Technical Progress Report
Foodnet Project G.10
1. IntroductionThe general goal of the project is to investigate a viable business or market driven interventional strategy to enhance Irish potato production in Kenya and East Africa. Irish potatoes are second to maize in Kenya as energy food and are potentially viable Food commodities for alleviation of chronic food insecurity, associated with frequent maize crop failure due to the frequent drought conditions. The project seeks to investigate the viability of the establishment and operation of a National Potatoes storage structure similar to the National Cereals and Produce Board, but operated commercially with similar operational objectives, namely
a. Element of strategic reserve and
b. Prices stabilization for the benefit of producers, (mainly in order to increase production) but also consumers for purposes of improving consumption as an alternative to the staple maize.
The project's deliverables are:
a. Market research studies on potatoes
b. Pilot plant investigations on the storage and utilization quality behavior of the popular local potato varieties and
c. The economic viability analysis of establishment and operation of large-scale potato storage facilities operated under the prevailing conditions.
The market research studies are meant to illuminate the market conditions influencing Irish potatoes, and particularly determine factors that fuel price fluctuations, the role of potatoes storage and its potential as an interventional strategy in stabilizing prices, given the prevailing market dynamics. The studies on the potato cultivars are meant to examine the storability of the available popular varieties, with reference to delaying setting or elimination of spoilage characteristics for purposes of reducing wastage on storage, and conserving the utilization qualities.
The economic analysis of commercial potato storage is expected to provide data to enable develop a feasibility report on the viability of large-scale commercial potatoes storages, given the expected investment, operational costs, and different prices offered to producers for potatoes that should provide farmers with sufficient incentives to produce more potatoes.
2. The Study Design and Methodology
2.1 Market Studies On Potatoes
The activities here involved:
a. Extensive literature review meant to retrieve secondary data on national Irish Potato production, prices fluctuation and contributing factors. Data on other constraining factors to production of Irish potatoes were also examined.
2.2 Storage Behaviour and Utilisation
Tana, Nyayo and Tigoni Chips
Kerrs Pink (Meru) Stew and mashing
Each variety was washed to remove soil dirt, dipped in 50 to 60 per cent ethanol solution to dry them or harden or make the skin firm, dusted with Propham, a germination suppressant and packed in small wooden crates. About 50kg were put in each crate for each variety and put in different environmentally controlled cabinets. The storage conditions set for all the five cabinets are as follows:
The quality parameters that were monitored with time are:
a. Deteriorative.
b. Utilisation Quality
· Crisps—Brown colour development on deep-frying in oil
---Sugars (sweetness development)
---Taste (Bitterness development)
· Chips—Colour development
---Sugars
---Oil absorption (sogginess).
· Stew/mashing—Flouriness check and development of translucence (mashing)
----Taste in comparison to the fresh control.
Annexure II shows the experimental design for the storage study
2.3 Economic Viability of Potato Storage
Data gathering towards the goal under this output has been initiated with the largest potato Storage Company in Holland, namely Netagco Tolsma B.V, which has branches in Germany, France and Russia. A questionnaire of Netagco Tolsma B.V, annexure III, indicates the basis and type of data being exchanged to facilitate compilation of relevant technical and financial data for the feasibility study.
The data obtained so far from outputs 1& 2 are proving invaluable in synthesising the necessary information for the questionnaire. Data derived from this questionnaire, plus supplementary data to be derived from a visit to the Netagco potato storage facility and subsequent assessment of investment costs related to buildings and other fixed costs will assist in putting together the necessary economic statistics appropriate to our local situation, for the purpose of viability analysis for a commercially operated potato storage in Kenya.
3.0 Results
3.1 Potatoes Market Structure in Kenya
Table I shows production statistics for potatoes in five provinces in Kenya for the years 1997 to 2000. Central province leads both in hacterage and tonnage production accounting for 40-60%of the total national potato production. Over the four years central province produced an average of 412,700 metric tonnes per year from an average of 57,650 hectares. Rift Valley followed this with an annual average production of 228230 metric tonnes from 27,138 hectares, and Eastern province, producing annual average of 160,725 metric tonnes from 22315 hectares. In total annual potato production in Kenya ranged from 670,000 metric tonnes in 1998 and 2000 to 1,050,000 metric tonnes in 1999. Such drastic fluctuations in production can be explained by the rainfall precipitation pattern, which has been erratic, with intervening dry spells. Fluctuations in yields are also weather or rainfall dependent. In general, rainfall has been higher in the Western Kenya, and that explains why yields are on average higher in Western and Riftvalley provinces. However, production in RiftValley, Western and Nyanza provinces has remained depressed in both cultivated area and potato production despite the relatively better weather conditions. Such discrepancy can be attributed to the market. The major market for potatoes is in large urban areas such as Nairobi, Mombasa and Nakuru. Accordingly, Central and Eastern provinces benefit from being near these markets, given the high transport costs involved in transporting bulky and high moisture commodities such as potatoes.
Tables 2 a, b, c and d show the detailed potatoes production statistics for the years 1997, 1998, 1999 and 2000 respectively by districts in the provinces of Kenya, in acreage and tonnage, according to long and short rain seasons of their production.
Tables 3 a, b, c, d and e present the recorded monthly prices for red and white potato varieties for the years 1995 to 2000. Previous similar studies on potato prices by Durr and Lorenzl in 1980 lumped together potato varieties on the basis of whether red or white and found a very significant difference in prices between red or white varieties based on colour grouping. Figures1 a and b present the yearly price and production averages for the five most productive districts in potatoes in a graphic form for the period 1995-2000.
