field and weather monitoring with youths as sensors for

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Available online at www.jstage.jst.go.jp/

Agricultural Information Research 21(3), 2012. 65–75

Original Paper

Field and Weather Monitoring with Youths as

Sensors for Agricultural Decision Support

Takashi Togami1), Seishi Ninomiya2), Kyosuke Yamamoto2), Yumiko Mori3), Toshiyuki Takasaki3),

Yasukazu Okano3), Ryoichi Ikeda4), Akane Takezaki5) and Takaharu Kameoka*1)

1) Graduate School of Bioresources, Mie University, 1577 Kurimamachiya, Tsu, Mie 514-8507, Japan

2) Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo 113-8657, Japan

3) NPO Pangaea, Shijo Hirano Bldg. #402, 716-1 Shin Kamanza, Shimogyo, Kyoto 600-8471, Japan

4) Faculty of International Agriculture and Food Studies, Tokyo University of Agriculture, 1-1-1 Sakuragaoka, Setagaya,

Tokyo 156-8502, Japan

5) National Agricultural Research Center, National Agriculture and Food Research Organization, 3-1-1 Kannondai, Tsukuba,

Ibaraki 305-8517, Japan

Abstract

In Vietnam, proper and continual agricultural engineering guidance for local farmers is required to improve rice cultivationand conserve environment, yet there are issues in the low literacy rate of adults and information dissemination. In order toresolve the issues, the YMC-Viet project, based on the Youth Mediated Communication (YMC) model in which youthsmediate communication between local farmers and agricultural experts in remote locations, was proposed. It is inadequateonly to unilaterally extract problems from farmers and provide guidance. Advice can be further optimized by providing localquantitative data to agricultural experts. Accordingly, information collection to accurately comprehend local environmentalconditions and the rice growth situation is indispensable. However, there is no weather station in the target area andenvironmental information is severely lacking. In addition, the number of agricultural experts in the area is extremely lowand gaining an understanding of the field situation is almost impossible. In this research, therefore, we devised a method toregularly collect environmental and field situation information, by having youths working as weather and field sensors, andutilizing the collected data for agricultural decisions supported by agricultural experts in remote locations, and its efficacywas verified. Then, we created a cultivation knowledge resource and applied it as a contrivance for youths to adequatelyinform agricultural experts about field growth situations based on collected information. As a result of the experiment, it wasrevealed that youths met more than 85 percent of the requirements of temperature and humidity measurement and weatherobservation. Additionally, the data collected and the records showed higher potential by agricultural experts for utilizing thedata in agricultural decision support. Moreover, it was confirmed that sometimes youths functioned as disorder and defectdetectors. Thus, the efficacy of youths as sensors in terms of collecting information for agricultural support was verified.

Keywords

youths as sensors, agricultural decision support, information collection, cultivation knowledge resource, YMC Model

Introduction

Agriculture is the basic industry in Vietnam and agricultural

produce, especially rice as their principle product, is necessary to

improve competitiveness in the international market. In order to

achieve it, stably produced high quality rice is required.

Until now, the yield amount has been secured, yet the level of

farmers’ rice cultivation technique in the country is low and the

overall product quality is extremely low. Moreover, there are

issues of cost and environmental conservation due to high density

planting and excess fertilization. Hence, the Vietnamese govern-

ment has been promoting a shift in policy to one of resource and

environmental conservation (Hung 2008).* Corresponding Author

E-mail: [email protected]

Field and Weather Monitoring with Youths as Sensors for Agricultural Decision Support

66

However, degradation in land capability caused by excess fer-

tilization has been observed, with the cause of fertilization being

local farmers’ unquestioning belief, from ignorance, that fertiliza-

tion directly leads to a secure yield. As a consequence, concern

about the stability of farming has been rising. Thus, the imple-

mentation of appropriate and continual technical guidance for

farmers is necessary.

