沙漠研究 22-1, 259 -262 (2012 )"ICAL 1 / DT X"

Journal of Arid Land Studies－Refereed Paper－

Developing an Index for Determining the Optimal Harvest Timingof Lagenaria siceraria.
Hiromichi TOYODA*1), Sawahiko SHIMADA1), Chizuru KUROSU2) and Makoto OOBA3)
Abstract: Harvest timing affects farmer’s income as well as cultivation technology. Harvest timing of the fruit crops is usually
decided by intuition and experience of farmers or other experts. However it may be difficult to determining the optimum harvest
timing for fruits with large and hard surfaces. We only can objectively confirm the fruit maturity after harvesting. Therefore, weattempted to develop more objective method for optimal harvest timing, using the measurement of spectral reflectance. We selected
fruits of bottle gourd as the target and the spectral reflectance characteristics were observed during the growth period until the day ofharvesting using spectrometer. Measuring positions were set at the fruit base, the fruit body, the fruit apex and the leaf surface. We
selected the spectral reflectance of four wavelength bands, the blue band, green band, red band, near infrared band. We analyzed thediurnal variations of four wavelength bands. As a result, in the near the harvesting stage, the value of spectral reflectance tended todecrease in at the fruit base. While, spectral reflectance value in the fruit body tend to increase.
We focused the wavelength on the difference of spectral reflectance curve in the fruit base. One is 550 nm in the green band
which shows the local peak of reflectance curve. Another is 720 nm which shows the local reflection point of reflectance curve in thenear infrared band. We proposed harvest timing index using spectral reflectance of these two wavelengths (named the base value),
after examining the correlation between the degree of fruit maturity and this index. As a result, the base value of 65 shows thethreshold value for harvest timing. Thus, we suggest the base value has a potential to determine of optimal harvest timing objectively.
Key Words: Dried gourd shavings, Fruit base value, Optimal harvest timing, Spectral reflectance, Wavelength

1. Introduction
Harvest timing affects farmer’s income as well as
cultivation technology. Harvest timing of the fruit crops isusually decided by intuition and experience of farmers or otherexperts. This is also important in arid land agriculture.
Because greenhouses have been introduced in arid area and themany fruit crops are cultivated using greenhouses, and those
have been contributed to food supply (Zhao et al., 2005).
However it may be difficult to determine the optimum harvest
timing for fruits with large and hard surfaces. The farmers
and other experts have been made much effort about judging
the optimal harvest timing (Arakawa et al., 1998).
Therefore, we attempted to develop more objective method
for optimal harvest timing, using the measurement of spectralreflectance. We selected fruits of bottle gourd (Lagenariasiceraria.) as the target. A bottle gourd fruits, which
harvested after optimal harvest timing, turn to the worthless inthe market because of those hardening.
A bottle gourd is an annual plant of the gourd family, andthe feature is that it bears big fruit (Fig. 1). The size of thefruit grows up to 35 cm - 40 cm large, 7 kg - 8 kg in weight
when it is harvested.
In Japan, bottle gourds are generally processing to dried
gourd shavings. Those fruits are shaved like slim bands andare dried using sunlight (Fig. 2). We Japanese used the dried
gourd shavings for a material of rolled sushi and miso soup.
When the bottle gourds were missed optimal harvest
timing, the fruits of bottle gourd are getting hard and thosebecome unsuitable for processing, and are abandoned without
harvesting.
Therefore, it becomes important not to miss optimal
harvest timing to hold the fruit hardness. However, it is noteasy to ascertain harvesting time and the harvest timing index
is not only with fruit size. From these view points, weFig.1. Bottle gourd fruit. Fig. 2. Processing to dried gourd shavings.

* Corresponding Author: h1toyoda@nodai.ac.jp
1-1-1 Sakuragaoka, Setagaya, Tokyo, 156-8502, Japan
1) Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
2) Japan Agricultural Cooperative Tochigi, Japan3)National Institute for Environmental Studies,Japanattempt to find the easy index of optimal harvest timing, and it
is useful for the income stability of the farmers.
In recent years, it is clarified that spectral reflectance value
is related to protein or the chlorophyll. Many studies on suchexpectation using spectral reflectance are published in the fieldof agriculture for the freshness measurement and optimal
harvest timing. It is known that an index to be called
normalized vegetation index (NDVI) reflects the activity(ability for photosynthesis) of the plant (Rouse et al., 1973).
Therefore we examined an objective index to estimate
the optimal harvest timing with non-destructiveness. And wesuggested that spectral reflectance characteristics of the fruit
surface in the growth process are useful for an index to judge
optimal harvest timing with non-destructiveness.

