Ehime University Institutional Repository

太田, 響子

OHTA, Kyoko

Japanese

防災行政における都道府県出先機関の役割をめぐる論点

鈴木, 靜

SUZUKI, Shizuka

青木, 理奈

AOKI, Rina

福井, 秀樹

FUKUI, Hideki

小佐井, 良太

KOSAI, Ryota

石坂, 晋哉

ISHIZUKA, Shinya

池, 貞姫

CHI, Jong Hi

十河, 宏行

SOGO, Hiroyuki

中川, 未来

NAKAGAWA, Mirai

吉椿雅道講演「コロナ禍と学生ボランティア　─ トルコ・シリア地震の被災地の現状と若者」

Ehime University (愛媛大学)博士(学術)thesi

Naraporn, Phomkaivon

（第３号様式）(Form No. 3) 
学  位  論  文  要  旨  
Dissertation Abstract 
 
 
氏名：  
Name 
Naraporn Phomkaivon 
 
学位論文題目：  
Title of Dissertation 
New proces s ing  t echno logi es  for  t he  enhancement  o f  
an t i ox idant  and  an t i a l le rg i c  ac t i v i t i e s  of  Thai  and  
Japanese  sweet  pot a toes  
(タイ産及び日本産さつま芋の抗酸化活性並びに抗アレ
ルギー活性の増加を促す新加工技術 )  
 
学位論文要旨：  
Dissertation Abstract 
 
 
 
 
 
 Phytochemicals in sweet potatoes varied on the color of flesh. The processing of 
colored sweet potatoes may affect the phytochemicals and their antioxidant activity. In 
this study, the effect of pre-gelatinization of colored sweet potato powders on 
extractable polyphenols and antioxidant activity was investigated. Pre-gelatinized 
double drum-dried powders prepared with Torperk and Purple, purple-fleshed cultivars, 
were superior to the conventional hot air-dried powder in terms of total phenolic content  
and total anthocyanin content. Formation of TBA reactive substances (4.4 nM MDA/mg 
linoleic acid) and DPPH free radical (SC50 72.1 µg/mL) were significantly lower in 
Torperk cultivars after pre-gelatinization. In consequence, pre-gelatinized powders of 
individual sweet potato cultivars showed higher extractable polyphenol content , 
including anthocyanins, and greater antioxidant activity than conventional powders, 
probably due to the destruction of cell matrix during the pre-gelatinization process. 
Moreover, the antioxidant activity (TBA value) of pre-gelatinized Torperk was 
statistically correlated to concentration of chlorogenic acid (peak 1) (r = 0.93 with p < 
0.05) and an acylated anthocyanin (peak 3) (r = 0.98 with p < 0.01). The releasing of the 
potent antioxidant substances of colored sweet potatoes during pre-gelatinization 
indicate the potential for promoting health and commercial application in food industry, 
health food market, natural food colorants, and nutraceuticals. This kind of information 
is useful for selection the thermal processing that suited for biological activity 
enhancement of target compounds in sweet potatoes. 
 In the following study, the importance of cooking technique in daily life was 
studied on antiallergic activity of Naruto Kintoki variety among sweet potatoes. The 
antiallergic activity of extracts of Naruto Kintoki sweet potato peel was enhanced after 
cooking the peel using three conventional methods. At 400 µg/mL extracts, baking at 
200°C for 12 min showed the highest suppression of β-hexosaminidase release of 36.9%, 
（第３号様式）(Form No. 3) 
followed by microwaving at 500 W for 6 min (41.9%) and boiling at 100°C for 15 min 
(64.2%). Based on 7 extracts of Naruto Kintoki from liquid-liquid partition technique, 
significant suppression of β-hexosaminidase release from RBL-2H3 cells of Naruto 
Kintoki peel was attributed to compounds 9 (r = 0.91 with p < 0.01) and 11 (r = 0.76 
with p < 0.05). It was noticed that baking and microwaving can enhanced compounds 5, 
8, 9, and 11 of Naruto Kintoki compare with those of raw one. UPLC/ESI-Q-TOF-MS 
analyses of compounds 5, 8, 9, and 11 clarified the existence of  two sulfates of flavonol 
aglycons (3, 5, 3′-trihydroxy-7, 4′-dimethoxyflavone 3-O-sulfate and 3, 5-dihydroxy-7, 
4′-dimethoxyflavone 3-O-sulfate). Baking the sweet potato peel changed compounds 5 
and 8 to compounds 9 and 11 with enhanced antiallergic activity: IC50 changed from 
11.0 µg/mL (5) to 4.1 µg/mL (9) and from 12.1 µg/mL (8) to 4.4 µg/mL (11). The results 
indicated those four chemicals contributed to the antiallergic activity. Cooked Naruto 
Kintoki peels are the excellent source of flavonols and flavonol sulfates for the 
suppression of allergy Type I. Moreover, this is a first to quantify two flavonol sulfates 
in raw and cooked Naruto Kintoki peel as the potent antiallergic substances.  
This study provides the information of phytochemicals, antioxidant substances and 
antiallergic substances, in sweet potatoes and their biological activity enhancement 
using thermal processing technologies. Increasing in amount of acylated anthocyanin led 
to a strong antioxidant activity in pre-gelatinized Torperk. Moreover, conversion of 
flavonol suflates to flavonol aglycon led to a great antiallergic activity in cooked Naruto 
Kintoki peels. The results proposed technique could be served as the useful tool for 
further development of antioxidants, antiallergic substances or nutraceuticals from 
sweet potatoes.  
 
