Easy path for photonics in agriculture

We all know that Photonics is simply defined as “science and applications of light” (1) and therefore it is one of key technology enablers in many applications.  In particular to agriculture, photonics in agriculture is not an emerging new application and most of the time we are unaware about it (2).  For example, we have observed through our naked eyes the brightness of Sun light radiating our plants and have tried to manipulate it via low cost nets to fit the plant’s need.  We have also estimated the greenness of rice or palm fields in order to apply the appropriate amount of fertilizer.  In addition, we have used infrared radiation from incandescent light bulbs for egg incubating and hatching.

Eggs incubated under infrared radiation from incandescent light bulbs. Credit: http://articles.greenchip.com.ua/3-0-23-2.html

Eggs incubated under infrared radiation from incandescent light bulbs. Credit: http://articles.greenchip.com.ua/3-0-23-2.html

Now, with the miniaturization of electronic components and optical devices through mass production processes, several photonic modules can be implemented and gain more acceptability easily.  One simple example is in horticulture where synthetic blue and red light from low-cost light emitting diodes (LEDs) are programmed for efficiently controlling the growth rate and color of vegetables, flowers, ornamental plants, and fruits.

Blue and red LEDs can control the growth rate of plants. Credit: http://articles.greenchip.com.ua/3-0-23-2.html

Blue and red LEDs can control the growth rate of plants. Credit: http://articles.greenchip.com.ua/3-0-23-2.html

Even if we look around us, hand-held devices, especially smart phones and tablets, have been grown very rapidly.  Not only do their processing speed and storage parts get better every six months, but they are also equipped with at least one color image sensor.  With their programability, their functionalities can be extended for agriculture application.

As mentioned earlier, rather than randomly observing the greenness of rice leaves by naked eyes and then estimating the amount of nitrogen fertilizer needed for rice fields, we can snap the image of the leaf and then analyze its color by using an application program called “BaiKhaoNK” (3).  Note that BaiKhao is Thai language and it means “rice leaf.”  As illustrated in the figure below, once the color of the rice leaf is analyzed, the amount of nitrogen fertilizer is suggested on the display.

A smart mobile phone embedded with “BaiKhaoNK” application program is used to analyze the rice leaf. Credit: Sarun Sumriddetchkajorn

A smart mobile phone embedded with “BaiKhaoNK” application program is used to analyze the rice leaf. Credit: Sarun Sumriddetchkajorn

With the same principle, we can analyze the color level of the solution as well.  One application example is ClApp which is specifically implemented for the analysis of the chlorine concentration in water for baby shrimp farms (4-5).  It is designed to work in conjunction with an AppsBox and a widely used chemical indicator called o-tolidine.

“ClApp” kit used for analyzing the chlorine concentration in water. Credit: Sarun Sumriddetchkajorn

“ClApp” kit used for analyzing the chlorine concentration in water. Credit: Sarun Sumriddetchkajorn

Combining visible imaging and fluorescent imaging can also lead to an innovating approach in estimating the fruit ripeness.  In the Figure below, green fruits such as bananas and mangoes can be spatially analyzed and classified into immature, ripe, and overripe levels (6).

Spatial classification of a banana into three different ripeness levels by using a smart mobile phone. Credit: Sarun Sumriddetchkajorn

Spatial classification of a banana into three different ripeness levels by using a smart mobile phone. Credit: Sarun Sumriddetchkajorn

Acknowledgements

The author would like to thank all past and current members of Photonics Technology Laboratory at NECTEC for their work and supports.  All resources and supports provided by NECTEC are also acknowledged.

More information

1 – Optics and Photonics: Essential Technologies for Our Nation, National Academy Press, Washington, D.C., USA, 2012.

2 – S. Sumriddetchkajorn, “How optics and photonics is simply applied in agriculture?,” Proc. SPIE, Vol. 8883, pp. 888311, Chonburi, Thailand, May 2013.

3 – Intaravanne, Y. and Sumriddetchkajorn, S., “BaiKhao (rice leaf) app: a mobile device-based application in analyzing the color level of the rice leaf for nitrogen estimation,” Proc. SPIE 8558, 85580F (2012).

4 – S. Sumriddetchkajorn, K. Chaitavon, and Y. Intaravanne “Mobile platform-based colorimeter for monitoring chlorine concentration in water,” Sensors and Actuators B: Chemical, Vol. 191, pp. 561-566, February 2014.

5 – S. Sumriddetchkajorn, K. Chaitavon, and Y. Intaravanne “Mobile device-based self-referencing colorimeter for monitoring chlorine concentration in water,” Sensors and Actuators B: Chemical, Vol. 182, pp. 592-597, 2013.

6 – Y. Intaravanne, S. Sumriddetchkajorn, and J. Nukeaw, “Cell phone-based two-dimensional spectral analysis for banana ripeness estimation,” Sensors and Actuators B: Chemical, Vol. 168, pp. 390-394, 2012.


SarunPhotoSarun Sumriddetchkajorn received his B.Eng. in electrical engineering with honors in 1994 from Khon Kaen University, Thailand.  He earned his M.S. and Ph.D. in optical science and engineering in 1998 and 2000, respectively.  His research interest is in the photonic area where he applies photonics to solve problems for industrial, medical, environmental, and education sectors.

He is a recipient of the 2005 ICO/ICTP Award from the International Commission for Optics (ICO) and the Abdus Salam International Centre for Theoretical Physics (ICTP).  In 2002, he initiated the formation of the OSA, SPIE, and IEEE-LEOS Thailand Chapters.  He is a Senior Member of IEEE and OSA as well as a Fellow of SPIE and an SPIE invited lecturer.

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