Table 1: Total Annual Potato Production and Yields In Hacterage and Metric Tonnes;
1997-2000
Province 1997 1998 1999 2000
Ha MT Ha MT Ha MT Ha MT
Central 76,283 501,454(7) 52,335 395,948(7.5) 53,325 475,722(9) 48,670 277,729(5.7)
Coast 25 250(10) -- -- 15 154(10) -- --
Eastern 20,172 125,762(6) 14,064 69,298(5) 32,718 314,403(9.5) 22,310 133,440(6)
R. Valley 21,666 203,177(9) 22,851 204,730(9) 27,591 251,904(9) 36,442 253,118(7)
Western 450 4,565(10) 362 3,609(10) 468 5,075(11) 609 5,704(9.5)
Total 118,596 835,208(7) 89,612 673,58(7.5) 114,117 1,047,260(9) 108,031 669,991(6)
Ha=Hectares MT=Metric tonnes Figures in brackets = Yield per hectare
Table 2a Irish Potatoes 1997
Annual Production
Central
|
District |
Ha |
Tons/ha |
Tons |
|
Kirinyaga |
21,500 |
0.45 |
9,750 |
|
Muranga |
2,380 |
4 |
10,210 |
|
Nyeri |
16,450 |
5 |
83,850 |
|
Kiambu |
10,834 |
9 |
94,364 |
|
Thika |
5,480 |
5 |
24,934 |
|
Nyandarua |
15,139 |
17 |
263,721 |
|
Maragua |
4,500 |
3 |
14,625 |
|
Total |
76,283 |
7 |
501,454 |
Coast
|
District |
Ha |
Tons/ha |
Tons |
|
T/Taveta |
25 |
0.45 |
9,750 |
|
Total |
25 |
4 |
10,210 |
Eastern
|
District |
Ha |
Tons/ha |
Tons |
|
Embu |
1,750 |
10 |
17,100 |
|
Machakos |
380 |
0 |
85 |
|
Mbeere |
37 |
3 |
121 |
|
Meru |
16,225 |
6 |
97,350 |
|
Nyambene |
1,360 |
8 |
10,880 |
|
T/Nithi |
420 |
1 |
226 |
|
Total |
20,172 |
6 |
125,762 |
Rift Valley
|
District |
Ha |
Tons/ha |
Tons |
|
Baringo |
54 |
11 |
602 |
|
Bomet |
291 |
12 |
3,492 |
|
Kajiado |
1,068 |
1 |
961 |
|
Keiyo |
400 |
9 |
3,400 |
|
Kericho |
850 |
10 |
8,500 |
|
Koibatek |
842 |
12 |
10,104 |
|
Laikipia |
3,236 |
9 |
29,124 |
|
Marakwet |
1,800 |
9 |
16,200 |
|
Nakuru |
7,843 |
8 |
62,117 |
|
Nandi |
325 |
18 |
630 |
|
Narok |
3,000 |
14 |
40,500 |
|
Samburu |
8 |
5 |
40 |
|
TransMara |
104 |
14 |
1,497 |
|
Trans Nzoia |
460 |
9 |
4,140 |
|
Uasin Gishu |
1,180 |
14 |
15,930 |
|
West Pokot |
495 |
12 |
5,940 |
|
Total |
21,666 |
9 |
203,177 |
Western
|
District |
Ha |
Tons/ha |
Tons |
|
Kakamega |
35 |
9 |
315 |
|
M-Lugari |
64 |
12 |
768 |
|
Mt. Elgon |
337 |
10 |
3,370 |
|
Vihiga |
14 |
8 |
112 |
|
Total |
450 |
10 |
4,565 |
Summary
|
Province |
Ha |
Tons/ha |
Tons |
|
Central |
76,283 |
7 |
501,454 |
|
Coast |
25 |
10 |
250 |
|
Eastern |
20,172 |
6 |
125,762 |
|
Rift Valley |
21,666 |
9 |
203,177 |
|
Western |
450 |
10 |
4,565 |
|
Total |
118,596 |
7 |
835,208 |
Table 2b Irish Potatoes 1998
Central
|
Long rains |
Short rains |
total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Kirinyaga |
741 |
5,705 |
975 |
1,072 |
1,716 |
6,777 |
|
Muranga |
400 |
1,100 |
400 |
880 |
800 |
1,980 |
|
Nyeri |
7,235 |
71,626 |
8,880 |
48,840 |
16,115 |
120,466 |
|
Kiambu |
5,695 |
15,3,340 |
3,340 |
11,935 |
9,035 |
27,598 |
|
Thika |
3,795 |
18,367 |
2,254 |
5,372 |
6,049 |
23,739 |
|
Nyandarua |
13,000 |
185,900 |
3,700 |
24,420 |
16,700 |
210,320 |
|
Maragua |
960 |
2,956 |
960 |
2,112 |
1,920 |
5,068 |
|
Total |
31,826 |
301,317 |
20,509 |
94,631 |
52,335 |
395,948 |
Coast
|
Long rains |
Short rains |
total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
T/Taveta |
13 |
130 |
- |
- |
13 |
130 |
|
Total |
13 |
130 |
- |
- |
13 |
130 |
Eastern
|
Long rains |
Short rains |
total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Embu |
750 |
4,500 |
500 |
40 |
1,250 |
4,540 |
|
Mbeere |
14 |
98 |
- |
- |
14 |
98 |
|
Meru Central |
4,600 |
23,000 |
7,250 |
36,250 |
11,850 |
59,250 |
|
Meru North |
250 |
2,500 |
250 |
2,500 |
500 |
5,000 |
|
Meru South |
200 |
160 |
250 |
250 |
450 |
410 |
|
Total |
5,814 |
30,258 |
8,250 |
39,040 |
14,064 |
69,298 |
Rift Valley
|
Long rains |
Short rains |
total |
||||
|
District |
Ha |
Tons |
Tons |
|||
|
Baringo |
53 |
367 |
- |
- |
53 |
367 |
|
Bomet |
150 |
1,200 |
406 |
3,250 |
556 |
4,450 |
|
Kajiado |
700 |
1,830 |
432 |
1,670 |
1,132 |
3,500 |
|
Keiyo |
190 |
3,420 |
90 |
1,620 |
280 |
5,040 |
|
Kericho |
1,200 |
14,400 |
- |
- |
1,200 |
14,400 |
|
Koibatek |
1,023 |
12,300 |
- |
- |
1,023 |
12,300 |
|
Laikipia |
2,435 |
21,900 |
800 |
3,235 |
22.700 |
|
|
Marakwet |
1,800 |
16,200 |
450 |
4,500 |
2,250 |
20,700 |
|
Nakuru |
7,864 |
60,195 |
- |
- |
7,864 |
60,195 |
|
Nandi |
30 |
288 |
- |
- |
30 |
288 |
|
Narok |
2,000 |
18,000 |
700 |
4,000 |