 
 
 
 
 
 
 
 


English

New processing technologies for the enhancement of antioxidant and antiallergic activities of Thai and Japanese sweet potatoes

Ehime University (愛媛大学)博士(医学)doctoral thesi

菊池, 明日香

KIKUCHI, Asuka

高尿酸血症は男性および女性の全死因死亡率と関連する:日本の地域在住者を対象とした調査から

Ehime University (愛媛大学)博士(農学)thesi

Fadli, Irsyad

1476

（様式５）(Style5) 
学位論文全文に代わる要約 
Extended Summary in Lieu of Dissertation 
 
 
氏名： 
Name 
Fadli Irsyad 
 
学位論文題目： 
Title of Dissertation 
Developing irrigation management system in the dry season for rice cultivation by 
utilizing remote sensing data 
(リモートセンシング・データを利用した乾季の水田における灌漑管理に関
する研究) 
 
 
学位論文要約： 
Dissertation Summary 
 
Local climate change cause uncertainty in water availability for agriculture. Changes in the local climate 
affect rainfall patterns and caused the shifting in the dry seasons, which forces farmers to shift the period of rice 
cultivation in the dry season. In most irrigated agricultural areas in Indonesia, rice is the main crop in the rainy 
season. Hence, rice production in the dry season generally decreases due to insufficient water availability, 
inappropriate planting schedule, and changes in cropping patterns. Various studies have discussed the onset and 
end of the dry season and even the rainy season for agricultural management. Thus, the dry season parameters 
(onset, end, and duration) are essential for irrigation management in rice cultivation.  
Understanding how the dry season has changed in the past and how it will change in the future becomes 
an important issue for irrigation management and food security. In addition, monitoring rice production is an 
important aspect of maintaining regional food security to ensure the stability of the food supply, especially in the 
dry season. There are three rice planting seasons in Indonesia, namely, the wet season planting (1st planting 
season), followed first dry season planting (2nd planting season), and the second dry season planting (3rd 
planting season/crops season) 
The utilization of remote sensing data can be one solution in monitoring rice cultivation and its production 
in a large-scale area during the dry season. On the other hand, remote sensing-based methods have been proven 
by several researchers as an effective alternative to estimating the rice field area and predicting its production. 
Therefore, the objectives of this study were: (1)  to determine the dry season's onset, end and duration, and 
predicted ones for the near future; (2) to develop a monitoring system for rice production in the dry season by 
utilizing Landsat 8 Operational Land Imager (OLI), with the impact of the dry season parameters on rice 
production; and (3) to develop a monitoring system for the response of rice plant canopy to soil water and 
meteorological conditions using the aerial photograph. To achieve the first and second objectives, this research 
（様式５）(Style5) 
was conducted in Agam Regency, West Sumatra, Indonesia. Agam District is the largest irrigation area in West 
Sumatra Province, Indonesia with around 24,266 ha. The district covers 2,232.30 km² at altitudes 0 to 2891 m 
above sea level. Agam District is an agricultural zone with a total irrigated rice field area of 24,266 ha.  
This study proposed a new approach to determine the dry season parameters by using annual cumulative 
rainfall for the past 35 years (1985 – 2019) in Agam District, West Sumatra, Indonesia.  Daily rainfall 
measurements from 1985 to 2019 were obtained from 5 stations. Two rain gauge stations are located in Agam 
District (Canduang and Gumarang) and additional stations (Padang Panjang, Suliki, and Paraman Talang) are 
outside but close to this district. Missing rainfall data were predicted using the inverse distance weighting (IDW) 
method. 
The 5th degree polynomial equation (quintic function) provides the highest correlation with cumulative 
rainfall data compared with other equations (5th polynomial: R2 = 0.9961, 3rd polynomial: R2 = 0.9942, 
logarithmic: R2 = 0.7347, and exponential: R2 = 0.9333). The example of quintic function fitted with cumulative 
rainfall at Candung station in 2019. In this study, the slope of cumulative rainfall for a year is presented as Grain, 
which is the threshold for determining the dry season parameters. The minimum Grain was set as 5.0 mm d−1 by 
assuming the minimum monthly rainfall for rainfed rice would be 150 mm month−1. The first derivative of the 
cumulative rainfall function in describes the rate of change in cumulative rainfall, i.e., rainfall rate in the year. The 
onset of the dry season occurs when the rainfall rate decreases below the slope of cumulative rainfall (F'(x) ≤ 
Grain). The minimum rainfall rate in the dry season can be obtained by finding the roots of F'(x) or F"(x) = 0. 
Moreover, the rainfall rate (F'(x)) would increase gradually to the end of the dry season (F'(x) ≥ Grain), as shown in 
Fig. 2. 
After determining the onset and end of the dry season in Agam District for the past 35 years, the yearly 
trends of the dry season parameters for each station were determined by using the nonparametric Mann-Kendall 
test and Sen’s slope estimator. The dry season trends and predictions were analyzed individually to see the 
response at each station to local climate change, which could affect the rainfall pattern and distribution in the 
future. Further, the parameters for future dry seasons were predicted using the autoregressive integrated moving 
average (ARIMA) model for the next five years (2020 – 2025). The predicted DOY of the onset and end of the 
dry season is a product of several past observations and random errors, which is useful for forecasting future dry 
seasons. The applicability of the ARIMA model was evaluated using the Nash-Sutcliffe efficiency (NSE) which 
compares the average of the actual dry season parameters and the parameters predicted by ARIMA in Agam 
District from 2010 to 2019. 
（様式５）(Style5) 
 
 
Fig. 1 A quintic function fitted to daily rainfall 
and cumulative rainfall at Candung station in 2019. 
 
