Sensors and CRISPR driving productivity and sustainability

This edible sensor could reveal what our gut microbes are up to

“Wouldn’t it be nice if our microbiomes could serve up diet advice—some science-based assurance that our food and medicines act in harmony with our resident microbes to keep us healthy? For that to happen, scientists will need to better understand how the interaction between food and microbes affects the chemical composition of our guts.” - Science

Think of how this could be used to optimize rations in livestock!

Engineers make wearable sensors for plants, enabling measurements of water use in crops

More precise and never before possible measures of phenotype through sensors can aid genetic improvements....also "The technology could "open a new route" for a wide variety of applications, the authors wrote in their paper, including sensors for biomedical diagnostics, for checking the structural integrity of buildings, for monitoring the environment" - Science Daily

Meet the Woman Using CRISPR to Breed All-Male “Terminator Cattle”

"Van Eenennaam, in fact, got the funding for the cattle project from a U.S. Department of Agriculture program looking at the potential hazards of gene-modified organisms. The department wants ways to sterilize GM organisms, including catfish and poplar trees, so their DNA modifications don’t spread to wild relatives."

"Van Eenennaam’s long-term goal is to make beef production more efficient. Males yield more meat than females and don’t get pregnant or go into heat. She thinks the ersatz males should be about 15 percent more efficient at turning grass and grain into muscle than females."

See also:

The future of independent crop consultants and killer ag apps

From:  Is Bayer’s Highly-Anticipated xarvio App the Next Uber for Ag?

"Yes, like I said this not only recognition, it's mixing four components in real-time in the nozzle. And we also are convinced that, speaking with regulatory bodies like U.S. EPA, we'll be able to register entirely new crop protection products which are resistance breaking, and we can tell them and actually prove that we are using them across only maybe 1% of the total acreage."

That seems really powerful and nothing short of just awesome. I've been talking for a long time about the convergence of big data and genomics and the impact on productivity and sustainability in this space and this is just another potential example of how this can all come together.  This also gets me thinking about an interview with Monsanto CEO Hugh Grant back in April 2016 where he discussed these kinds of applications in Monsanto's future:

"If I think about the next 30 or 40 years, I think through the use of data we’ll be applying these chemistries much more accurately and we’ll be applying them earlier, so applying them before diseases really take a hold in these crops or bugs are tearing these crops apart, so I think we’ll be more prophylactic, we’ll be more accurate and our selection of these chemistries will be a lot more discriminating. That’s kind of my vision of the future as through the use of data and bringing biology and science together, we’ll get much smarter about how we use these things, a bit like how the vision works for personalized medicine.” 

That sounds a lot like how they are describing  the Bayer xarvio app in the PrecisionAg article above. And, based on Grant's vision back in 2016, this all seems consistent with a strategy involving a Monsanto-Bayer merger.

However the article makes another interesting claim:

"The idea that a huge corporation like Bayer can largely automate and deliver agronomic recommendations remotely though a smartphone is a far greater danger to the future sustainability of any agronomic consulting operation, in this author's opinion, than a few large growers buying generic glyphosate off an online marketplace"

Based on what I have already said above, I can't doubt the value and potential disruption this app may bring with it. This makes me think of some parallels with apps and algorithms in the medical diagnosis space as well. Recently on LinkedIn data scientist Nasim Eftekhari offered an interesting perspective on this:

"With the recent news of the pneumonia detecting algorithm that has proved to be more accurate than human doctors, I see a lot of "who needs doctors anymore?" Or "are doctors going to lose their jobs?" Circulating around Linkedin. Guess who these algorithms learned from? Guess who labeled millions of images for the algorithm to find patterns? DOCTORS! What if new diseases and patterns emerge that are nowhere in the historical data? Who has to detect and interpret them? DOCTORS! 
AI can't replace doctors, but can tremendously empower them! It can give them a heads up when they don't notice a pattern they have seen before. Or for problems they have not seen before, it can help them with thousands of  similar examples and their diagnosis. It can give them access to the knowledge of smart doctors like themselves all around the world."

This reminded me of a discussion a few years back with economist Tyler Cowen on EconTalk with Russ Roberts:

"I would stress much more that humans can always complement robots. I'm not saying every human will be good at this. That's a big part of the problem. But a large number of humans will work very effectively with robots and become far more productive"

What Nasim says about doctors may largely apply to crop consulting, with some exceptions. Consulting might change, more focus on leveraging the array of tools, technology, and most importantly data being generated. As Grant noted back in the Here and Now interview:

"It takes about 40 decisions, from right around now until harvest in August or September, the grower takes about 40 decisions to produce a crop. Some of those decisions are highly technified, and others it’s because of what his mom and dad did or what he hears in the coffee shop or what he read in a magazine. So we’ve been populating those 40 decisions with data and I think by improving the quality of decisions, you increase the yield. I think the transition for Monsanto is increasingly in the next 10 years becoming a solutions-driven company, and coalescing the biology, the more accurate application of chemistry and the much smarter use of data. You know, these big green John Deere combines are streaming data off the field, one yard at a time, and it’s how you use that biological data and apply it back to the field to help growers with better insights, I think that’s going to be the next piece.” 

