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A GIS and Remote Sensing based approach to develop cold storage infrastructure for horticultural crops: A case study for potato crop in Bardhaman district, West Bengal
Results and Discussion
- Analysis of Data for Existing Cold Storage:
A database of the information collected regarding all the
35 cold storages in the study area were analysed using Dbase. The analysis
showed that the existing cold storages have a total capacity of 281.3
thousand tonnes which is remarkably low compared to the total production of
potato (738.9 thousand tonnes) the area (Table 1). Assuming that ten per
cent of potato will be used for local consumption , there is still a storage
infrastructure deficit of 383.8 thousand tonnes. The average storage
capacity of the existing cold storages is 6.74 thousand tonne. Hence there
is a need of at least 57 new cold storages, of the average capacity, to
store the additional potato production.
- Potato Crop Map Generation
IRS WiFS data was digitally classified using a Maximum Likelihood classifier
with the help of field information. The overall classification accuracy
achieved was 92.0 per cent (Panigrahy and Chakraborty, 1998). The high
accuracy achieved with the medium resolution (188 m) data was due to the
fact that the potato in the study area is mostly grown in concentrated area,
especially near rivers. The total estimated potato acreage of the study area
was 28.7 thousand ha. A potato crop map was generated by masking all other
land cover classes. The pixels in the map were converted to points in the
Arc/Info coverage for being used as demand points in locating and allocating
cold storages.
- Buffering Analysis
Buffers
are the zones around the geographic features. The buffers were generated
around the settlements (big villages and townships) and cold storages. The
buffer radius for each cold storage has been calculated based on its
capacity. A buffer of 111 m was created for 1,000 tonne capacity of a cold
storage. This buffer size was decided by taking the Bardhmann district
average yield value of 257.06 quintals per ha. The settlement buffer was of
the radius of 500 m except for three large townships (Memari, Kalna and
Jamalpur) where it was 2.0 km. These buffers were used for marking,
interactively, a large number of probable new cold storage sites (96 in
number) as per the criteria set in the previous section.
- Location -Allocation Analysis
Minimum distance criteria was used in the location-allocation
analysis to optimally locate the new cold storage sites from the probable
sites and allocate the crop points to the cold storage locations. Since the
crop points are generally not connected by road a radial distance method has
been used. The allocation showed that 5 out 35 existing cold storage are so
injudiciously located that not a single crop point is allocated to them.
Even when the analysis was repeated for only those 35 existing locations 4
did not get any allocation. The average distance to travel from crop point
to cold storage reduced from 3.1 km to 1.6 km by incorporating the 57 new
sites (Table 2). The maximum distance of travel also decreased from 5.6 to
3.6 km. While the average load on the existing storages were 210.7 thousand
quintals it would be decreased to 79.0 thousand quintal on by incorporating
these new locations.
All the new suggested cold storages have
been classified into three groups based on the number of demands allocated
to them. The first 11 sites are of highest priority are those sites which
are catering more than 200 crop points. There is an urgent need to create
infrastructure for new cold storage in these sites. The 5 original cold
storage sites which are not getting allocated any crop site can also be
relocated to the new sites suggested.
Conclusions
The study shows that remote sensing and GIS can be used to develop a scientific approach to draw an integrated plan for cold storage, food processing, packaging sites etc. for fruit and vegetable crops.
Acknowledgement
The authors are grateful to Dr. R. R. Navalgund, Deputy Director, RESA and Shri J. S. Parihar, Group Director, ARG for constant encouragement. The help provided by Shri N. S. Mehta, Shri N.P.Bhatt, Shri Ananth Rao and Dr. Anupama Rastogi for GIS analysis and Dr. Manab Chakraborty for digital analysis is duly acknowledged.
References
Panigrahy, S. and Chakraborty, M, 1998. An integrated approach for potato
crop intensification using temporal remote sensing data. ISPRS J. of Photogramm.
& Rem. Sens. 53:54-60.
Table
1.Statistics of potato crop and cold storage in three police stations as
compared to Bardhman district.
| Parameter |
Bardhmann |
Study Area |
| Acreage (`000 ha) |
34.6 |
28.7 |
| Production (`000
t) |
886.6 |
738.9 |
| Cold Storage Number |
59 |
35 |
| Cold Storage Capacity
(`000 t) |
355.1 |
281.3 |
Table 2. Improvement achieved
in potato cold storage allocation
| Parameter |
Existing Cold storage |
Suggested Cold Storage
(Existing + New) |
| Total No. Of Cold
Storage |
35 |
92 (35+57) |
| Travel Distance
(Crop site to Cold Storage), km |
|
|
| Maximum |
5.6 |
3.6 |
| Minimum |
607 |
1172 |
| Average |
3.1 |
1.6 |
| Capacity Required
(‘000 q)* |
|
|
| Maximum |
614.0 |
367.0 |
| Minimum |
0.91 |
0.91 |
| Average |
210.7 |
79.0 |
*Average capacity
of existing cold storage is 67.4 thousand quintal
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