In recent years, studies aiming to accurately disseminate infor-

mation on a sophisticated agricultural technique have been

widely conducted. For instance, Reddy and Ankaiah (2005)

proposed a cost effective agricultural information dissemination

system (AgrIDS) with the purpose of delivering expert agricul-

tural knowledge to farming communities in India in order to

increase crop yields. Another example is the research by Ratnam

et al. (2006), which describes the dissemination of customized

information to farmers using an IT based personalized agricul-

tural extension system (eSagu). Similarly, Armstrong and

Diepeveen (2008) described the results of a case study of the

Farmer Decision Support Framework (FDSF). Additionally in

Japan, Kamiya et al. (2011) developed the web-based interface

for sharing cultivation information among local communities.

However, there was a problem with information dissemination

in a rural area of Vietnam due to the illiteracy issues of adults.

In order to solve the problem, the YMC-Viet project was pro-

posed (Mori et al. 2011). In this project, the YMC model (Mori

2009) was applied and farmers and agricultural experts, with the

mediation of educated youths, communicated with each other.

However, it is inadequate only to unilaterally extract problems

from farmers and provide guidance. Further optimization of the

advice should be carried out by providing local quantitative data

to agricultural experts in remote locations.

In order to do this, information collection to accurately assess

local environmental conditions and the rice growth situation is

indispensable. In this regard, nowadays, research using an envi-

ronmental monitoring device and a sensor network has widely

been conducted (Wang et al. 2006, Ruiz-Garcia et al. 2009). We

have also worked on research into agro-environmental monitor-

ing in terms of utilizing data on olive cultivation (Togami et al.

2010), research using a wireless sensor network in a mandarin

orange orchard (Togami et al. 2011a) and in a vineyard for smart

viticulture management (Togami et al. 2011b). However, it is

difficult to install monitoring devices in Vietnam in local areas

where power supplies and network infrastructures are undevel-

oped.

Utilizing middleware, such as MetBroker (Laurenson et al.

2002), which accesses many different weather databases and

provides weather data, is a possible solution, yet there is no avail-

able weather station in the area and environmental information is

severely lacking. In addition, the number of agricultural experts

in the area is extremely low and gaining an understanding of the

field situation is almost impossible.

In this research therefore, we devised a method whereby

youths worked as weather and field sensors, regularly collecting

environmental and field growth situation information, with

agricultural experts utilizing the information from the youths for

agricultural decision support, and we attempted to comprehend

the feasibility of data collection and the efficacy of information

exchange facility by youths as sensors. Then, we created a culti-

vation knowledge resource and applied it as a contrivance for

youths to adequately inform agricultural experts in remote loca-

tions about field and growth situations based on collected infor-

mation.

Materials and Method

Details of demonstration experiment

In this research, the target area is Thiê.n My~, Trà Ôn District,

Vinh Long, Vietnam, which is about 30 square kilometers shown

in Fig. 1.

Before carrying out this research, the hearing survey to 30

farmhouses was conducted. Table 1 shows a part of the results of

the survey and it presents typical 5 of 30 farmhouse answers.

According to the survey, minimum acreage is 0.15 hectares while

maximum acreage is 2.2 hectares, and the average is 0.57 hec-

tares. In regard to the approximate distance between paddy and

house where youth observes the weather, minimum distance is

about 120 meters, maximum distance is about 2,800 meters and

the average is 607 meters. Cultivar varies among farmhouses

Fig. 1 Location map of Thiê.

n My~, Trà Ôn District, Vinh Long,Vietnam (Map obtained from Google Maps <http://maps.google.com/maps>)

Agricultural Information Research 21(3),2012

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and OM 4900, OM 4218, Jasmine 85, IR 50404 and OM 1490 are

cultivated.

After the survey, 30 youths from 29 farmhouses of the 30

farmhouses were selected and their ages are from 11 to 15. In

addition, their parents have low literacy levels.

The official project period is from mid-February to the end of

March in 2011, and the period falls under the growth stage

between seedling stage and meiotic stage.

Determination of measurement components, instruments and

intervals

In order to have youths working as weather and field sensors, it

is critically important to set minimum yet effective measurement

components and numbers of measurements which do not become

a burden on the youths. Otherwise, it is likely that the youths will

abandon the role and not function as sensors.