2. Materials and Methods
2.1 A measurement site
We measured the spectral reflectance in the bottle gourd
farm located at the north Kanto District (Kamimikawa-machi,Kawachi-gun, Tochigi, Japan), where bottle gourd cultivation
was the most prosperous in Japan. The farmlands around
Kanto area are covered by the soil with good drainage ability
and light volcanic ashes (the Kanto loam layer). Because thebottle gourd is a plant setting up a root aside, the bottle gourd iseasy to come to set a root in that soil.
2.2 Measuring positions and way of measurement
In the measurement of the spectral reflectance of the fruit,
we used a spectrometer, MS -720 (© EIKO co., ltd.) which it’sangle of view field is 10 degrees.
We measured the spectral reflectance through the fruit
growth process since bottle gourd bears fruit. And wemeasured several times for two different period of bottle gourd
fruit growth, from 14 July, 2009 to 5 August and from 6August, 2009 to 27 August.
The spectral reflectance characteristics were observed
during the growth period until the day of harvesting using
spectrometer. Measuring positions were set at the fruit base,the fruit body, the fruit apex and the leaf surface (Fig. 3).
At the same time, we measured the spectral radiance aboutstandard white board (Spectralon: Image One company) to
calculate spectral reflectance of the objects.
2.3 Objective indicesAt first, we focused NDVI (Normalized Difference
Vegetation Index) value change during a fruit growth period toclarify an index to get the optimum harvest timing. It takes
the value from -1 to +1, and NDVI is known for an index toshow the presence and the activity of vegetation, and leaf

Fig. 3. measuring positions for bottle gourd fruit.

quantity. When the vegetation activity is high, the value
shows large value.
NDVI is showed the following
expression.
NDVI = (NIR-R) / (NIR+R)
Where, NIR : Reflectance of Near Infra BandR : Reflectance of Red Band
Next, we focused fruit base value as an example of theharvest timing index. Takeuchi et al. (2007) suggested anindex for harvest timing of melons. They focused the spectralreflectance of melon fruits. When farmers harvest the melons,farmers pay their attention to the color of the base connected afruit and the stem. So, Takeuchi et al. (2007) suggest “Fruitbase value” as for an index of the harvest time judgment. As
for “Fruit base value” in case of the melon, they aim at aspectrum reflectance change during growing period inwavelength area from 670 nm to 800 nm. They suggested thefollowing expression of fruit base value.
Fruit base value = ((A-B) / (A+B)) *100
Where, A: spectrum reflectance at the wavelength, 730 nm.
B: spectrum reflectance at the wavelength, 780 nm.
We guessed the similar tendency to be in the case of thebottle gourd and applied this value, but it was inappropriate for
an index in the same expression because spectrum reflection
properties were different from a melon. So, we tried toimprove the fruit base value for the bottle gourd harvestingtime.

3. Results and Discussion
3.1 Observation results on the spectral reflectance
We get the observation result (in the first harvest period) of
the spectral reflectance at the leaf, the fruit apex, the fruit baseand the fruit body of the bottle gourd. The daily variations of
the value at the fruit base during the growth period showed adifferent tendency from that of the fruit body (Figs. 4 and 5).
On the other hand, such tendency cannot see at the leaf andfruit apex, we can see only fluctuation (Fig. 6).
Therefore, we focused the fruit base and the fruit body andexamine spectral reflectance characteristics and relations of theoptimal harvest timing.
We selected the spectral reflectance of four wavelength
bands, the blue band (470 nm ~ 501 nm), green band (539 nm

14 Jul

706050403016 Jul23 Jul05 Aug

20100400500

600

700800Wavelength (nm)Fig. 4. A variation of spectral reflectance at the fruit base of thebottle gourd.

Spectral Reflectance (%)

Spectral Reflectance (%)

80

7/11/ 7/16/ 7/21/ 7/26/ 7/31/ 8/5/0 8/10/0909
09
09
09
909

Fig. 7. A variation of spectral reflectance on four wavelength bands
at fruit base.

23 Jul05 Aug

Fig. 5. A variation of spectral reflectance at the fruit body of thebottle gourd.

Spectral Reflectance (%)

14 Jul16 Jul10080

bluegreen
redNIR

60
40200
7/11/ 7/16/ 7/21/ 7/26/ 7/31/ 8/5/0 8/10/09
09
09
09
09
909

Fig. 8. A variation of spectral reflectance on four wavelength bands
at the fruit body.
0.9

16 Jul

0.8

23 Jul

0.7

NDVI

14 Jul

05 Augbluegreen
redNIR

80
70
60
50
4030
20
1000.6
0.5

Fruit Base
Fruit Body

0.4
0.3
7/11/09 7/16/09 7/21/09 7/26/09 7/31/09

8/5/098/10/09

Fig. 6. A variation of spectral reflectance at the leaf of the bottle gourd.