2,700 |
22,000 |
|
TransMara |
70 |
700 |
18 |
180 |
88 |
880 |
|
Trans Nzoia |
656 |
9,470 |
- |
- |
656 |
9,470 |
|
U/Gishu |
1,204 |
23,800 |
- |
- |
1,204 |
23,800 |
|
W/Pokot |
580 |
4,640 |
- |
- |
580 |
4,640 |
|
Total |
19,955 |
188,710 |
2,896 |
16,020 |
22,851 |
204,730 |
Western
|
Long rains |
Short rains |
total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
B/Mumias |
1 |
9 |
0 |
0 |
1 |
9 |
|
Kakamega |
11 |
110 |
18 |
180 |
29 |
290 |
|
Malava-Lugari |
53 |
530 |
- |
- |
53 |
530 |
|
Mt. Elgon |
109 |
1,090 |
160 |
1,600 |
269 |
2,690 |
|
Vihiga |
5 |
45 |
5 |
45 |
10 |
90 |
|
Total |
179 |
1,748 |
183 |
1,825 |
362 |
3,609 |
Nairobi
|
Long rains |
Short rains |
total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
220 |
862 |
125 |
177 |
345 |
1,039 |
|
|
Total |
220 |
862 |
125 |
177 |
345 |
1,039 |
Nyanza
|
Long rains |
Short rains |
total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Gucha |
34 |
510 |
25 |
375 |
59 |
885 |
|
Kisii |
100 |
200 |
80 |
1,600 |
180 |
1,800 |
|
Migori |
22 |
220 |
4 |
32 |
26 |
252 |
|
Nyamira |
43 |
64 |
140 |
2,100 |
183 |
2,164 |
|
Total |
199 |
994 |
249 |
4,107 |
448 |
5,101 |
Summary
|
Long rains |
Short rains |
total |
||||
|
Province |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Central |
31,826 |
301,317 |
20,509 |
94,631 |
52,335 |
395,948 |
|
Coast |
13 |
13 |
- |
- |
13 |
13 |
|
Eastern |
5,814 |
30,258 |
8,250 |
39,040 |
14,064 |
69,298 |
|
Rift Valley |
19,955 |
188,710 |
2,896 |
16,020 |
22,851 |
204,730 |
|
Western |
179 |
1,784 |
183 |
1,825 |
362 |
3,609 |
|
Nairobi |
220 |
862 |
125 |
177 |
345 |
1,039 |
|
Nyanza |
199 |
994 |
249 |
4,107 |
448 |
5,101 |
|
Total |
58,206 |
523,938 |
32,212 |
155,800 |
90,418 |
679,738 |
Table 2c Irish Potatoes 1999
Central
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Kirinyaga |
800 |
7,200 |
900 |
7,560 |
1,700 |
14,760 |
|
Muranga |
300 |
1,296 |
480 |
1,728 |
780 |
3,024 |
|
Nyeri |
7,545 |
63,378 |
8,280 |
59,616 |
15,825 |
122,994 |
|
Kiambu |
4,830 |
46,368 |
6,320 |
56,880 |
11,150 |
103,248 |
|
Thika |
4,300 |
25,800 |
2,650 |
19,080 |
6,950 |
44,880 |
|
Nyandarua |
12,260 |
147,120 |
2,580 |
30,960 |
14,840 |
178,080 |
|
Maragua |
890 |
3,738 |
1,190 |
4,998 |
2,080 |
8,736 |
|
Total |
30,925 |
294,900 |
22,400 |
180,822 |
53,325 |
475,722 |
Coast
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
T/Taveta |
15 |
154 |
0 |
0 |
15 |
154 |
|
Total |
15 |
154 |
0 |
0 |
15 |
154 |
Eastern
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Embu |
750 |
4,500 |
7,500 |
58,500 |
8,250 |
63,000 |
|
Mbeere |
20 |
140 |
650 |
43,050 |
670 |
43,190 |
|
Meru Central |
8,750 |
87,500 |
400 |
3,200 |
9,150 |
90,700 |
|
Meru North |
95 |
855 |
1,700 |
12,600 |
1,795 |
13,455 |
|
Meru South |
103 |
2,060 |
12,750 |
102,000 |
12,853 |
134,060 |
|
Total |
9,718 |
95,055 |
23,000 |
219,350 |
32,718 |
314,405 |
Rift Valley
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Baringo |
23 |
258 |
0 |
0 |
23 |
258 |
|
Bomet |
300 |
2,400 |
660 |
5,280 |
960 |
7,680 |
|
Buret |
200 |
22,200 |
300 |
3,330 |
500 |
25,530 |
|
Kajiado |
824 |
2,472 |
800 |
2,400 |
1,624 |
4,872 |
|
Keiyo |
80 |
1,280 |
0 |
0 |
80 |
1,280 |
|
Kericho |
602 |
4,334 |
90 |
586 |
692 |
4,920 |
|
Koibatek |
836 |
12,540 |
0 |
0 |
836 |
12,540 |
|
Laikipia |
2,000 |
16,000 |
600 |
4,800 |
2,600 |
20,800 |
|
Marakwet |
2,000 |
20,000 |
1,460 |
14,600 |
3,460 |
34,600 |
|
Nakuru |
6,098 |
40,244 |
4,672 |
30,784 |
10,770 |
71,028 |
|
Nandi |
200 |
1,600 |
100 |
800 |
300 |
2,400 |
|
Narok |
2,650 |
23,850 |
0 |
0 |
2,650 |
23,850 |
|
Samburu |
8 |
0 |
0 |
0 |
8 |
0 |
|
TransMara |
52 |
416 |
0 |
0 |
52 |
416 |
|
Trans Nzoia |
564 |
6,768 |
0 |
0 |
564 |
6,768 |
|
U/Gishu |
1,852 |
30,002 |
0 |
0 |
1,852 |
30,002 |
|
W/Pokot |
400 |
3,200 |
220 |
1,760 |
620 |
4,960 |
|
Total |
18,689 |
187,564 |
8,902 |
64,340 |
27,591 |
251,904 |
Western
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
B/Mumias |
8 |
96 |
0 |
0 |
8 |
96 |
|
Bungoma |
46 |
230 |
0 |
0 |
46 |
230 |
|
Mt. Elgon |
150 |
1,800 |
200 |
2,400 |
350 |
4,200 |
|
Vihiga |
10 |
100 |
13 |
130 |
23 |
230 |
|
Kakamega |
6 |
54 |
10 |
90 |
16 |
144 |
|
Malava/Lugari |
11 |
77 |
14 |
98 |
25 |
175 |