Hence, an agricultural group, consisting of agricultural experts

and researchers, an agricultural terminology researcher, a child

education expert and a systems architecture expert, was formed

to determine the measurement components, instruments and

numbers of measurements necessary to interpret the crop growth

situation, crop conditions and field conditions, and to provide

advice on the next action.

Table 2 summarizes the measurement components, instru-

ments and numbers of measurements. Five measurement compo-

nents were set: temperature and humidity, weather, crop height

and leaf color. In addition, two tasks were also given to youths to

comprehend field situations. One is the observation and counting

of insects and the other the digital image acquisition of rice

leaves, rice stems and any defects in the paddy field. The relation

and necessity of each component to rice cultivation follow.

Temperature and humidity

Air temperature and humidity induce the sterility of rice. For

example, Matsui et al. (1997) described the relation between

the spikelet sterility of Japonica rice at flowering and air temper-

ature, humidity and wind velocity conditions. According to

Weerakoon et al. (2008), in tropical rice-growing ecosystems,

high temperature-induced grain sterility in rice became a serious

problem. Therefore, it is important to measure temperature and

humidity in the target area.

Weather

Climate conditions influence rice growth. Kawatsu et al.

(2007) reported changes in weather conditions and their effects

on rice production using a data set covering 40 years in Japan.

Thus, weather observation in the target area should be imple-

mented for stable rice production.

Crop height

For the growth diagnosis of rice plants it is necessary to meas-

ure the height of the rice. For example, elongated seedlings

appear to be caused by Bakanae disease (Naito et al. 2008).

Hence, even in Vietnam, it is assumed that measurement of crop

height is important to detect an affected rice plant earlier and to

monitor rice growth.

Leaf color

Leaf color is one of the most important indicators for the

growth diagnosis of rice plants. Islam et al. (2007) presented the

research results for nitrogen use efficiency in rice using rice leaf

color charts. Additionally, a lesion also appears on rice plants and

it is easily recognized by its color. Even though there are a lot of

cultivars grown in the target area, leaf color can be used to diag-

nose a rice plant.

Insect count

The amount of insect pests emerging varies yearly and season-

ally in each field, and the variance relates to the stage in rice

growth and the fertilization system (Inoue and Fukamachi 1990,

Miyashita and Kawanishi 2003). In addition, insect pests influ-

ence rice quality and the volume of production. For instance,

Miyashita (1985) reported the relation between the amount of

production and injury to rice leaves by rice leafholder at two dif-

ferent growth stages. Thus, although location and fertilization

system of target area is different from above research reports, it

can be thought that insect count is crucial for appropriate pest

control.

Table 1 Result of hearing survey: Farmhouse description

No.Youth

ID

Acreage

(ha)

Approximate

Distance between

House and Paddy (m)

Cultivar

3 3 2.2 240 Jasmine 85, OM

4900, OM 4218

4 4 0.4 350 IR 50404, OM 4900

5 5 0.5 470 OM 4900, OM 1490,

IR 50404

20 20 0.4 1,060 OM 1490, Jasmine 85

26 26 0.5 180 OM 4900

The table above presents typical 5 of 30 hearing survey results.

Table 2 Measurement components, instruments and intervals

Measurement

Components

Measurement

Instruments

Measurement

Intervals

Temperature and Humidity Thermo-hygrometerDaily

Weather Kids’ Eye

Crop Height MeasureTwice weekly

Leaf Color Leaf Color Chart


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Digital photographs

Digital photographs help the youths communicate properly

with the agricultural experts and also help the experts diagnose

rice plant conditions and provide action advice. Therefore, digital

photographs of rice plants can be a strong communication tool.

There are two different intervals of measurement determined in

this research. One is daily measurement and the other is twice

weekly measurement. The components of daily measurement

comprise a collection of data that becomes the backbone for

scientifically interpreting crop growth and condition, and are

necessary for the later use of analysis and development of crop

growth simulation. Twice weekly measurement components

were set for the purpose of assessing the changes in crop growth

and field environment over the seasons.

