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May 25, 2013
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Economic Sense

RSS By: Matt Bogard, AgWeb.com

Matt's primary interest is in the biotech industry and ag policy.

Big Ag Meets Big Data: Part 2

May 06, 2013

By Matt Bogard

I just came back from the SAS Global Forum conference where 'big data' was an ongoing theme, which reminded me I needed to post the second installment of my Big Ag and Big Data series. Previously I discussed the role of social media in producing ‘big data’ and tools that may be used to get the most from this data in the ag industry. In this second installment I’m going to discuss other sources of ‘big data.’

I recall once about 10 years ago attending a UK College of Agriculture field day in Princeton Ky, and someone made the comment that went something like this

"these events are good because on the farm we don’t have time to set up experiments, collect data, and analyze to figure out best practices. We can’t stop and measure and record and report about everything we do."
 
It’s certainly true that extension services will continue to conduct valuable research and it will probably remain a fact that producers aren’t going to necessarily have the time and resources to reduce their operation to a collection of well-crafted scientific experiments. However, every decision made on the farm is a trial of sorts, and with modern technology it is much easier to collect and log data about your operation, and some companies are now figuring out ways to take this farm level data and turn it into powerful analytical tools that can boost productivity and efficiency. In a recent article ‘Building Big Data: Farming Big Data Goes To The Cows’ the following statement is made:
 
 "The major problem we keep on seeing — especially in bigger, modern farms — is that there's a lot of data being created and not being used, on how they're performing, what they're doing."
How is this data being generated? Lots if it is generated via your equipment including GPS:
 
"Next generation farm equipment like combines and tillers are going to be able to take soil samples as they move along, perform analysis on those samples, and feed the results of the analysis back to the manufacturer for crunching on a macro scale. This will result in a better understanding of what is happening in that entire area and make it possible to adjust things like the amount or types of fertilizer and chemicals that should be applied. If the farm equipment manufacturers figure out how to harness all this information, this kind of big-picture analysis could change the commodity trading markets forever." – from 4 Examples of Big Data Trends. Spetember 27,2012. VmwareBlogs.
 
 And how might we use this data?  Well some seed companies are already combining farm level data, public data, and their own proprietary data to develop some pretty powerful analytical tools. As discussed recently in an AgWeb technology article Steyer seeds offers a great example with its ACRES tool which is based on a complex form of decision tree:
 

"After they sign up, customers start by selecting their fields from Google Earth maps. Back-end programming then pulls up a wealth of information – everything from soil type to yield potential. As farmers enter in additional information about their farm, such as crop rotation, traits used, etc., the ACRES algorithm spits out recommendations, which users can accept or tweak as needed." AgWeb - Unlock Your Farm Data

Another company, Climate Corporation is also taking advantage of massive amounts of data useful in agricultural applications:
 
"We took 60 years of crop yield data, and 14 terabytes of information on soil types, every two square miles for the United States, from the Department of Agriculture," says David Friedberg, chief executive of the Climate Corporation, …We match that with the weather information for one million points the government scans with Doppler radar — this huge national infrastructure for storm warnings — and make predictions for the effect on corn, soybeans and winter wheat." –New York Times
 
We’ve seen lots of efficiency, environmental, and productivity gains in agriculture related to GPS/GIS and biotechnology.  But with every trip across the field more and more data is being generated. Combining these technologies with ‘big data’ definitely will have its benefits, if not continue to revolutionize the industry.  
 
References and Further Reading:

Climate Corp. Updates Crop Insurance via High Tech. BloombergBusinessWeek. By Ashlee Vance on March 22, 2012.  http://www.businessweek.com/articles/2012-03-22/climate-corp-dot-updates-crop-insurance-via-high-tech
 
Big Data Goes to the Cows
 
Big Data in the Dirt (and the Cloud) October 11,2011. NYT. Quentin Hardy.
 
4 Examples of Big Data Trends. Spetember 27,2012. Vmware|Blogs.
 
Data analysis, biotech are key in agriculture's future sustainability
By Sarah Gonzalez
© Copyright Agri-Pulse Communications, Inc.
 