|
Total |
231 |
2,357 |
237 |
2,718 |
468 |
5,075 |
Nairobi
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
290 |
248 |
195 |
64 |
485 |
312 |
|
|
Total |
290 |
248 |
195 |
64 |
485 |
312 |
Summary
|
Long rains |
Short rains |
Total |
||||
|
Province |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Central |
30,925 |
294,900 |
22,400 |
180,822 |
53,325 |
475,722 |
|
Coast |
15 |
154 |
0 |
0 |
15 |
154 |
|
Eastern |
9,718 |
95,055 |
23,000 |
219,350 |
32,718 |
314,405 |
|
Rift Valley |
18,689 |
187,564 |
8,902 |
64,340 |
27,591 |
251,904 |
|
Western |
231 |
2,357 |
237 |
2,718 |
468 |
5,075 |
|
Nairobi |
290 |
248 |
195 |
64 |
485 |
312 |
|
Total |
59,868 |
580,278 |
54,734 |
467,294 |
114,602 |
1,047,572 |
Table 2d Irish Potatoes 2000
Central
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Kiambu |
4,730 |
39,220 |
5,050 |
40,400 |
9,780 |
76,620 |
|
Kirinyaga |
800 |
880 |
1,200 |
4,200 |
2000 |
5,080 |
|
Maragua |
1,170 |
18 |
1,100 |
4,000 |
2,270 |
4,018 |
|
Muranga |
390 |
195 |
370 |
370 |
760 |
565 |
|
Nyandarua |
7,780 |
74,688 |
2,380 |
17,850 |
10,160 |
92,538 |
|
Nyeri |
8,100 |
24,300 |
8,500 |
68,000 |
16,600 |
92,300 |
|
Thika |
4,300 |
3,440 |
2,800 |
168 |
7,100 |
3,608 |
|
Total |
27,270 |
142,741 |
21,400 |
134,988 |
48,670 |
277,729 |
Eastern
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Embu |
800 |
800 |
1,200 |
6,000 |
2,000 |
6,800 |
|
Meru Central |
7,000 |
7,000 |
8,530 |
85,300 |
15,530 |
92,300 |
|
Meru North |
1,880 |
6,540 |
2,500 |
25,000 |
4,380 |
31,540 |
|
Meru South |
120 |
0 |
280 |
2,800 |
400 |
2,800 |
|
Total |
9,800 |
14,340 |
12,510 |
119,100 |
22,310 |
133,440 |
Rift Valley
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Bomet |
9,000 |
7,200 |
200 |
1,600 |
9,200 |
8,800 |
|
Buret |
150 |
12,000 |
200 |
20,000 |
350 |
32,000 |
|
Kajiado |
750 |
0 |
900 |
6,300 |
1,650 |
6,300 |
|
Keiyo |
200 |
4,000 |
120 |
1,920 |
320 |
5,920 |
|
Kericho |
210 |
1,890 |
200 |
1,800 |
410 |
3,690 |
|
Koibatek |
900 |
10,800 |
360 |
4,320 |
1,260 |
15,120 |
|
Laikipia |
2,420 |
12,100 |
900 |
7,200 |
3,320 |
19,300 |
|
Marakwet |
2,800 |
28,000 |
1,950 |
19,500 |
4,750 |
47,500 |
|
Nakuru |
6,285 |
31,400 |
1,560 |
12,350 |
7,845 |
43,750 |
|
Nandi |
227 |
1,816 |
425 |
3,400 |
652 |
5,216 |
|
Narok |
2,500 |
13,750 |
644 |
3,542 |
3,144 |
17,292 |
|
Samburu |
15 |
60 |
0 |
0 |
15 |
60 |
|
TransMara |
56 |
560 |
0 |
0 |
56 |
560 |
|
Trans Nzoia |
600 |
900 |
0 |
0 |
600 |
900 |
|
U/Gishu |
2,320 |
41,760 |
0 |
0 |
2,320 |
41,760 |
|
W/Pokot |
370 |
3,330 |
180 |
1,620 |
550 |
4,950 |
|
Total |
28,803 |
169,566 |
7,639 |
83,552 |
36,442 |
253,118 |
Western
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
B/Mumias |
5 |
50 |
2 |
20 |
7 |
70 |
|
Bungoma |
41 |
246 |
0 |
0 |
41 |
246 |
|
Kakamega |
8 |
64 |
3 |
24 |
11 |
88 |
|
Malava/Lugari |
120 |
960 |
0 |
0 |
120 |
960 |
|
Mt.Elgon |
214 |
2,996 |
204 |
1,224 |
418 |
4,220 |
|
Vihiga |
6 |
60 |
6 |
60 |
12 |
120 |
|
Total |
394 |
4,376 |
215 |
1,328 |
609 |
5,704 |
Nairobi
|
Long rains |
Short rains |
Total |
||||
|
District |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
290 |
248 |
195 |
64 |
485 |
312 |
|
|
Total |
290 |
248 |
195 |
64 |
485 |
312 |
Summary
|
Long rains |
Short rains |
Total |
||||
|
Province |
Ha |
Tons |
Ha |
Tons |
Ha |
Tons |
|
Central |
27,270 |
142,741 |
21,400 |
134,988 |
48,670 |
277,729 |
|
Eastern |
9,800 |
14,340 |
12,510 |
119,100 |
22,310 |
133,440 |
|
Nairobi |
290 |
248 |
195 |
64 |
485 |
312 |
|
Rift Valley |
28,803 |
169,566 |
7,639 |
83,552 |
36,442 |
253,118 |
|
Western |
394 |
4,376 |
215 |
1,328 |
609 |
5,704 |
|
Total |
66,557 |
331,271 |
41,959 |
339,032 |
108,516 |
670,303 |
Tables 3 a, b, c, d and e present the recorded monthly prices for red and white potato varieties for the years 1995 to 2000. Previous similar studies on potato prices by Durr and Lorenzl in 1980 lumped together potato varieties on the basis of whether red or white and found a very significant difference in prices between red or white varieties based on colour grouping. Figures 1 a and b present the yearly price and production averages for the five most productive districts in potatoes in a graphic form for the period 1995-2000.