Data collection method

In order to support youths for data collection, a specialized

booklet called YMC passport was created by NPO Pangaea

shown in Fig. 2a, and provided to each youth. This booklet con-

sists of several components such as notebook for the weather

observation (Fig. 2b), notebook for questions from parents to

agricultural experts and the answers (Fig. 2c), measurement

instructions (Fig. 2d) and insect pest reference (Fig. 2e). All

youths use YMC passport during the project.

There are two data collection flows corresponding to daily and

twice weekly measurements. Daily, youths read the temperature

and humidity values from a thermo-hygrometer (Fig. 3a) placed

outside of each house and observe the weather; then, they record

them in the YMC passport and subsequently, they send the

recorded data to the YMC system’s server using mobile phones,

as shown in Fig. 3b. Twice weekly, the youths go to their respec-

tive rice paddies and implement four tasks. First, they measure

the height of the rice with the tape measure provided (Fig. 3c).

Second, they check the rice leaf color against a leaf color chart

Fig. 2 YMC passport: a) Front and back cover, b) Notebook for observation, c) Notebook for question and answer, d) Measurementinstruction, e) Insect pest reference

Fig. 3 Measurement tools: a) Thermo-hygrometer, b) Mobile phone, c) Tape measure, d) Leaf color chart, e) Bug search board


69

(Fig. 3d) and record the closest numbered color on the chart.

Then they record both the rice height and leaf color results in the

YMC passport. Third, they check the insects with a bug search

board (Fig. 3e), for the purpose of pest control, by holding the

board in one hand and beating the rice plant with other and then

counting the fallen insects. If the number is greater than 15, they

take a digital photograph with the mobile phone provided, which

has a camera with a resolution of 1.3 mega pixels, and send the

photographs, with a report, to an agricultural expert since 15

insects on one rice plant can be interpreted as an extraordinary

situation. Lastly, they take digital photographs if there is any

defect on the rice or in the paddy.

Normally, repeated measurement is necessary for measure-

ments. In addition, it is necessary to measure crop height of

several rice plants and use the average value as the crop height.

In this research however, the observation and measurements are

carried out by youths. Hence, it is critically important to minimize

the burden on youth to make them function as sensors, which is

mentioned in earlier section. Thus, the number of determinants

for all measurements was set to one. In regard to the time of

measurement for daily measurement and weather observation, it

was not definitely set since youths go to school. Therefore, it was

set to before going to school as much as possible.

In order to minimize errors in measurement and data collection

under the difficult situation as mentioned above, a briefing

session and a training session for the use of measurement tools

and for measurement were held before this research. Then, with

regard to crop height, youths were instructed to measure the

ground from the highest leaf or the highest ear of a rice plant.

Creation of cultivation knowledge resources

Cultivation knowledge resources were created with two pur-

poses; one, in order for youths to adequately inform agricultural

experts in remote locations about the field and growth situations

based on collected weather and field information, and the other,

so that agricultural experts can give optimal advice and properly

convey the information.

With regard to proper information exchange, it was essential to

prepare knowledge resources in Multilanguage in this project.

Accordingly, cultivation knowledge resources were prepared in

three languages; Japanese, English and Vietnamese. Then, the

translation was supported by the Language Grid (Ishida 2011),

which provides multilingual communication support and is an

online multilingual service platform.

Fig. 4 shows the creation flow for the cultivation knowledge

resources. At first, categorization of the components in relation to

rice cultivation, such as plant physiology, rice paddy and irriga-

tion, was implemented among the agricultural group in order to

organize rice cultivation knowledge. In the categorization, main

categories, subcategories, which relate to each main category, and

sub-subcategories, relating to each subcategory, were created.

Next, in accordance with the main categories, drafts of the cul-

Fig. 4 Cultivation knowledge creation flow


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tivation knowledge resources for experts’ use were created based

on specialized books, research papers, articles and web materials.

After that, for ease of understanding and to create correct

knowledge, the drafts were checked and corrected by agricultural

group members. Then, they were accumulated as the knowledge

resource. After the first check of drafts by the experts, cultivation

knowledge for the youths’ use was created as a parallel text

corresponding to the corrected drafts.

Results

Functionality of youths as sensors

During the official project period, each youth was to conduct

47 daily measurements and 13 twice weekly measurements.