Taken one  decision at a time it might seem that a producer could cut out the middle man with a combination of a few apps. But they still might need someone that can step back and take a big picture systems view of the operation- that's where consultants can provide better insights and continue to create value. The way they do it just might not be the way I did 20 years ago with pen, paper, and a yardstick trotting across the field.

Food Costs, Satellite Data, and Diversity within Species

Russ Roberts talks with Tomar Haspel about food costs, animal welfare, and modern agriculure on EconTalk.

A couple great discussions regarding the future ag macro environment and satellite based crop data in finance.

More on the myth of monoculture - biodiversity within species in Nature.

"the health of an ecosystem may depend not only on the number of species present, but also on the diversity of their traits. …Equally important to keeping an ecosystem healthy and resilient are the species' different characteristics and the things they can do — measured in terms of specific traits such as body size or branch length."

See also:

Big Data + Genomics  Not Your Grandparent's Monoculture
Crop Diversity

The Convergence of Big Data and Genomics in Agriculture

Several links to some posts I've done over the years across a number of blogs related to the convergence of big data and genomics in agriculture:

Transforming a Company for a New Kind of Agriculture (WillAg closing market report w/Robb Fraley)
Big Data + Genomics != Your Grandparents Monoculture
Big Data (agriculture schematic)
Big Data vs Clean Data
Big Ag Meets Big Data (Part 1 & Part 2)
Big Data- Causality and Local Expertise are Key in Agronomic Applications
Big Ag and Big Data-Marc Bellemare
Big Data, IoT, Ag Finance, and Causal Inference

Monsanto CEO Hugh Grant on Here and Now

Nice interview: http://hereandnow.wbur.org/2016/03/30/monsanto-ceo-hugh-grant

I particularly appreciated the commentary related to the convergence of big data and genomics:

What’s the next step for Monsanto? What will you be building next?

“We were a chemical business that became a biotech and biology business that morphed into a seed business. I think the main transition as you look forward is the application of data. It takes about 40 decisions, from right around now until harvest in August or September, the grower takes about 40 decisions to produce a crop. Some of those decisions are highly technified, and others it’s because of what his mom and dad did or what he hears in the coffee shop or what he read in a magazine. So we’ve been populating those 40 decisions with data and I think by improving the quality of decisions, you increase the yield. I think the transition for Monsanto is increasingly in the next 10 years becoming a solutions-driven company, and coalescing the biology, the more accurate application of chemistry and the much smarter use of data. You know, these big green John Deere combines are streaming data off the field, one yard at a time, and it’s how you use that biological data and apply it back to the field to help growers with better insights, I think that’s going to be the next piece.”


Do you ever envision a pesticide-free Monsanto?

"If I think about the next 30 or 40 years, I think through the use of data we’ll be applying these chemistries much more accurately and we’ll be applying them earlier, so applying them before diseases really take a hold in these crops or bugs are tearing these crops apart, so I think we’ll be more prophylactic, we’ll be more accurate and our selection of these chemistries will be a lot more discriminating. That’s kind of my vision of the future as through the use of data and bringing biology and science together, we’ll get much smarter about how we use these things, a bit like how the vision works for personalized medicine.” 

See Also:
Big Data + Genomics is not your grandparent's monoculture
Big Data: Causality and Local Expertise Are Key in Agronomic Applications 
Agritalk Discussion of Biotechnology, Big Data, and Genomics on Seed Choice

How Big Data and Genomics are Crushing the Myth of Monoculture

From: Multi-hybrid corn planter trials in Corn and Soybean Digest (link):

"If multi-cultivar planters gain significant market share in coming years, farmers could see a big shift in the corn hybrids and soybean varieties available to plant in unique field environments, says Jason Webster, Beck’s Hybrids research agronomist…….“We may have customized hybrids for certain soils that never would have been released in the past,” he says."

This is in line with what I have said before (see Big Data + Genomics ≠ Your Grandparent's Monoculture):

"the disruptions of new technology, big data and genomics (applications like FieldScripts, ACRES, MyJohnDeere or the new concept Kinze planters that switch hybrids on the go etc.) will require the market to continue to offer a range of choices in seeds and genetics to tailor to each producer's circumstances of time and place. There are numerous margins that growers look at when optimizing their seed choices and it will require a number of firms and seed choices to meet these needs as the industry's focus moves from the farm and field level to the data gathered by the row foot with each pass over the field."

The convergence if big data and genomics is driving more diversity into every seed in every field across every acre.