The drastic fluctuation
in production tonnage indicates the effects by drought. In 1996, production
was very low due to the prolonged drought from 1995, which was followed by a
bumper crop in 1997 as a result of El nino. Nyeri, one of the highest potato
producer districts in the republic illustrates the production trend very well
as influenced by the drought and rain patterns. The yields of 1997 came down
slowly to levels in 2000, lower than those in 1996, again due to drought conditions.
Examination of the prices trend over the same period shows that prices fluctuations
over the years are not 100% dependent on production as would be expected. Only
the pattern of change from 1999 to 2000 in both production and prices that reflect
the normal inverse change relationship.
![]() |
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Fig.6 shows the
monthly potato buying prices in Nyandarua for the years 1997 to 2000. On the
local situation, the prices indicate very much the typical production seasonality
effect, with some significant distortional effect. The data for 1997 were unfortunately
not all available, but as usual prices started high increasing to 1650/= per
bag in March. The El nino rains set in during 1997 and it would be interesting
to find out how the prices trends were affected by El nino. It has been established
that despite improved potatoes supply during rainy season, producers prices
are known to decline while those at the market outlets steeply increase due
to muddy roads, which make it impossible to ferry the potatoes to the market.
In 1998 prices remained above shs.700/= through out the year mainly because
of the shortage in the country due to drought, and the same trend was maintained
in 1999 except after June 1999 when prices dropped drastically to below shs.500/=
until October. After October prices increased moderately, to December 1999,
then dipping to below 500/= only to increase almost 4 fold in April, and remained
so until after July 2000. These erratic and rather unpredictable prices fluctuations
appear to be influenced not only by the drought conditions but also the potato
production and supply from other parts of the country including the effect of
road conditions in rainy seasons. The potato supply from different parts of
the country to particularly Nairobi plus other towns such as Nakuru, Naivasha,
Thika and Nyeri appear to be the main price setters for buying prices in Nyandarua
and other major potato growing areas.
Figure 2 a Prices fluctuations 1995/96 - White potatoes
Figure 2b Price fluctuations 1997/98 - White potatoes
Figure 2c Price Fluctuations 1999/2000- White potatoes
Figure 2 d Price fluctuations 1995-96 red potatoes
Figure 2 e price fluctuations 1997-98 - red potatoes
Figure 2f Price fluctuations 1999/2000 - red potatoes
Figure 3: Mean monthly prices fluctuations 1995-2000
Figure 4: Total production in the 4 districts Vs prices at Wakulima
Figure 5a Potatoes prices in Nairobi vs Production in Meru and Thika
Figure 5b Potato prices in Nairobi vs production in Nyeri and Nyandarua
Figure 6: Average buying prices for Irish Potatoes in Nyandarua
for the years 1997-2000
The implications of these findings are:
a. The potato supply at the local production areas is not a direct determinant of the selling or buying prices for potatoes in the area.
b. The potato producers in the growing areas lack the ability and mechanism to set or influence selling prices for their potatoes.
c. The market forces responsible for determining the producer selling prices for the farmer are based in the marketing chains and operational efficiency by the market agents, prices prevailing at the major urban market outlets, and the supply of potatoes from other areas in the country, whose supply seasonality differ due to climate variation and specifically differences in the rainfall pattern.
d. Accordingly, on-farm potato storage by farmers under the current potatoes market structure is unlikely to be viable in terms of availing better prices to the farmer, due to the unpredictable prices and lack of control of the prices by the potatoes producers.
Fig.7 presents the potatoes marketing channels in Nyandarua. In total 8 marketing channels for potatoes to the consumers exist. The consumers of potatoes include rural producers & consumers, urban consumers and institutional consumers namely Hotels/Restaurants, schools, hospitals, Processors and the army. A significant change from the marketing channel as identified twenty years ago by Durr and Lorenzl in 1980, is the creation of brokers as agents in the chain, at both producers and consumer levels. Over 80% of commercially marketed potatoes can be estimated to go through brokers at both ends of the marketing channels where they are involved. The little that does not go through brokers is either marketed directly to consumers (mainly institutions on contracts) by producers or producers /traders with on- farm storages or by transporters /distributors particularly those supplying sub-urban markets where there are no brokers.
Table 4 gives a summarized description of the marketing channels' agents in terms of their activities in the chain. From the data, it is clear that only producers are involved in some storage of potatoes on Farm. It was estimated that less than 10% of producers held on potatoes in form of" storage". The kind of storage ranged from simply covering heaps of harvested potatoes with grass and then soil to simple mud plastered wooden structures for a potato store. Part of doing this was as a matter of fact not deliberately meant to store potatoes but rather hold potatoes while awaiting brokers or buyers. 20 years ago Durr and Lorenzl (1980) reported lack of potato storage for speculative purposes, but instead gathering of large quantities in the field, enough to fill a lorry according to order or in fulfillment of a large contract. Producers said to store potatoes for speculative purposes reported storing potatoes for periods ranging from 2-6 months. However they pointed out that storage of potatoes was not preferred because of
a. The need for cash
b. High labour costs involved
c. New harvest in other areas arrived before selling the crop, and storing did not guarantee better prices and
d. A lot of wastage.