Table 3 summarizes the result of the fundamental statistics for

each task.

For the daily task, on average, 41 measurements were con-

ducted, and the median, larger than the mean, and the negative

value of the skewness indicate that each frequency distribution

curve is skewed to the right. On the other hand, one youth

performed only 20 daily measurements, which is a 43 percent

satisfaction rate.

From the statistical results of the twice weekly task, it was

revealed that the youths, on average, conducted 11 measure-

ments, which is about an 85 percent satisfaction rate, but one

youth implemented only about 62 percent of the required tasks.

In addition, both medians and the skewness reflect that each

frequency distribution curve is skewed to the right.

With regard to the photographs, the number of updates indi-

cates the number of uploads while the number of images indicates

the number of digital photographs taken by each youth. This task

was at the youths’ discretion and youths took photographs at their

paddy fields whenever they detected any defects. Therefore, the

maximum number of updates corresponds to the maximum num-

ber of twice weekly measurements. The results showed that both

the numbers of updates and images varied widely among the

youths from 2 to 13 updates and 6 to 196 images.

Data collected by youths

Temperature and humidity data varied quite widely among the

youths. Table 4 shows an example of the results for temperature

and humidity data recorded by youths on two days. The tempera-

ture data on February 13th were quite uniform, except for two

instances, while the temperature data on March 18th varied

greatly from 27 up to 35 degrees Celsius. In addition, obvious

human error, such as the temperature and humidity data of youths

ID 10 and 23, could be noted from the results.

The results of the weather observations differed even at the

same time of the same day. Table 5 shows an example of the

results of the weather observations by youths in chronological

order. The time in the table corresponds to the update time of the

data. Observation records between youth ID 28 and 3 on March

17th are within a minute, yet the records show different weather

even though the distance between each house is about 720 meters

according to the result of previous hearing survey. On the day,

Youth ID 28 recorded 31 degrees Celsius with the humidity of

Table 3 Statistical results for each youth task

Daily Task Twice Weekly Task Degital Photographs

Temperature Humidity Weather Rice Height Leaf Color No. Update No. Images

No. of Sample (Persons) 30 30 30 30 30 30 30

Mean (No. of times) 41.7 41.7 41.6 11.1 11.1 8.4 57.9

Median (No. of times) 43.5 43.5 44 11.5 11.5 9 50

Mode (No. of times) 46 46 46 12 12 10 55

Standard Deviation: U 5.7 5.7 5.7 1.4 1.4 3.3 44.9

Unbiased Estimator of Variance: U2 32.8 32.8 32.5 1.9 1.9 10.7 2012.8

Skewness –2.1 –2.1 –2.1 –0.6 –0.6 –0.4 1.6

Max (No. of times) 47 47 47 13 13 13 196

Min (No. of times) 20 20 20 8 8 2 6

Range 27 27 27 5 5 11 190

Table 4 Temperature—humidity data measured by youths

Date MeasurementYouth ID

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Feb. 13th Temperature (°C) 28 28 28 28 28 28 28 28 28 28 30 28 33 28 29 28

Humidity (%) 70 70 68 67 70 67 68 68 70 68 68 70 48 70 69 70

Mar. 18th Temperature (°C) 70 34 28 — — 30 30 — 35 27 33 30 29 72 29 28

Humidity (%) 50 60 72 — — 70 70 — 60 70 69 76 72 27 70 76

— indicates no data


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70 percent while youth ID 3 recorded 30 degrees Celsius with the

humidity of 70 percent. Additionally, when extending the time

span to 10 minutes duration, observation records of youths ID 12

and 28 on March 17th, and youth ID 11 and 28 on March 18th

are completely different, one is sunny and the other is rainy.

The result of rice height measurement records showed great

variation among the youths. Fig. 5a and 5b show rice growth sit-

uations during the project period. The rice height of the vertical

axis represents the highest leaf or ear of rice plant in a rice plant.

The numbers on the horizontal axes such as “1-1” indicates the

week number and the measurement number. For instance, “1-1”

indicates the first measurement in week 1. From Fig. 5a it can be

seen that the rice grew steadily over time. On the other hand, Fig.