 
Fig. 2  The first derivative of cumulative rainfall 
(solid black line) F'(x) using Eq. (2-3) and the 
determined dry season period using F'(x) and Grain at 
Candung station in 2019. 
This study also examined the impact of the dry season on rice production using the Normalized Difference 
Vegetation Index (NDVI) of Landsat 8 Operational Land Imager (OLI) in Ampek Angkek sub-district, West 
Sumatra, Indonesia. Landsat-8 images were downloaded through USGS (United State Geological Survey) 
website with Landsat Collection 2 Level-1 (Lv1) and Level-2 (Lv2) products from 2017 to 2021 during the dry 
season.  
Landsat 8 Lv1 was calibrated by the top of atmosphere (TOA) reflectance for targeted bands (i.e., bands 4 
and 5). NDVI of Landsat-8 OLI level 1 with TOA reflectance and level 2 with surface reflectance was calculated 
on a composite image. A supervised classification method was applied to detect rice cultivation during the dry 
season from Landsat 8 OLI imageries. The reference of NDVI images was carried out by unmanned aerial 
vehicle (UAV) DJI Mavic Pro2, which is equipped with a multispectral camera (Yubaflex, 
http://www.bizworks.co.jp/YF/Spec.htm). The ground check was carried out to verify the NDVI values (from 
Landsat 8) that met each rice cultivation stage. NDVI analyses focused on the rice field in this sub-district 
downloaded from Geospatial Information Agency (BIG). 
In this study, NDVI values (from UAV) were categorized into five rice field classifications, namely RF1 
(for the rice field with land preparation and after transplanting), RF2 (rice cultivation between 40 days after 
transplanting (DAT) and 80 DAT), RF3 (rice cultivation after 80 DAT), RF4 (for the rice field with harvest and 
after harvest), and RF5 (crops cultivated in the rice fields). This study observed 217 ground checkpoints to 
classify the five rice field classifications in this sub-district. This study used the most popular yield estimation 
method, a regression model between NDVI images and the observed yield (field observation) focused on RF2 
（様式５）(Style5) 
and RF3.  
Field observation was conducted on 26 points of the rice fields that were cultivated during the dry season 
from September to October 2020. The measurement in the field observation consists of transplanting date and 
rice yield (ton ha-1). In addition, the rice yield data from 2017 to 2021 was also collected from the Agricultural 
Department of Agam district. The dry season condition could affect rice production due to the amount of rainfall, 
the onset, and duration of the dry season. Pearson correlation analysis was performed to determine the 
relationship between dry season parameters (i.e., the amount of rainfall, the onset, the end, and the duration) and 
rice yield in this sub-district.  
On the other hand, to achieve the third objective, this study was conducted in the rice field of Ehime 
University Senior High School, Matsuyama, Japan. Monitoring the response of rice plant canopy in terms of 
canopy temperature and NDVI to soil water and meteorological conditions using the aerial photograph. Thermal 
infrared (TIR) and NDVI imageries obtained by unmanned aerial vehicles (UAVs) may provide a means for 
determining canopies' temperature and plant conditions in the rice field. This study focused on the heading and 
flowering stage from July 31 (67 DAT) to August 10 (77 DAT), 2020. Even in one rice field, soil and water 
conditions were not the same in the whole field. This study's target points were in the middle and the edge of the 
rice fields to detect the difference in response between the two points. 
The aerial photographs (i.e., NDVI and thermal) were taken every day during the heading (July 31-August 
4) and the flowering stage (August 4-August 10) between 10:00 am and 11:30 am under clear sky conditions. 
The flight altitude was 20 m above ground level. DJI Go 4 and FreeFlight Thermal Applications were employed 
for UAV controlling and image acquiring. The targeted points in this study were in the middle and the edge of the 
rice field to detect the differences in response between the two points. 
The result of this study showed that the 5th degree polynomial equation (quintic function) successfully 