Those who did not store potatoes also cited lack of a guarantee for better prices on storing potatoes, and preferred to feed potatoes to cattle if they were unable to dispose them off during the glut season. The level of wastage cited ranged from 40 % and involved rotting, greening, loss of flouriness and watery development, germination plus shrinkage and weight loss. It was however pointed out that consumers did not object to germination in potatoes for consumption, and the potatoes, which developed greening, were set aside for seeds. The production yields per acre varied widely among the producers namely 20-120 bags, reflecting varied agronomic practices and use of agronomic inputs. This translated to drastic variable quantities handled per producer, ranging from 500-2000 bags per year depending on the acreage cultivated. Such data indicate the vast potential in increasing potato production by both acreage and yields, provided the necessary incentives are given to the farmers. In Nyandarua, producers reported that they could produce potatoes 2 to 3 times a year depending on weather patterns. Such incentives are best in form of prices that can guarantee the farmers' return for their investment, which should also be predictable.
The prices fluctuations in terms of highest and lowest fits in within the reported pattern in Fig. 5. However the lowest prices reported in 2001 were significantly lower ranging from shs.150-300/= per bag compared to those in Fig 5. The difference of course is due to the bumper crop in 2001compared to the poor harvest during the drought years following El-nino to the year 2000. The highest prices occurred during the months of November to May and early in the year 2001, then were depressed again because of the bumper crop to averaging shs.500 per bag. The sale unit bag is not standard and ranges in weight from 130 - 180 kg. The broker, who is responsible to bagging and loading transport vehicles, determines the weight. According to producers, the ideal price for their potatoes should range from shs.600- 800 /= in order to make profit. There is also need to standardize the bag size to say 90kg like in maize, or stick to the accepted size 130kg. The producer however has no say in this, and is under the buyer or broker's mercy so to speak.
As one moves up the channel, the prices increase due to the costs and operational margins for the marketing agents involved. The brokers charged shs.100- 120/= per bag for their services namely identification of suppliers, prices negotiation, potatoes bagging and loading. Depending on the prevailing producer prices, this amounts up to between 20-60 % of the prices offered to the producers. It was difficult to establish the exact margins for other agents although retailers reported that their target was making shs. 100 per bag. The wholesalers targeted shs.100- 150/= per bag. Various agents also paid various statutory fees in their marketing operations, namely county council cess, open air market space rent, cost of empty bags, and sewing sisal ropes. Most of the agents interviewed reported their business as being 100% based on potatoes. Only a few transporters reported being involved rarely in transportation of cabbages of even building sand. This is an indication that operations by the marketing channels agents for potatoes is a full time business for the agents involved. Towards the consumer level, the prices thus increase as expected. The lowest and highest price ranges reported by transporters /distributors are shs.150- 350/= and shs.500-1500/= respectively, during the corresponding peak and low supply seasons. At the wholesaler level the lowest prices recorded ranged from 400-500/= while the highest ranged from shs. 1000-1500/=. At the retailer level, lowest buying price of shs.350/= versus highest buying price of shs.1500 and above were reported.
Table 4:Descriptive characteristics of agents in the marketing channels for Potatoes in Nyandarua.
|
Description Item |
Producers |
Brokers |
Transporters/ Distributors |
Wholesalers |
Retailers |
|
|
1. |
Marketing functions |
Potatoes production and harvesting |
· Producers/suppliers identification. · Buying and prices negotiation. · Bagging and loading |
· Buy through broker. · Transport to market. · Sell through broker. |
· Buying from farmer direct or lorry via broker. · Bagging. · Hire transport. · Sell to retailers |
· Buying in bags from lorry or transporters cum distributors. · Repackage in buckets, display and sell to consumers or traders. |
|
2. |
Storage |
By less than 10 per % of producers for 2-6 months. Problems: · Germination · Rotting · "Kugacha" · Shrinkage + weightloss · Greening · Better prices not guaranteed |
None |
None |
None |
None |
|
3. |
Wastage |
10-40% |
None |
0-5bags/40 bags(truck load) |
0-10% |
0-5% |
|
4. |
Quantity handled |
500-2000 bags per year depending on acreage |
Organises for 4-5 buyers per week at 40 bags per truck |
Approx. 80 bags per week |
10-60 bags per week |
6-18 bags per week |
|
5. |
Varieties: · Tana · Tana(K) · Tigoni · Nyayo |
· For sale mainly · For sale mainly · For sale mainly · Household consumption |
Commercial and house hold consumption |
Mainly for chips and stew |
Mainly Nyayo and Tana for stew and Chips |
Mainly for stew and chips |
|
6. |
Prices fluctuation |
· Highest price: 500-1000(Nov-May) · Lowest price: 150-300(April-Nov) · Best price: 600-800 |
Charges 100/=per bag but usually can negotiate |
· Lowest price: 150-350 (April-Nov) · Highest price:500-1500( Dec-April) |
· Highest Buying Price: 1000-1500 · Lowest Buying Price:400-500 |
· Highest Buying Price: 1500/= (Dec-Mar) · Lowest Buying Price: 350/= (Dec-Mar) |
|
7. |
Supply seasonality |
Production seasons: 2-3 times per year |
Move to different production areas |
· Lowest season: Nov-May · Highest season: (April-Nov) |
· Lowest · Season(Nov-April) · Highest Season( May-Sept) |
· Lowest Season (Jan-May) · Highest Season (May-July) |
|
8. |
Marketing Problems |
· Low prices determined by brokers · Sale bag unit too big(130-180kg) · High production cost. · Fewer buyers and over supply. · Diseases (blight and rotting) · Poor roads. · Drought. |
Buyers may reject potatoes after bagging if price is unfavourable. |
· Poor roads. · High vehicle operation costs. · Erratic selling price hence losses. · No problem in buying price. · Insecurity during travel. |
· Poor erratic selling prices. · High council charges. · Perishability. |
· Lack of buyers. · Price fluctuation. · Rotting and wastage |
Over the years various marketing agents reported occasional high spiky prices rising between 2000 and 6000 per bag during severe shortage times. These prices of course are negotiable and also depend on whether the purchase is direct from the farmer or not.