5b shows a completely different result. Rice plants of youth ID 6,

12 and 15 became smaller in height. The decrease, in the case of

youth ID 15, is especially dramatic. In addition, youth ID 12 and

15 started recording the height of a rice plant which had already

grown substantially. Furthermore, deficits in the data came to the

fore.

With regard to the result of leaf color, observation records were

similar to the result of rice height measurement. The records show

the change in color and the color change indicate youths recorded

the data by using the color chart. However, results that suggest the

necessity of tutorial for proper use of color chart were obtained.

There were a total of 1737 digital photographs taken by the

youths, and they could be divided broadly into nine categories in

relation to rice cultivation. The categories are insect, leaf, paddy

field, rice ear, rice height, rice plant (the entire body imagery),

rice stem, root and weed. Subsequently, picture quality was deter-

mined. About 41 percent of the photographs (704 photographs)

were blurred. In addition, the proportion of clear photographs in

which the target could not be judged or could not be identified by

a third person due to the size of the target being too small size was

approximately 30 percent. Furthermore, there were two sizes of

photograph: 176 by 220 pixels, and 1280 by 1024 pixels. This

small size made the judgment more difficult for a third person. On

the other hand, the results affirmed the usefulness of images.

Fig. 6 shows examples of photographs taken by the youths and

Table 5 Weather observation by youths

Youth IDMarch 17th March 18th

Time Weather* Youth ID Time Weather*

Youth 5 10:05:56 2 Youth 11 11:00:15 1

Youth 8 10:08:22 3 Youth 28 11:07:18 4

Youth 30 10:15:14 2 Youth 24 11:11:30 2

Youth 4 10:32:09 3 Youth 19 11:17:56 3

Youth 11 10:34:15 1 Youth 27 11:18:21 3

Youth 12 10:50:32 1 Youth 30 11:23:49 4

Youth 28 10:58:12 4 Youth 21 11:34:10 2

Youth 3 10:58:40 2 Youth 22 11:39:28 2

Youth 24 11:00:27 4 Youth 6 11:52:43 4

Youth 27 11:16:42 2 Youth 23 12:05:49 3

Youth 21 11:39:57 2 Youth 26 12:17:02 4

Youth 1 11:41:10 2 Youth 18 13:09:15 1

* Weather data where 1: Sunny, 2: Partly Cloudy, 3: Cloudy, 4: Rainy

Fig. 5 Rice growth situation using rice height records: a) Intelligible growth situation, b) Unintelligible growth situation


72

the target of each picture could be easily recognized and catego-

rized. For instance, Fig. 6a can be recognized as eggs, Fig. 6b as

an insect larva, Fig. 6c as an infected leaf and Fig. 6d as cracks in

a paddy field.

Cultivation knowledge resources

As a result of the categorization, nine main categories related

to rice cultivation were created, together with 57 subcategories

corresponding to the main categories, and 108 sub-subcategories

according to the subcategories,.

In the creation of cultivation knowledge resources, over 1,400

resources for the youths’ use based on environmental information

and field growth situation were created. Additionally, more than

900 resources for experts’ use to provide optimal advice were

created in order to properly convey sophisticated agricultural

techniques to the youths with different language backgrounds.

Table 6 shows an example of the created cultivation knowledge

resources. In the communication between youths and agricultural

experts, youths select question from knowledge resources for

youths on the web according to the question from parents or ques-

tion based on their paddy and rice growth situation, and then send

the message with digital image if necessary to the experts. The

experts then check the measured data of the youths. After that

they create an answer and next action advice by combining the

knowledge resource for experts, and then send it back to the

youths. After that, youths check the answer and convey the

answer to parents. Parents then use the answer for decision-

making. In total, the youths and agricultural experts communi-

cated with each other 260 times using the resources.

Discussion

In this section, the youths’ capability in data collection is dis-

cussed according to the results. First, the fundamental statistics of

both the daily and twice weekly tasks suggest that youths are

capable of undertaking long-term data collection. Therefore,

using youths as sensors will contribute to meteorological obser-

vation where it is difficult to construct a weather station and

where meteorological data is not available.