correlated with the cumulative rainfall at the five stations (Candung, R2= 0.9973; Gumarang, R2= 0.9983; Padang 
Panjang, R2= 0.9984; Suliki, R2= 0.9966; and Paraman Talang, R2= 0.9981). The dry season in Agam District 
started on April 28 (119 DOY) and ended on September 17 (261 DOY) with a duration of 142 days.  
The averages of the onset and end of the dry season at the five stations showed positive trends, which were 
determined by using the Mann-Kendall test and Sen’s slope estimator, with probabilities of 78.83 and 84.42%, 
respectively. The duration of the dry season would become longer, with a probability of 67.54%. The ARIMA 
model for predicting the onset and end of the dry season showed good performance (Nash-Sutcliffe efficiency 
(NSE); NSE = 0.747) and very good performance (NSE = 0.769), respectively. The predicted dry season period 
（様式５）(Style5) 
in the next 5 years (2020 – 2025) would start between April 29 and May 5, and end between September 19 and 
October 4. 
The impact of the dry season on rice production was successfully detected in Ampek Angkek sub-district 
using the NDVI from Landsat 8 Level 2. NDVI of Landsat 8 Lv2 had a good correlation with NDVI from the 
unmanned aerial vehicle (UAV) (R2 = 0.682). The rice cultivation area in this sub-district in the dry season was 
successfully detected by NDVI from Landsat 8 OLI Lv2. This study successfully predicted rice production in the 
dry season by a linear function of NDVI from Landsat 8 Lv2 (y = 18.62970 x NDVI - 7.969) with a significant 
correlation (R2= 0.665). By using the model found in this study, Ampek Angkek sub-district would produce 
4038.9 tons of rice (yearly average) in the dry season from 1012.8 ha of the predicted rice field area.  
This study successfully predicted rice production in the dry season by a linear function of NDVI of 
Landsat 8 Lv2 with a significant correlation (R2 = 0.665). The total rainfall during the dry season showed a high 
correlation with rice production (R2 = 0.960). In addition, the amount of rainfall in the dry season positively 
correlated with rice production, which is identified in Pearson's correlation of 0.981 (p-value = 0.003). 
Meanwhile, the onset, end, and duration have no significant correlation with predicted rice production, with 
Pearson's correlation of 0.219, -0.425, and -0.402, respectively. In addition, this study could explain that the 
amount of rainfall and the dry season parameters (i.e., the onset, the end, and the duration) had an impact on the 
predicted rice production in Ampek Angkek sub-district. 
Irrigation water influences the canopy temperature and plant conditions in the rice field, which were 
clearly detected by the camera of UAVs. The NDVI camera value was lower than the actual ones (NDVI sensor), 
with a correlation coefficient of 0.63 (Fig. 3(a)). Meanwhile, thermal imagery by UAVs successfully detected the 
canopy temperature in the rice field, which hand-held TIR FLIR i5 was measured with a correlation coefficient of 
0.83 (Fig. 3(b)). In addition, NDVI values from UAV camera correlated successfully with the Soil Plant Analysis 
Development (SPAD) chlorophyll meter at the same point (R2 = 0.96), as shown in Fig. 4. 
The irrigation water decreased the temperature of the soil surface, and it affected the observed canopy 
temperature. The soil surface temperature decreased during the irrigation process and reduced the rice canopy's 
temperature, as shown in Fig. 4-8. A thermal camera precisely represented the canopy temperature across the rice 
field. It detected that the edge of the rice field was higher than the middle ones, with an average differencing of 
0.63 oC. Before irrigation water started, soil surface temperature was more influenced by the air temperature. 
Irrigation water decreased the soil water temperature, and it would affect the canopy temperature. The canopy 
temperature would decrease when the vapor pressure deficit increases for both sides. Rice canopy structure with 
（様式５）(Style5) 
chlorophyll and water content decreased the air temperature and made the soil surface cooler. Moreover, in the 
middle of rice fields with high soil water content, it can maintain rising temperature and reduce soil water content 
for plants and their surrounding area. 
 