The bottom line is that: It is the marketing agents who control, determine and set the buying prices for the producer as well as the selling prices for the consumer. The consumer prices at the major urban market outlets are however subject to supply and demand forces due to competition among suppliers from different production areas of the country. Whatever prices are set at for example, Wakulima in Nairobi, they form the basis for setting buying prices for the producers in the production areas, via down the market chains. Only when there is severe potato shortages at the major urban markets followed by sharp increases in prices, is this effect likely to reach the producers, and only when the shortage is prolonged for example during droughts. If such prices spiky or short-lived then the producers miss the opportunity. During the drought situation, the farmer is unable to bag- in the opportunity since potato production in Kenya is 100% rainfed, unless one is lucky and benefits from the rainfall usually irregularly distributed over the country, during the prolonged drought periods. The producers thus find themselves in gambling situations where he produces potatoes first for home consumption and secondly for sale, and only make profit if they are lucky, else they feed them to the cattle. On being asked why the producers grow commercial potatoes without profit anticipation, the answer by most producers was that there was no other opportunity cost for the utilization of the land free from other enterprises, and in any case, there are times or years when they have been lucky and made some money.
The marketing problems encountered by the producers are:
· Unpredictable low prices determined by the brokers that make the producer even unable to break even in the potato production enterprise.
· The sale bag unit, which is too big and unstandardised (130 -180 kg) is exploitive and further depresses the real price for their potatoes.
· High production cost due to expensive inputs.
· Fewer buyers and over supply.
· Potato diseases mainly blight and rotting.
· Poor roads.
· Drought
Those encountered by brokers include buyers or transporters rejecting potatoes after they have procured and bagged them from the farmer, if prices change unfavorably at the market outlets.
The transporters faced the problems of poor roads, high vehicle breakdown and operational costs, erratic selling price hence losses, and insecurity on the roads when transporting potatoes to the market. They expressed having no problems with the buying prices. The wholesalers on the other hand indicated having problems with erratic selling prices, high statutory council charges and losses due to potatoes perishability. The retailers complained of lack of buyers, again prices fluctuations, wastage and losses due to rotting of potatoes.
The results above show that the potatoes market in Kenya operates at near perfect conditions only at the level of major urban market outlets due to supply competition offered by potatoes from different production districts of the country. At the producer's level the market is imperfect with the prices determination and control being done by the marketing chain agents and in particular brokers. This is apparently done without consideration for the producers' economic performance in their potatoes production enterprises. Accordingly there is a strong need to restructure the market such that the producers can be empowered to repossess ownership of their potatoes which they lose once they have harvested their crops. Then they can have some control over determination of prices for their potatoes on a predictable basis; to enable them break even and make some profits with their potatoes. They would then increase production according to market demand. The on-farm storage has been shown to be ineffective given the different harvesting seasons in different parts of the country, and the variable erratic distribution of rainfall in the potatoes growing areas in the country. The only potential effective market restructuring that would incorporate the above element is having a national potatoes storage, preferably owned partially or fully by producers, and operated commercially as a private company, unlike the similar structure in marketing of cereals, where National Cereals and Produce Board is government owned. The Potato Storage Company would purchase and market the potatoes from the producers in competition with the existing market channels at prices favourable to both the producers and consumers, and even possibly in collaboration with the existing marketing channels agents. In this way the favourable prices offered to the producers would enable them produce more potatoes thus contribute towards evening out of prices fluctuation and amelioration of Food Insecurity in the country, particularly during times of maize crop failures.
3.2 Irish Potatoes Changes during Storage
The potatoes were set up for the storage experimentation on 6th July 2001, and have been tested starting from 6/07, 26/07, 16/08, 18/09and 15/10, in total, after 120 days. The last evaluation tests are due to be done on 14th Nov and 14th Dec, thereby completing the storage period of six months as planned. The storability experimentation was carried out on 4 potato varieties namely Tana for chips, Dutch for crisps, Meru for mashing &stew and Nyayo for chips.
Results:
a. Sprouting:
After 51 days, sprouting was evident in the Dutch variety only. After 141 days Nyayo had shown slight signs of sprouting, but Tana and Meru have not yet shown any signs of sprouting. Also Tana and Meru have shown no change in their physical appearance. The Dutch variety has also not changed much by way of physical appearance except sprouting. Nyayo has however shown relatively more change in physical appearance than the rest.
b. Weight Loss.
Table 5 shows the average weight loss for the 4 varieties.
|
Storage Days |
Varieties |
|||
|
Tana |
Nyayo |
Dutch |
Meru |
|
|
Fresh |
514.55 |
411.73 |
538.35 |
468.30 |
|
21 |
514.50 |
411.70 |
558.30 |
468.00 |
|
51 |
506.78 |
397.74 |
552.18 |
451.12 |
|
81 |
499.83 |
388.69 |
546.00 |
438.39 |
|
111 |
490.44 |
377.91 |
540.90 |
416.29 |
|
141 |
483.70 |
370.19 |
522.70 |
401.26 |
|
% Weight Loss |
6 |
10 |
6.6 |
14.3 |
Meru appears so far to have lost the greatest weight of 14.3% compared to Tana, which has lost 6% less than half of the loss in Meru. Interestingly enough there is apparently no association between changes in physical appearance and loss in weight. Weight loss would be expected to be associated with shrivelling.
c. Sugar development
Table 6 shows the sugar development with storage by the varieties studied.
Table 6: Development of Sugars on storage
|
Storage Days |
Sugars Developed in % |
||
|
Dutch |
Tana |
Nyayo |
|
|
81 |
2 |
5 |
1 |
|
111 |
5 |
6 |
3 |
|
141 |
7 |
6 |
5 |
Development of sugars is only expected to cause problems in varieties used for crisps and chips because of browning or colour change on deep-frying. Table 7 shows the colour development for the products made from the 3 varieties.
