ECONOMICS OF IRRIGATION ON SUGARCANE CROP IN PESHAWAR

Transcription

1 ECONOMICS OF IRRIGATION ON SUGARCANE CROP IN PESHAWAR *Amjad Ali,* Muhammad Nazir, *Muhammad Sajjad, **Dr. Dawood Jan, ** Dr Abbasullah Jan ***Muhammad Fayaz and ***Abdur Rahman ABSTRACT Yield, cost and net revenue of sugar crop grown along two watercourses originating from Kabul River Canal (KRC) and Joe Shiekh Canal (JSC) were analyzed to differentiate between the effects of various locations, including head, mid and tail areas. On an average, the yield per acre was estimated at 451 maunds. However, yields per acre at head was 471 maunds and lower by 18 and 41 maunds per acre at mid and tail locations. Contrasting to the yields, net revenue were higher at mid and tail locations than at head these were Rs per acre at head and were higher by Rs and Rs per acre over the mid and tail locations, respectively. The increases in net revenue, in spite of the decreases in yield per acre, occurred due to the relatively high prices and low cost at mid and tail areas. Prices were found higher at lower areas (mid and tail of watercourses) and differences were quite significant statistically. Costs were found lower at lower locations and reductions were statistically significant. Such reductions occurred in an overall case, as well as, in two watercourses under study. On the basis of analysis, it was learnt that net revenue from sugarcane production increased along watercourses from head-to-tail; however, the increases in net revenue were not due to higher yields, but were due to higher prices and lower costs of production along head-to-tail direction. It was further learnt fertilizers applied, labor days employed and costs incurred on all other inputs seemed to determine yields. However, KRC exhibited somewhat different results where items/factors other-than-fertilizers and man-days seemed to exert statistically more strong results than the two other explanatory variables included. Keywords: Economics ; Irrigation ; Sugarcane Crop ; Peshawar INTRODUCTION Sugarcane (saccharum officinarum L.) is an important cash crop of Pakistan (Rehman et al.1992), which plays an important role in economic up lift of farmers and the ever-expanding sugar industry totally depending on cane cultivation.however the national *Amjad Ali Muhammad Nazir and Muhammad Sajjad are PhD students in Deptt: of Agricultural Economics Khyber Pakhtunkhwa Agricultural University, Peshawar, Pakistan. **Dr. Dawood Jan, Dr. Abbas Ullah Jan are associate professors Department of Agriculture Economics, Khyber Pakhtunkhwa Agricultural University, Peshawar Pakistan. ***Muhammad Fayaz and Abdur Rahamn,are Lecturers Department of Agriculture Economics,Khyber Pakhtunkhwa Agricultural University, Peshawar Pakistan. 120

2 average cane yields 47 t/ha, which is far below the exciting potential (GOP: 2000), sugarcane is a tropical crop, being cultivated in worlds and main source of sugar production. It is being produced in 69 countries of the world (Humber 1968). Sugarcane is an important industrial and cash crop of Pakistan but its production per unit area is considerably lower than many other sugarcane producing countries of the world. This crop is usually cultivated on irrigated lands. Its optimum sowing time ranges from mid February to late March in the Punjab and from September to mid October in Sindh Province. In NWFP sugarcane is usually planted from mid September to December as autumn plantation and from February to March as spring Plantation. This crop is usually intercropped with other crop such as wheat (Masih et al 1988). Total area during in Pakistan under this crop was million hectares with million tones production. In this NWFP had million hectares area with production of 4.71 million tones (GOP :1999). Water is a precious input in farming because the potential of genetic improvement in the crop verities and agronomic innovations can be fully tapped only if irrigation available in the vast areas, where the annual precipitation is very low or inadequate. Irrigation provides scope for sustainable agriculture and paves the way to reduce rural poverty, hunger and malnutrition. If irrigation is managed properly, it increases the intensive and extensive use of land.(jehangir and Sympathy, 1991: Sarwar and Bastianssen, 2001) Irrigation water is essential for Pakistan farmers because it means an assured crop, higher yield, more income and more employment. To Pakistan, it means 24.1% of gross domestic product and 64% of all exports provided by product originating in the agricultural sector (GOP:2002). The study is important in several ways. Firstly the study yields important data on different aspects of sugarcane production, cost and revenue. Secondly, this data would be of immense value to planners, researchers, and other persons interested in sugarcane crop. The study was mainly based on quantative analysis techniques. The research finding showed the position of the farmers at the watercourse and also where the irrigation water relatively found more reliable. These included comparison on the basis of t-statistics besides using simple averages. Production function for different categories of farmers was also estimated and used for comparison purposes. 121