Unlock Your Farm Data
February 15, 2013
By: Ben Potter, Farm Journal Technology Editor

 

 

Consumers have a right to know!

Apr 05, 2013

By Matt Bogard

My recent discussion about labeling biotech foods may have led some to believe that I'm against informing the consumer about what's in their food. I'm not. Let's pose a hypothetical. Let's label biotech foods on the premise (supported by evidence or not) that recombinant DNA technology presents uncertainty about food safety.

What kind of label then should we put on conventional foods? Most research indicates that non-biotech foods pose nearly identical if not other more certain risks. In fact biotech ('GMO' if you must) crops actually reduce some of these risks. What about exposure to chemical weed killers? Roundup Ready biotech crops have lead to a substitution away from much more toxic and environmentally persistent chemistries toward much safer options. Biotech corn with the Bt trait actually reduces the ear mold toxin fumonisin which is known to be carcinogenic and related to throat cancer. The Bt trait in general has greatly reduced or eliminated the use of many very toxic chemical pesticides.

Researchers in the journal of Ecological Economics have found that "Bt cotton has reduced pesticide applications by 50%, with the largest reductions of 70% occurring in the most toxic types of chemicals." And that " Bt cotton now helps to avoid several million cases of pesticide poisoning in India every year."

In the journal Nature Biotechnology, Henry Miller and Gregory Conko go so far as to say that companies that purposefully exclude biotech ingredients could be liable for increasing consumers exposure to these types of risks.

This is a case where government interventions that require labeling could actually do more harm than good. Labels help consumers concerned about fat and sodium make healthy choices, however sensational 'GMO' labels could be misguiding and lead consumers  to actually make choices that are either worse for them, the health of producers, or the environment.

Consumers certainly have a right to know about what's in their food. They also have a right to not be misguided by the improper application of food labels. Our farmers and educators are in the best position to inform consumers about the very specific and complicated processes and technologies involved in food production as opposed to some blunt uninformative term on a label that could easily be manipulated for political ends or sensationalized by media.

References:

Comparison of Fumonisin Concentrations in Kernels of Transgenic Bt Maize Hybrids and Nontransgenic Hybrids. Munkvold, G.P. et al . Plant Disease 83, 130-138 1999.

Indirect Reduction of Ear Molds and Associated Mycotoxins in Bacillus thuringiensis Corn Under Controlled and Open Field Conditions: Utility and Limitations. Dowd, J. Economic Entomology. 93 1669-1679 2000.

"Why Spurning Biotech Food Has Become a Liability.'' Miller, Henry I, Conko, Gregory, & Drew L. Kershe. Nature Biotechnology Volume 24 Number 9 September 2006.

Genetically Engineered Crops: Has Adoption Reduced Pesticide Use? Agricultural Outlook ERS/USDA Aug 2000

Will including the words ‘Genetically Modified’ on food labels really serve to inform the public?

Mar 29, 2013

By Matt Bogard

 

The Role of Information Asymmetry

 

Whenever one party has better information about their product or service than the buying public, information asymmetries may exist.  Proponents of proposition 37 claimed that their initiative was to reduce information asymmetry and improve the functioning of markets, as stated in this recent Forbes article:

 

"Free markets only work when there is transparency and people are able to make decisions based on information, which does not exist in the case of GMOs. If Prop 37 is enacted, and, armed with this information, a significant enough number of consumers decide not to buy these products, the onus will be on the companies to conduct more research and produce better data."