Second, rice height measurement and clearly acquired images

indicate the high potential of utilizing the collected data for

proper agricultural management. For instance, Fig. 6a can be

easily recognized as the eggs of an apple snail (Pomacea

canaliculata), which is well known as a serious pest threatening

rice production. Accordingly, agricultural experts will be able to

provide proper guidelines for prevention or removal methods.

In addition, the photography task revealed that the youths under-

took three functional roles as field sensors: field monitoring,

defect detection and informing. Consequently, it is assumed that

earlier detection of disease and defects in each paddy field will be

possible.

Last, it was assumed that, as a consequence of creating cultiva-

tion knowledge resources, the youths were able to communicate

with the agricultural experts about wide-ranging topics based on

Fig. 6 Digital photographs taken by youths: a) Eggs, b) Insect larva, c) Infected leaf, d) Cracks in a paddy field

Table 6 Examples of created cultivation knowledge resources

Knowledge Resources for Experts Knowledge Resources for Youths

There are various types of insect pests damaging rice plants. A plant-hopper and a

leafhopper suck out plant juice, and pass on the virus causing a viral disease.

Additionally, locusts can be found around a paddy during the harvest season. Even if you

store rice grains after harvest, a maize weevil eats away the grains.

Is there any insect harmful for a rice plant?

Ensure fertilizer is stored in a building. Sunlight makes the fertilizer bag fragile. When

fertilizer gets wet with rain, it turns into a solid mass. Please cover the fertilizer with an

opaque sheet so as to protect it from sunlight and rain when putting it outside. Fertilizer

should not be placed directly on the ground.

How do I store fertilizer? Can I store it outside?

Please look at the shape of the reseda. Is it longitudinally diamond-shaped? If so, it

indicates rice blast.

Reseda and bistred mottles are on a rice leaf. What are they?


73

collected weather and field information.

On the other hand, several assignments have been extracted

from the results. First, the variability of the measured data and

observation records clarified the importance and necessity of

defining clear measurement rules before employing youths with-

out agricultural knowledge as field sensors so that the data and

the records can be used for later analysis.

Second, the failures in measurement, such as rice height

measurements showing a decrease in height with rice growth,

leaf color and photography failures, such as blurred photographs,

clarified that a minimum agricultural education, including proper

measurement methods and a tutorial for proper use of data col-

lecting tools, are the keys for data collection by youths as

sensors. In addition, in terms of utilizing photographs effectively

in agricultural management, having digital photographs without

recognizable targets revealed the need for metadata explaining

each picture.

Last, the feedback from the youths and their parents, such as

requests for the replenishment of resources in a specific category

and the incidence of the lack of a category, made it necessary for

them to consult with the agricultural experts. Therefore, the user’s

requests regarding the cultivation knowledge resources should be

heard and carried out in order to enrich the resources in accor-

dance with the research.

Thus, the feasibility for data collection and the efficacy for

information exchange facility of the youths as sensors were

demonstrated in terms of continuously collecting information on

the weather and field growth situations on a long-term basis. In

addition, many advantages of using the youths as sensors were

clarified, such as low cost, maintenance free, applicability and

movability to any measuring point, and the simplicity of earlier

disorder and defect detection. Among the advantages, the main

advantage would be the possibility of spontaneous improvement

in measurement accuracy and the speed of defect detection, with

an increase in both the agricultural and general knowledge of the

youths. Hereafter, the establishment of clearly defined measure-

ment rules and the development of tools for defect detection such

as silicon balls developed by Suzaki et al. (2011) are necessary to

maximize the advantages for the youths, and for the experts to

effectively utilize the collected information in agricultural deci-

sion support. In addition, the arrangement of educational pro-

grams which correspond to both agriculture and the measurement

tools, and the regular verification of data during cultivation, are

also significant future tasks.

