After publishing the previous post, I also found another fascinating graph, this time from the article on War and Heat: India under pressure:

The fertiliser production depends on gas; as the LPG becomes more scarce, the fertiliser production declines, here by nearly 40%!

What does this mean for Indian agriculture? Monsoons and the Kharif season planting are going to start soon. A 40% reduction in fertilisers is going to have a major impact on crop health, and subsequently on yield and food security.

This is a slightly different post. I have been looking at the impact of the 2026 Iran war on agriculture, partly motivated by the Substack post Heads up: food crisis incoming by Sarah Connor.

And, it was Plant Health Week last week.

So, I set Claude Cowork to collect data and produce an interactive dashboard for the major fertiliser and pesticide prices.

The impact is very clear, although in the case of pesticides/herbicides, it is probably indirect – China is a major producer and energy prices going up will affect the outputs.

The point I am making here is about potential synergistic effects. As Sarah points out, plants that do not get enough fertiliser, nitrogen, phosphorus and potassium (NPK) as well as sulfur, are weaker.

But this means that they are also more susceptible to pests and diseases.

If the cost of pesticides also goes up, farmers are hit twice: lower yield, higher losses. For annual plants, like wheat, rice, soya, the hit is confined to this year. For perennial plants, like coffee, this might be irreversible.

I have not verified the data, so the graphs below need to be used with caution, but they do make sense.

Major fertiliser & pesticide prices vs the 2026 Iran war

Weekly benchmark prices, 5 Jan – 18 May 2026. The chart defaults to index (5 Jan 2026 = 100) so very different commodities can be compared on one axis. Vertical dotted lines mark the five key events of the war. Toggle commodities on/off below the chart.

Move since 5 Jan 2026

Weekly database

Using AI wisely

Gary Marcus writes a very interesting but also very sceptical Substack on generative AI. I have found a lot of very interesting information in his posts, and I agree with many of his statements. I have recently found the following quote which captures very well his – and my – approach to AI and, in particular, AI coding tools:

AI coding tools are genuinely revolutionizing the software industry, but more than almost anything I have ever seen, they fall into the category of things you maybe shouldn’t try at home without significant prior experience

I have recently been increasing my use of generative AI, mainly for literature search and synthesis, and for coding. But I am doing it very cautiously and starting with a lot of pre-existing experience, so Marcus’ point is both a confirmation and a warning to me.

Marcus’ quote is also, I think, an excellent starting point for how we should approach educating our students. As I am looking at my teaching commitments this Autumn – a second-year statistics course and a master’s statistics course – I am fully aware that almost everything I teach them can be solved by genAI. If they use Claude Code, or a similar agentic AI, they can produce a full report including R code.

So, what is the point of teaching them how to actually carry out ANOVA, linear regression, or design an experiment? They can easily

Marcus also quotes a new paper which just appeared in BMJ – a medical research journal, with a typically understated conclusion:

The audited chatbots performed poorly when answering questions in misinformation-prone health and medical fields. Continued deployment without public education and oversight risks amplifying misinformation.

This post will appear on my Substack, StatisticallySkeptical. I have recently been really enjoying reading posts there and would like to be part of the Substack revolution – it feels at times like Twitter in the good old days!

I do not plan to fully abandon my blog here, but some of the pieces will definitely move to Substack.