Table 7: Browning colour development on deep-frying with oil
|
Storage Days |
Colour development in absorbance units at 420nm |
||
|
Dutch(Crisps) |
Tana(Chips) |
Nyayo(Chips) |
|
|
Fresh |
0.126 |
0.114 |
0.084 |
|
21 |
0.140 |
0.147 |
0.103 |
|
51 |
0.366 |
0.366 |
0.140 |
|
81 |
0.490 |
0.864 |
0.323 |
|
111 |
0.792 |
1.338 |
0.561 |
|
141 |
1.992 |
1.506 |
0.858 |
From the results it is clear that Dutch variety which showed significantly more germination than others by as early as 51 days showed considerable colour development by 141 days. The sugars development pattern in the 3 varieties however appear not to be significantly different. It is difficult to standardise the cooking method to avoid errors due to temperature variation. Crisps however on account of their thin shapes are likely to achieve much higher temperatures for the same period
they are exposed to hot oil with chips. Accordingly one cannot draw from the data, a direct relationship between variable degrees of germination plus sugar development and browning colour development on cooking. However it was apparent that crisps from the Dutch variety developed bitterness after 81 days of storage.
From the results so far, one can conclude that except for the Dutch variety, all the others can be stored for the days so far experimented without compromise on the utilisation quality. It is significant to also note that contrary to what one would expect, acceptability improved with sweet taste development on storage of the varieties, (with the exception of bitterness imparted to crisps from Dutch variety) and in particular with Meru used for mashing and stew.
3.3 Viability of large-scale potato storage
With the collaboration with Netagco Tolsma, the necessary data is being collected for a feasibility analysis, according to annexture (III) questionnaire. This information plus a visit meant to gain an appraisal on the fixed Capital Investment, plus the up-to-date operational technology, will enable putting together all the necessary economic parameters for viability analysis of a commercially operated large scale potato storage facility in Kenya or for East Africa in general.
1. Materials
1.1 Irish potato varieties as under:
Product Variety
Crisps Dutch (Ngorof /Bomet)
Chips Tana or Nyayo or Tigoni
Cooking Kerrs pink (Meru)
1.2 Germination suppressant : Prophan 1%CIPC dust
2. Storage Conditions in Environmental controlled Cabinets.
q Each variety in its own cabinet.
q No light (day or artificial) in all cabinets thus must be light proofed.
q Humidity maintained at 95%.
q Storage temperature 500 F º 100C.
q Potatoes are washed to remove soil and dipped into 50 - 60% ethanol solution to dry them off, and harden the skin. They are then dusted with Propham.
q Potatoes are packed in small crates and put into cabinets.
3. Quality evaluation during storage.
3.1 Quality evaluation regime:
a) 1st one when freshly put in the cabinets.
b) 2nd one after 3 weeks.
c) 3rd one after 30 days.
d) Thereafter analysis after 60, 90, 120, 150 and 180 days.
3.2(a) Analytical Parameters:
q Weight loss - to discuss method.
q Note time when sprouting from the eyes begins.
q Length of the sprout (average)
q Greening.
q Examination for storage rot.
q Shrivelling - development of softness and compression.
(b) Utilisation evaluation.
q Crisps - Colour development
- Sugars development
- Taste (bitterness)
q Chips - Colour
- Sugars
- Oil uptake
q Cooking - Flouriness check and mashy/ translucence development.
- Taste compare with fresh control.
Annexure 1
INTERVIEW GUIDE ON POTATO COMMERCIALISATION AGENTS IN NYANDARUA DISTRICT
Name and Address (Physical and Residential)
________________________________________________________________________________________________________________________________________________________________________________________________________________________
(a) Describe the type of agent in the chain (according to the list below by ticking one of the descriptions).
(i) Producers/Storage - warehousing/Traders
(ii) Transporters/Distributors/Wholesalers/Retailers
(iii) Organizations
· Producer to Retailer (institutions/consumer)
· Producer to wholesalers (stores) to traders to consumers
· Producer to trader / transporter to wholesalers (Indians) to Traders to Consumers.
· Producers to Traders to Institutions.
· Importers/Exporters
· Open air market
· Others (name)
(b) No. of agents in (a) above (self assessment)
(c) Marketing functions of agents in (a). What functions do you perform?
(d) Quantity percentages of product flow in the chain and distribution channels (self assessment)
(e) What is the quantity of wastage at the various levels of the chain?
(f) What varieties are quite commonly traded and for what use?
USE
VARIETY
CRISPS
CHIPS
MASHING FOOD OR MAKING STEWS
(g) What no. of competitors do you have?
(h) No. of suppliers/sellers.
(i) How does price change within the year? What are the highest and lowest prices that you purchase and sell at within the year? (Price per kg).
Price change
PURCHASES (price per bag in Kshs)
SALES (price per bag in Kshs)
Lowest price
Average price
Highest price
(j) Monthly price changes per kg/bag in the past year.
(k) Price elasticity of supply (by calculation).
(l) How do you identify your market and how do you determine your prices.
(m) What are the constraints and problems you face during marketing?
(n) What are the credit facilities available to you?
(o) Do you market any other products/commodities?
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(p) Do you have an all year round supply of your potatoes?
(p) During which months do you obtain your highest and lowest supply of
potatoes?
Any other comment/observation: ……………………………………………………
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NOTES FROM PILOT
TESTING:
It was noted that the most commonly traded potatoes at Kinangop region were:
Nyayo- multipurpose
Mugaruro- for cooking
Tigoni- for chips
Tana-Kimande- they last longer and are more storigible.
It is very difficult to get a constant pattern of monthly changes in the price of potatoes since in most of the cases, it is not the farmer who determines the price of the potatoes at any one point. In most cases, the price is determined by the outlet markets, and also the quantity of potatoes brought into the market from other regions. The price also varies depending on the variety.
No specific agent has specific competitors. For them, any agent automatically becomes a potential competitor. This, to some extent is due to the fact that the farmers do not have specific agents to whom they always go to.
Prof. S.K. Mbugua
DFT&N.