Question 1 (opens 25 Nov.) What are the main achievements in the area of ICT for agriculture and rural development...
Question 1 (opens 25 Nov.) What are the main achievements in the area of ICT for agriculture and rural development in the past three to five years?
Consider the different dimensions of this broad topic and identify specific categories for the achievements. Areas to discuss may include development outcomes and "impact", business models, partnerships, the roles of different organizations, capacity development, enabling environments, technology, and more.
Please be specific and substantive in your comments, and provide links to supporting reports and information as much as possible.
Consider the different dimensions of this broad topic and identify specific categories for the achievements. Areas to discuss may include development outcomes and "impact", business models, partnerships, the roles of different organizations, capacity development, enabling environments, technology, and more.
Please be specific and substantive in your comments, and provide links to supporting reports and information as much as possible.
Dear Sergiy, thank you for sharing this. It is an interesting use of ICT that is not often discussed as you point out.
At what stage of development are these technologies? When could we expect them to be commercially available, or are they already?
Dear Michael,
Thank you for your interest in this topic. First attempts to practical use of digital image processing for this purposes are dated back to 1980-s (R. I. Olson et al. An inexpensive flow cytometer for the analysis of fluorescence signals in phytoplankton: chlorophyll and DNA distributions, J. Exp. Mar. Biol. Ecol., 1983, 68, 129-144) and resulted in clear algorithms appropriate for practical use in agriculture (R.L. Rorie et al. The assessment of leaf nitrogen in corn from digital images, Crop Sci. 51:2174–2180 (2011); S. Kawashima, and M. Nakatani. An algorithm for estimating chlorophyll content in leaves using a video camera. 1998. Ann. Bot. 81: 49-54). One of the most recent works - M. Vaher et al. Automatic spot preparation and image processing of paper microzone-based assays for analysis of bioactive compounds in plant extracts. Food Chem. 2014. 143. 465–471.
Mobile phone now can also be considered as analytical instrument – (not kidding: A. García et al. Mobile phone platform as portable chemical analyzer. Sensors and Actuators B 156 (2011) 350–359). Published algorithms can be easily implemented by average programmer and lab analyst.
So these technologies are just in one step from being implemented in market devices. But I guess if manufacturers will be interested in production of such devices due to low costs. Thus, chlorophyll meter costs approx. 1500$, while you can have almost the same results (slightly less precise) for no additional value, if you have digital camera in your phone plus some “Do-It-Yourself” skills.
By the way, chlorophyll measurements are of special interest as they allow to estimate N content (available to plant) for monitoring and operative adjustment of nitrogen fertilizer use, that is limiting factor for plant biomass in many agricultural conditions.
Hope listed references are useful fo further discussion.
Hi Sergiy
I think is very interesting your post. This is opening to us new ways to implement easy and simple protocols to "measure" new data that could offer new indicators to help the diagnosys and characterization of some critical problems, like your example in plant nutrition.
We are going to start working in a project in Spain to integrate a new indicator from digital image processing from mobile phones in field to mesure "plant leaf area" (LAI) in trees. This is a "critical" information that each grower should know every year from its plants because means "how big is its factory" and its size depends in its strategy in water and nutrientes in-puts. If we measure the weight of this plant crop and we have the number of "working days" during the crop, we have a very intuitive "performance of the plant" in each year.
We are going to start working and to adapt to spanish conditions and crops the app for smartphone to calculate leaf are index (LAI), developed by Sigfredo Fuentes et al from Adelaida and Melbourne University during 2012 “Development of a smartphone application to characterise temporal and spatial canopy architecture and leaf area index for grapevines”.
The first approach should be to test its utility, second how we could iintegrate it in a commercial farm procedures. We will test nex year in two wineries. I think you should move in that way, but i think that we must know that there is not any indicator that is the "most" important. The key point is to integrate them.
We are "recovering" interesting indicators or technologies that had commercial failure because they did not solve growers problems "alone", but integrated with other indicators they help to reach the target to create a history from failure and success that could be used as the growes know-how for future years. That is my advise to keep working.