Fig. 9. NDVI value change at the fruit base and fruit body of thebottle gourd.

~ 580 nm), red band (637 nm ~ 680 nm), and near infrared
band (801 nm ~ 870 nm).
We analyzed the diurnal variations of four wavelength
bands. As a result, in the near the harvesting stage, the valueof spectral reflectance tended to decrease at the fruit base (Fig.
7). While, spectral reflectance value at the fruit body tend toincrease (Fig. 8). The ratio of the increase and decrease areparticularly large in a near-infrared band.

other hand, NDVI value at the fruit body showed and it
decreased gently from 0.82 on July 14 to 0.73 on August 5.

3.2 The variation of NDVI value during growing period
The NDVI value at the fruit base and the fruit body in thefruit growing period (from July 14 to August 5) are shown
Figure 9. The value at the fruit base was 0.51 on July 14
when our measurement started, and the value become to 0.78
by harvesting date (August 5). The NDVI value at the fruit
base tended to increase near the harvesting stage. On the3.3 Estimating by optimal harvest timing using improved
fruit base value
We focused the wavelength which showed a great changeof spectral reflectance at the fruit base. One is 550 nm in thegreen band which showed the local peak on reflectance curve.
Another is 720 nm which shows the local reflection point ofreflectance curve in the near infrared band. We proposed
harvest timing index using spectral reflectance of these twowavelengths (improved fruit base value).
We suggest to improve the fruit base value for a bottlegourd and to calculate by the following formula.
Improved fruit base value = {((1+A)) -B)/((1+A)+B) }*100

4. Conclusion

Fruit Base Value

7060504030
7/11/0 7/16/0 7/21/0 7/26/0 7/31/0 8/5/09 8/10/0
999999Date

Fig. 10. The variation of fruit base values.
90

ＮＤＶＩ*100 and Base Value

80706050

ＮＤＶＩ*100 atfruit base
Fruit BaseValue

40
30
31-Jul5-Aug

10-Aug 15-Aug 20-Aug 25-Aug 30-Aug

Fig. 11. A variation of NDVI at fruit base and Fruit base value in thesecond harvesting period.

Where, A：Spectral reflectance at the wavelength 550nm
B：Spectral reflectance at the wavelength 720nm
The improved fruit base value tended to increase near theharvesting stage (Fig. 10). The value was 43.8 on July 14,
and it became to 66.8 by harvesting date (August 5). In
addition, a coefficient of correlation is very high between
NDVI value at the fruit base and improved fruit base value.
By the farmer’s judgment, our observed fruit was harvested
on August 5. That harvested fruit was matured and good forthe processing material. Then the improved fruit base value
in the harvested date was 66.8. From this result, when thebase value is around 65, we can guess that fruit get to beoptimal harvest timing. Thus, we suggest the base value has
a potential to determine of optimal harvest timing objectively.
3.4 The relation between NDVI and fruit base value
The spectral reflectance of the other bottle gourd fruit wasobserved in the second harvest period. We have been got thesimilar tendency with the results of the first harvest period.
While this time, we continued the observation over the optimal
harvest timing.
The fruit base value tend to increase linearly, from 36.8 to81.8. While NDVI value tend to increase linearly at first, thevalue have a peak near the harvest timing. After getting peakvalue, it tend to decrease (Fig. 11). When NDVI value
becomesto peak value, the fruit base value is around 65. From
this result, we can guess the optimal harvest timing is on 25 Aug.

According to the observation results in the growth processof the bottle gourd, we intended to make clear the optimal
harvest timing of bottle gourd in non-destructiveness using
spectrum reflectance characteristics.
The improved fruit base value tended to increase near the
harvesting stage. When NDVI at the fruit base reached to thepeak value, the improved fruit base value is regarded as
optimal harvest timing around 65. We suggest that the basevalue has a potential to determine of optimal harvest timing
objectively.
Also we need to discuss the relation between the spectralreflectance and the maturity in future. Next step, we must
examine the correlation between the degree of fruit maturity
and this index. For example, we must know about thehardness of the bottle gourd fruit objectively.
Now a spectrometer is expensive. However, we expect that
this method contributes the efficiency of the future agricultural
production and grown up for farmers income.

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