At this moment, a system for utilizing the collected data has not

been reached, yet weather observation by many youths in areas

where there are no weather stations is significant and higher

measurement accuracy can be expected. In the near future, if

youths can act as sensors, not only will conveying information to

agricultural experts in remote locations and optimizing advice

become possible, but also the development of rice growth simula-

tion models, tailored to a target field by continual information

collection, will be possible. Accordingly, proper cultivation

management, such as fertilization based on accurate forecasts for

the sprouting season for ears of grain, can be implemented.

Moreover, the roles of youths as weather and field sensors and

the communication between youths and agricultural experts

enable sophisticated agricultural techniques to be conveyed to the

youths. In addition, the role and the communication can also

make the youths realize the importance of agriculture, and it will

be possible to foster youths as future farmers in local areas and as

future technical engineers. From farmers’ or youths’ perspective,

there are significant advantages of our proposed system. First, it

is possible to obtain optimal action advice according to a paddy

situation, growth stage and cultivar from experts. Second, if field

and weather data are collected and accumulated, the data will

become reference data for next cultivation. Last, they are able to

acquire proper knowledge, and the production of high quality rice

would be possible by implementing proper cultivation manage-

ment that includes appropriate usage of agricultural materials

such as fertilizer and agricultural chemicals, leading to the

improvement in profitability.

Conclusion

This paper devised the method of having youths working as

weather and field sensors in an area where the adult literacy rate

is low and environmental information is severely lacking, and to

regularly collect information on the environment and field growth

situations. Furthermore, utilization of collected data by agricul-

tural experts in remote locations was also devised.

The fundamental statistics for the number of determinations of

each measurement component revealed that long-term data col-

lection by youths as sensors would be highly possible. In addi-

tion, properly measured rice height records and clearly taken

pictures indicated that the collected data would be applicable to

agricultural experts providing optimal advice. In consequence of

creating cultivation knowledge resources as a contrivance to

adequately inform agricultural experts of the local situation, it

was ascertained that the youths utilized the resources and commu-

nicated with the experts many times. Thus, the feasibility of data

collection and the efficacy of information exchange facility of

youths as sensors were verified.

On the other hand, several issues to improve the functionality

of youths as sensors were also obtained. From the variability in

measured data and observation records, it was clarified that

clearly defined measurement rules are imperative before employ-

ing youths as field sensors. Additionally, the measurement and

photography failures suggested the significance of and need for

educational programs in both agriculture and the proper use of


74

measurement tools and devices. Therefore, the establishment of

clearly defined measurement rules and the arrangement of educa-

tional programs in both agriculture and measurement tools are

the next important tasks in order to improve the functionality of

youths as sensors. Additionally, the replenishment of the agri-

cultural cultivation resources, including category addition, is a

further task necessary to achieve more accurate information

dissemination.

In this research, data collected by the youths has not yet been

utilized as a system. In terms of the sophistication of agricultural

engineering guidance therefore, the utilization of field data

collected by youths is the main challenge. In the near feature, if

the development of a rice growth simulation model, tailored to a

target field by the combination of digital photographs of different

growth stages and rice height records, becomes possible, it can

be utilized in the guidance to indicate the proper time for rice ear

fertilization and harvesting. In addition, the model can also be

expected to apply the observation records of the leaf color and

occurrence of insect pest, and digital photographs showing the

infected rice plant into the cues for the proper timing of pesticide

spraying and fertilizing. From farmers’ or youths’ perspective,

there are significant advantages of our proposed system. First, it

is possible to obtain optimal action advice according to a paddy

situation, growth stage and cultivar from experts. Second, if field

and weather data are collected and accumulated, the data will

become reference data for next cultivation. Last, they are able to

acquire proper knowledge, and the production of high quality rice

would be possible by implementing proper cultivation manage-

ment that includes appropriate usage of agricultural materials

such as fertilizer and agricultural chemicals, leading to the

improvement in profitability.

Acknowledgement

This project was funded by the Ministry of Internal Affairs and

Communications as part of its emphasis on Information and Com-

munication Technology model projects in three priority areas in

developing countries (Ubiquitous Alliance Project). The authors

would like to thank Prof. Toru Ishida of Kyoto University for

advice and support.

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Received April 6, 2012

Accepted June 11, 2012

Ergonomics & Outreaches

field and weather monitoring with youths as sensors for

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