Archive for September, 2013

Tropentag 2013 “Agricultural development within the rural-urban continuum” starts today

TT logoToday starts the Tropentag 2013 conference “Agricultural development within the rural-urban continuum”.

Througout the conference there will be a conference blog and continous reporting will come via @tropentag on Twitter.


Open Agrar – Repository for agricultural research from Germany

A new open access repository OPEN AGRAR provides access to the research output of five federal research institutes under the realm of the German Federal Ministry of Food, Agriculture, and Consumer Protection.

Unfortunately, the user interface is in German language only. But the papers mostly in English…

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What is (agricultural) economics worth?

The philosophers Alex Rosenberg and Tyler Curtain inquire in the New York Times about the possible contributions of economics, in spite of it’s poor track record of making reliable predictions:

[…] economics has never been able to show the record of improvement in predictive successes that physical science has shown through its use of harmless idealizations. In fact, when it comes to economic theory’s track record, there isn’t much predictive success to speak of at all. [..]

The point they make is that economic theory can make a big contribution to

[…] the design and management of institutions that will protect us from […] those parts of our selves tempted to opportunism, free riding and generally avoiding the costs of civil life while securing its benefits. […] Fixing bad economic and political institutions (concentrations of power, collusions and monopolies), improving good ones (like the Fed’s open-market operations), designing new ones (like electromagnetic bandwidth auctions), in the private and public sectors, are all attainable tasks of economic theory.

A good point, indeed.

From the perspective of an agricultural economist working on the impact assessment of agricultural research, there is another example for the worth of economics:

Even when applying only simple and stylized models, the exchange with scientists from other disciplines (i.e., those who typically develop new agricultural technologies) and decision makers (research managers and donors) about the assumptions made in these models and the results they generate adds an important — the economic — dimension to the work of these colleagues. Thereby, they become informed about aspects of their work they otherwise would neglect. This enables them to better judge the value of their work and make better decisions about the design and future directions of their research programs.

As an example, economists would apply a simple model to estimate the economic surplus effects of a given new agricultural technology. A crucial parameter in such a model is the expected adoption rate of the new technologies. In order to arrive at an estimate about this parameter, economists would discuss with crop scientists the expected magnitude of adoption. Being the suppliers and “owners” of the technology, crop scientists would tend to be rather optimistic. Economists, in contrast, would seek to factor in aspects like cost changes associated with the technology or market demand that may act as drivers or impediments to technology diffusion, and possibly arrive at more cautious estimates.

Such a discussion process will provide crop scientists with a clearer picture about the likelihood of success of their research outputs and, in particular if done for several alternative options for research and technology development, lead to better decisions about the design of a research portfolio.

Crop model calibration with yield trial data: Dealing with missing soil data

A previous blog post discussed how to deal with missing weather data when calibrating a crop model with incomplete yield trial data. A further common problem associated with the use of field trial data from crop breeders for the purpose of calibration of the DSSAT-SUBSTOR  potato model is missing or insufficient soil data.

The DSSAT soil water and nutrient routines require information of the soil found at the site, consisting of a broad range of soil physical and chemical parameters taken from different depths of the soil. The soil data provided along with yield trial data, however, often only consists of information on pH, nutrient availability, organic matter content and soil texture, taken from a sample at one single depth. In this situation, how can we obtain a complete soil profile to be used in DSSAT? Read more…

Crop model calibration with yield trial data: Dealing with missing weather data

06/09/2013 1 comment

One of our tasks in the Global Futures project was to calibrate potato cultivars in the DSSAT-SUBSTOR potato crop model with field trial data requested from CIP breeders. A common problem with the use of that kind of data was that weather data was missing. In most cases, only maximum and minimum temperature, as well as rainfall measured during the cropping season are available. The crop model, however, in addition requires solar radiation data. Furthermore, in order to carry out simulations with different planting or harvest dates, data which goes beyond the original cropping period is needed.

The approach we took to obtain a complete set of weather data that can be used with the crop model rests upon data provided by the NASA Langley Research Center POWER Project funded through the NASA Earth Science Directorate Applied Science Program. It consists of the following steps:
Read more…