 

Will including the words ‘Genetically Modified’  on food labels really serve to inform the public or create more confusion? This form of labeling won’t do any thing to decrease information asymmetry in and of itself. The actual language in the law may in fact make it worse. This is made clear on page 10 of a report by  Northbridge Environmental  Management Consultants (The Genetically Engineered Foods Mandatory Labeling Initiative Overview of Anticipated Impacts and Estimated Costs to Consumers):

 

"The Genetically Engineered Foods Mandatory Labeling Initiative (A.G. File No. 11-0099 – hereinafter the Initiative) would have a substantial impact on California consumers. The Initiative would change how many of the foods they eat are produced and would make that food more expensive. At the same time, however, the Initiative would provide relative little by way of consistent and useful information to consumers because of the loopholes and exceptions in its language and the uneven ways in which it would apply to the same food consumed in different settings. "

 

 If informing consumers were the primary goal, then there are much more effectivet ways to do so, perhaps in the ingredients listing following industry standards (instead of using ‘genetically modified' if a product contains GMO corn, list instead ‘rCORN’, an idea I reluctantly entertain here) If it alarms otherwise apathetic consumers, are they really going to invest the time researching the safety of biotech foods  to close the information gap or are they going to turn to the unqualified opinions of celebrities and activits?  I would bet that the special interests are counting on consumers weighing heavily the opinions of celebrities and conspiracy theorists, and therefore letting the information asymmetries associated with biotech direct them to their own products.  In this way, Prop 37 is specially designed by special interests to take advantage of information asymmetries and exploit the fears of the public in an effort to drive market share or punish companies that they have philosophical or political issues with.

 

Just Label It! What's in a name? A free market perspective on labeling gentically modified foods

Mar 25, 2013

By Matt Bogard

(re-blogged from Economic Sense- www.ageconomist.blogspot.com )

The AgriTalk March 20th podcast addressed GMO labeling and reminded me of a post I did on my personal blog some time ago. In the post I investigate:

 

 

Is there justification for government intervention requiring labeling of GMO foods?
 
In order to decide this, I identified three questions that should be asked.


Is there an uncompensated harm?

Is there sufficient information so that citizens can recognize the potential harm?

Does the market provide a way to avoid the harm?

With regard to the first question, despite unsubstantiated claims about harming monarch butterflies, finding GMO toxins in pregnant women, or killing cattle, the science does not offer a strong or definitive case that biotechcrops pose environmental or healthrisks. In fact, the precision of biotechnology and the increased regulatory scrutiny that we put GMOs through makes these modern techniques safer than traditional methods.

"Characterisation of GM crops is a legal requirement, however. As a result GM crops are better characterised than ever before in the case of conventionally bred crops, including knowledge on the site and nature of the genetic modification." (1)

So in terms of uncompensated harm, government intervention does not pass the first hurdle for justification.  Given that we can’t scientifically affirm that GMOs impose increased risks over traditional plant breeding methods, it may not be relevant to consider the next question. One might certainly argue that there is a degree of widespread ignorance related to the use of biotechnology in food production. It is a fact that 98% of all farms are family farms, and 70% or more of the corn and soybeans grown on these farms is of GMO origin. Perhaps more could be done to make consumers more aware of this fact, but it seems like it could be achieved very easily through marketing and consumer education without  government intervention. This brings us to the last question- does the market provide a way to avoid the harm? Again, without scientific evidence of harm, this question seems irrelevant. But if we want to assume that there is some remote chance of harm, the market has various mechanisms for avoiding GMO foods via organic and other branding options. Except for the most zealous advocates of government intervention in the market, it seems the case for it is quite weak.

What if people just want labels for other reasons? 

In some cases, people are not opposed to GMOs for just health reasons, but they don’t approve of the business practices of companies Monsanto. First off, labeling seems like a blunt tool to punish one company, as it could penalize the many companies in the biotech industry, as well as the family farms that overwhelmingly choose this preferred production method.  Secondly, the U.S. constitution and legal precedent may establish a role of government to establish weights and measures but this does not justify the use of labels on the basis of personal or political preferences. Personal food preferences should not be expressed in the voting booth, but through the market.

Could labeling do more harm than good?