Fig. 3   Relationships between the camera and sensor measurement (a) NDVI and (b) canopy temperature. 
 
Fig. 4.   Relationships between NDVI and SPAD value (a) Flag and (b) 2nd Leaves. 
Furthermore, this study can be a valuable reference for the government, stakeholders, and decision-makers 
in formulating policies regarding preventing rice scarcity in the dry season.  In Agam district, the onset and end 
of the dry season were predicted to be delayed around 4 and 9 days, respectively, for the next five years. The 
available water was mostly surplus in the rainy season (Jan-Mar and Oct-Dec) and dry season (Apr-Sep) with an 
average of 114 mm month-1 and 25 mm month-1, respectively. However, the available water decreased during 
the dry season and reached a deficit from May until July.  
This study suggested that water users' association and relevant departments of local 
（様式５）(Style5) 
government should prepare some countermeasures in irrigation management that can anticipate the 
water shortages problems during the dry season, as follows: (i) to reassess the distribution of 
agricultural water and the schedule for water use, (ii) to postpone the transplanting time to the first 
week of July in future dry seasons, (iii) to prepare additional irrigation water from a river, a small 
reservoir and artificial wells, (iv) to minimize water loss from the irrigation system, and (v) to strive 
for the application of water harvesting in the dry season. The new approach presented in this study 
would be applicable for predicting the dry season parameters for irrigation management in a region 
with dry and rainy seasons. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
(注) 要約の文量は，学位論文の文量の約１０分の１として下さい。図表や写真を含めても構いません。
(Note)  The Summary should be about 10％ of the entire dissertation and may include illustrations 


Developing irrigation management system in the dry season for rice cultivation by utilizing remote sensing data

諸田, 龍美

「山の詩人」白居易〔二〕─仙遊山・「長恨歌」・山水画家─

尾花, 忠夫

村田, 潔

折戸, 洋子

崔, 英靖

法テラス愛媛 岩谷健作弁護士講演録「SNS と法律問題」

若林, 良和

鹿児島県奄美大島北部におけるカツオの産業と文化 -「ぎょしょく」をもとにした地域モノグラフ(7)-

高橋, 敏明

佐野, 健斗

コロナ禍における大学生の肩こり・腰痛に対する実態調査

高橋, 勇介

Policy Significance of Education and Training Benefits in Japan's Employment Insurance System

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