can be easily made in India. Viridian is readying to produce these motors for electric two- and three-wheelers.

Sagawa, 81, is still active. It is not known if he rues the fact that his singular invention has unwittingly added geopolitical muscle to China, but the octogenarian may still have some tricks up his sleeve. He is said to be favourably disposed towards India. One lives on hope.

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Published on June 15, 2025



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Creep-resistant aircraft part

Creep-resistant aircraft part


In aircraft engines, nickel-based superalloys are extremely important — they make up about half the weight of the engine because they can withstand very high temperatures and stress. One such alloy is Inconel 718 (IN718), valued especially for its creep resistance — that is, ability to resist deforming when exposed to high heat for long periods. This makes it ideal for jet and rocket engine parts.

However, when IN718 is made using additive manufacturing (AM) — a 3D printing-like process — its creep resistance is worse than when made the traditional way (called ‘wrought’ processing).

The reason for that wasn’t clearly understood — until now.

Researchers at IIT-Madras have discovered both the cause and the solution.

They found that in AM-processed IN718, a metal called niobium doesn’t spread evenly. Instead, it gathers at the grain boundaries — the microscopic zones between crystal-like regions in the metal. This unevenness creates soft spots next to the grain boundaries, known as precipitate-free zones (PFZs), which are weak and reduce the metal’s ability to withstand creep.

In traditional methods, these problems are fixed later, during the forging and heating steps, which helps niobium spread evenly. But in AM, where parts are printed directly to shape, this step is skipped, and the segregation problem remains.

To fix this, the researchers tried heating the AM metal to a higher temperature (1,150 degrees C) than usual, giving niobium atoms more energy to move and spread out. They carefully balanced this to avoid damaging the metal’s structure. “The long-term exposure heat treatment methodology demonstrates that PFZs are the major influencing factor responsible for microsegregation-dependent creep rupture behaviour,” the scientists say in a paper.

The new treatment successfully removed the soft PFZs and made the material much more creep-resistant — improving its performance by five times compared to the standard heat treatment.

This breakthrough could make 3D-printed IN718 parts practical for real-world use in aircraft and space engines.

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Published on June 15, 2025



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