Given the gate to plate nature of the agricultural industry, false consumer perceptions can actually do a great deal of harm to family farmers. For instance, misconceptions about finely textured beef lead to huge losses in cattle markets and 800 or more jobs in the beef industry. Or take the case of high fructose corn syrup (HFCS). Due partly in response to government intervention through sugar tariffs as well as technological advances, this new sweetener was produced by increasing fructose levels in corn syrup. The end product was technically higher in fructose compared to normal corn syrup, but it did not represent a ‘high fructose’ sweetener relative to other sweeteners such as ordinary table sugar. At the time listing the technical name ‘high fructose corn syrup’ in the ingredients of food products seemed harmless enough. However, recently many misconceptions about HFCS have made their way into the media, despite the evidence to the contrary. Similar to finely textured beef or HFCS, listing or labeling GMO ingredients could have a similar effect on consumer sentiment if this conveyed a false sense of risk or harm associated with GMO foods. This could not only have a negative impact on family farms that depend on this technology, but a government incentivized drop in consumer demand for GMOs  through labeling would also imply a loss of the actual environmental and safety benefits of this rather green technology. 

If government intervention to label GMOs were justified, how would we do it?

Playing devil's advocate, what kind of labeling would make sense? What about the current proposal in California?

"Commencing on July 1, 2014, any food offered for retail sale in California is misbranded if it is or may have been entirely or partially produced with genetic engineering and that fact is not disclosed . . . with the clear and conspicuous words Genetically Engineered on the front of the package."

This seems to be the worst example of what would be an acceptable labeling initiative. First off, placing the words ‘Genetically Engineered’ on the front of the package seems a bit extreme, and could easily be used by anti-biotech factions as a marketing ploy to mislead consumers. The very thought of making it conspicuous is a blatant  indicator that this initiative is more about political and consumer manipulation and less about disclosure of information. If identification of GMO origin is to be noted on food packaging, the appropriate place would be more inconspicuous within the ingredients listing. GMO products are used widely in the pharmaceutical industry and they have already set a precedent for how these products could be labeled.

For example, pharmaceuticals produced via biotechnology follow a common naming convention: name (rDNA origin). The ‘rDNA origin' indicates that the drug was produced through recombinant DNA technology. Food products manufacturers could follow a similar protocol:

INGREDIENTS:
SUGAR, ENRICHED FLOUR ,RIBOFLAVIN  HIGH OLEIC CANOLA OIL AND/OR PALM OIL AND/OR CANOLA OIL, AND/OR SOYBEAN OIL (rDNA origin).

Bovine Somatotropin is a currently used biotech product used in dairy production, and is often simply referred to as rbST. Instead of following a biotech food ingredient with (rDNA origin) it may be simpler to just prefix the ingredient with an ‘r’ as such:

SUGAR, ENRICHED FLOUR ,RIBOFLAVIN  HIGH OLEIC CANOLA OIL AND/OR PALM OIL AND/OR CANOLA OIL, AND/OR  rSOYBEAN OIL

This approach would identify GMO food ingredients without explicitly creating unwarranted alarm or attention. Concerned consumers could simply read through the many ingredients listed and look for the 'r' ingredient prefix or  (rDNA origin) suffix.  However, this should still be approached with extreme caution, as simply agreeing to list GMO ingredients this way admits to some extent that GMO products merit some reason for being identified in food, which again the neither science nor libertarian principles for government intervention seem to justify.  As previously stated, with only a little consumer education, consumers could easily be made aware of the prevalence of GMO ingredients in food products without reading ingredients lists. Formally identifying these ingredients in any way would seem to only serve the political ends of manipulating the free choices of consumers and producers from gate to plate.

 

Additional References:

1- European Commission (2010) A decade of EU-funded GMO research (2001–2010). Luxembourg, Belgium: Publications Office of the European Union.

 

 

Big Ag Meets Big Data: Part 1

Mar 18, 2013

An agricultural economist by training, I typically blog about policy related issues. However, by trade I spend a ton of my time doing empirical data analysis (modeling and forecasting). In the next couple posts I'm going to highlight some major trends in the ag industry related to to how we are generating and utilizing data for better informed management and policy decision making. This first post looks at the role of social media in this context.