3 Objectives of the Study The main objectives of the study are: 1. To determine per acre yield, cost and net revenue of sugarcane crop. 2. To determine the difference in per acre yield, cost and net revenue at head mid and tail section of irrigation water supplying watercourse. 3. To estimate production and cost functions. 4. Making recommendation based on findings of the study. MATERIAL AND METHODS This chapter deals with the methodology and material to be used for analyzing the problem under investigation. In order to obtain valid and reliable data pertaining to the problem under investigation, there is need to take in consideration a number of important factors. These are briefly discussed as follows. Selection of the Study Area The study was conducted in district Peshawar in areas commanded by two watercourses originating from Kabul River Canal (KRC) and the Joe Sheikh Canal (JSC), which runs from Warsak Dam and flows towards Peshawar City. The two watercourses selected originate from villages Dermange and Patwarbala, which are respectively, situated at Joe Sheikh and Kabul River Canal. The purpose behind this selection was that, Peshawar is one of the key Agricultural District. Its soil and climate conditions are very conducive for various agricultural crops. Sugarcane, Wheat, maize, fodder and various types of vegetables are cultivated here on large scale, but sugarcane and wheat are the main crops of this area. Most of the crop area is irrigated through canal water coming from Warsak Dam. Sampling of the Study Area: Peshawar District comprises of a large number of villages. Thus it was impossible to study all the villages because of financial constraint, time and conveyance problems. Therefore, two villages namely Dermangi and Patwarbala, were selected. 122

4 Sample Size and Sampling Design A list of all operating farmers was obtained. The total number of such farmers was 67. Than a two stages stratified random sampling was used. In the first stage these farmers were divided into two strata i.e. those lying at JSC (about 37), and at KRC (about 30). In the second stage each strata was divided into watercourse Head, Mid and Tail on the basis on their location at the watercourse. All of the 67 farmers located along the two watercourses were selected out of which small farmers at JSC and KRC were 19 and 13 in numbers whereas the numbers of medium and large farmers at these watercourses were 12, 10 and 6, 7 respectively. The distribution along Head, Mid and Tail is provided as follows. Table 1 Distribution of Sample Sugarcane Growers by Head, Mid and Tail locations Name of canal Number of respondents WC-Head WC-Mid WC-Tail JSC KRC Source: Survey Data Collection of Data This research was based on primary data. For the collection of primary data from the respondents the following steps were followed. a) Preparation of Interview Schedule Interview schedule/questionnaire was constructed in such a way to collect complete and correct information. b) Interviewing Procedure The researcher personally interviewed each respondent individually and separately. During interviewing the purpose of the study was also explained to the respondents. 123

5 Analysis of the Data Data collected from the selected respondents was entered in to computer software excel. Using software package SPSS the data was analyzed to estimate the required co-efficient of the various inputs. For the analysis of primary data the following steps were followed. 1. Simple budgeting technique was employed to arrive at cost and revenues of sugarcane growers. 2. The following dummy-variable econometrics techniques were used to differentiate between yield (Y), net revenue (NR), prices (P) and cost (C) across the two watercourses (JSC-WC & KRC-WC) and Head-to-Mid-to-Tail locations. The purpose of the dummy variable econometrics techniques is to consider the role of qualitative explanatory variable in regression analysis. The introduction of the qualitative makes regression model extremely flexible tool that is capable of handling many problems encountered in empirical studies (Gujrati: 1995) Y = β 0 + β 1 DM + β 2 DT Y (JSC) = β 0 + β 1 DM + β 2 DT Y (KRC) = β 0 + β 1 DM + β 2 DT NR = β 0 + β 1 DM + β 2 DT NR (JSC) = β 0 + β 1 DM + β 2 DT NR (KRC) = β 0 + β 1 DM + β 2 DT P = β 0 + β 1 DM + β 2 DT P (JSC) = β 0 + β 1 DM + β 2 DT P (KRC) = β 0 + β 1 DM + β 2 DT C = β 0 + β 1 DM + β 2 DT C (JSC) = β 0 + β 1 DM + β 2 DT (3.1a) (3.1b) (3.1c) (3.2a) (3.2b) (3.2c) (3.3a) (3.3b) (3.3c) (3.4a) (3.4b) 124

6 C (KRC) = β 0 + β 1 DM + β 2 DT (3.4c) DM stands for dummy for mid location and DT dummy for tail location, and the coefficients attached with these two dummies β 1 & -β 2 would measure the magnitudes by which the two locations would differ from Head; the intercept β 0 would measure the average value for head location. 3. The trend-variable econometrics techniques has also been used to further confirm whether yields (Y) and costs (C) of sugarcane per unit areas change along Head-to-Tail direction, and if such changes occur, then in which directions negative or positive. Y = α + βt C = α + βt (3.5a) (3.5b) Variable t = 1, 2, 3, would represent number for growers located along head-to-tail direction; α would measure average value of Y or C and β would measure the rate at which the average value of the variable (Y or C) involved would change; sign of β would indicate whether the Y and C would be increasing or decreasing. 4. The following econometrics models have been specifed to estimate production (Y) and cost (C) functions of sugarcane crop. Models 3.6 (a, b & c) would attempt to identify and capture the effects of major determinates of production/yields per acre of sugarcane. Amongst the three major explanatory variables specified are fertilizer used (FU), labor days employed (LU) and costs incurred on all other inputs (AOC). In case of cost function, inputs like fertilizers (F), farm yard manure (FYM), seed (S) and labor (L) along with expenses on all other items would be used as explanatory variables. 125