Social media has allowed farmers to organize and communicate about their industry.  The #agchat conversations on twitter are a good example. Not to mention Facebook (see Agriculture Proud for example) and YouTube ( like this look behind the scenes of a family farm). We've seen powerful examples of how social media can be used to mobilize voices and impact perceptions on a national level ( for example issues related to Yellow Tail wine and Pilot Travel Centers).


Social media also provides a rich data source for measuring sentiment or perceptions about the industry. Take for instance text mining. With Twitter, Facebook, email, online forums, open response surveys, customer and reader comments on web pages and news articles etc. there is a lot of information available to companies and organizations in the form of text. Without hiring experts to read through all of the thousands of pages worth of text available and making subjective claims about its meaning, text mining allows us to take otherwise unusable 'qualitative' data and convert it into quantitative measures that we can use for various types of reporting and modeling. Companies are finding that by mining text from web pages, comments, blogs, and social media, they can get measure consumer perceptions almost as well or better than they can through explicit surveys or other directly measurable outcomes in their databases. In my own personal experience, I've bench marked predictions made from traditional data base variables vs. text mining and found remarkable comparisons in performance.  The  validity of these  tools is not based necessarily on their ability to make new breakthrough discoveries, but on the contrary, how these algorithms give us almost exactly what we would expect, if we had time to manually process all of the information social media provides. (For a basic example of mining tweets related to 'factory farms' see: http://ageconomist.blogspot.com/2011/04/mining-tweets-abou-factory-farms.html ).

Besides the actual text we get from social media, the actual structure of social networks can also be very informative.  Social network analysis (SNA) allows us to answer questions such as who are key actors in a network? Who are the most influential members of a network? Who seems to be acting on the peripheral? Which connections in the network are most important?  Are there key players bridging connections or information between otherwise disconnected groups? Have policies or other forces changed the overall dynamics/interaction between people in the network (i.e. has the network structure changed in any meaningful way) and does that relate to some other performance outcome or goal? I’ve recently used this kind of information to help a company develop a predictive model to improve its viral marketing campaigns.

Of course, it doesn't take a rocket scientist to read tweets, Facebook posts, or blog comments to know when people are upset about a product. But there is also a wealth of knowledge to be gained from this type of information that is so voluminous, it would take an army of social media experts to glean and analyze. This is the essence of what has been termed in the industry as 'big data.' It requires new tools for capturing, storing, processing and analyzing this data, and a new type of analyst referred to as a data scientist.  These powerful analytics could be very beneficial to those in the ag industry or agvocacy groups. But this goes beyond social media, and I will discuss how big data is revolutionizing agriculture at the farm level in the second part of this two part series on big data.

 
(Below: Visualizing 'big data' architectrue in agriculture created by Matt Bogard)
 


*Note: I’m not using the term ‘big ag’ in the derogatory sense used by anti-agricultural activists, but in a complimentary sense referring to the complex network of modern family farms, biotechnology companies, food processors, other agribusinesses and retailers that cooperate to bring healthy and sustainable food to your table.

References:

Social Media Analytics. Matt Bogard, Applied Econometric and Analytical Consulting.
http://econometricsense.blogspot.com/2012/09/social-media-analytics.html

With Hadoop, Big Data Analytics Challenges Old-School Business Intelligence. Doug Henschen, Information Week
http://www.informationweek.com/software/business-intelligence/with-hadoop-big-data-analytics-challenge/240001922
Big Bets On Big Data. Eric Savitz, Forbes.  http://www.forbes.com/sites/ciocentral/2012/06/22/big-bets-on-big-data/

Creative Commons Image Attributions:
Handheld GPS
By Paul Downey from Berkhamsted, UK (Earthcache De Slufter  Uploaded by Partyzan_XXI) [CC-BY-2.0 (http://creativecommons.org/licenses/by/2.0)], via Wikimedia Commons
Satellite: NAVSTAR-2 (GPS-2) satellite Source: http://www.jpl.nasa.gov/images/grace/grace_083002_browse.jpg Status: PD-USGov-Military-Air Force {{PD-USGov-Military-Air Force}} Category:Satellites
Tractor: bdk [CC-BY-SA-3.0 (http://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons
 

 

 

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