7 RESULTS AND DISCUSSION The results achieved during the course of study are presented as below:cane crop. General Background Information Of the total 67 respondents studied, 37 are located on watercourses originated from Joe Sheikh Canal (JSC) and 30 are located on watercourses originated from Kabul River Canal (KRC). The two watercourses (JSC-WC and KRC-WC) are further divided into Head (H), Mid (M), and Tail (T) locations. A further breakup of growers, showing their H, M and T- wise distribution, is provided in Table 2. Yields, Costs and Revenues of Sugarcane Across Two Watercourses Data on yields of sugarcane obtained, costs per acre incurred and revenues per acre accrued in the two watercourses areas are provided in Table 3, while the same information, giving an H-, M- and T-wise position, has been summarized in separate Tables 4 and 5 Per Acre Yield Compared The aforementioned referred tables reveal that per acre yield ( maunds) at Kabul River Canal is higher than Joe Sheikh Canal (449.92); the overall yield is mounds per acre. Head and mid of the watercourses at Joe Sheikh Canal give higher yields than that of Kabul River Canal. While at tail, Kabul River Canal exceed Joe Sheikh Canal, where per acre yield is 443 and 432 mounds per acre, respectively. Per Acre Cost Compared A comparison of cost per acre shows that costs at Kabul River Canal (Rs. 9986) are slightly higher than Joe Sheikh Canal (Rs ). Costs at head and tail of Kabul River Canal are Rs and Rs. 8746, while at Joe Sheikh Canal, these are Rs and Rs , respectively. Per Acre Revenue Compared A comparison of per acre revenues revels that total revenue at head and mid of Joe Sheikh Canal are Rs and Rs per acre, respectively, and are higher than that of Kabul 126

8 River Canal (Rs and Rs ). At tail, Kabul River Canal s total revenues (Rs ) exceeds that of Joe Sheikh Canal (Rs ). As far as net revenues are concerned, it appears that net revenues increase from head to tail. Net revenues at both the canal fluctuate less compared to the costs. Net revenues at the watercourses located at Kabul river canal are Rs , and while at Joe Sheikh are Rs , and 13774, respectively; the overall average net revenues are Rs , Rs and Rs per acre. Table 2 : Yield, Costs and Revenue Per Acre of Sugarcane Crop JSC-WC KRC-WC Overall Yield/acre Cost Of Prod Npl cost/acre SB cost/acre Seed cost/acre Urea cost/acre DAP/NP cost FYM cost/acre Hoe cost/acre Hr cost/acre Coll cost/acre CFFMr/acre Irr cost/acre L cost/acre

9 Tax/acre Total cost/acre Total Rev/acre Net Rev/acre Where JSC= Joe Sheikh Canal, KRC= Kabul River Canal, WC = watercourse NP1 = Normal plough, SB = seed bed preparation, DAP/NP = Di Ammonium Phosphate/Nitrophos, FYM = Farmyard Manure, Hoe = Hoeing, Hr = Harvesting, Coll = collection, CFFMr = Cost from field to market, Irr = Irrigation, L = Loading Table: 3 Yield Cost and Revenue of Sugarcane at Head Areas of JSC and KRC JSC H KRC H Overall Yield/acre Cost Of Prod Npl cost/acre SB cost/acre Seed cost/acre Urea cost/acre DAP/NP cost FYM cost/acre Hoe cost/acre Hr cost/acre

10 Coll cost/acre CFFMr/acre Irr cost/acre L cost/acre Tax/acre Total cost/acre Total Rev/acre Net Rev/acre Where JSCH= Watercourse head at Joe Sheikh Canal, KRCH= Watercourse head at Kabul River Canal, NP1 = Normal plough, SB = seed bed preparation, DAP/NP = Di Ammonium Phosphate/Nitrophos, FYM = Farmyard Manure, Hoe = Hoeing, Hr = Harvesting, Coll = collection, CFFMr = Cost from field to market, Irr = Irrigation, L = Loading Table: 4 Yield Cost and Revenue of Sugarcane at Mid Areas of JSC and KRC JSC M KRC M Overall Yield/acre Cost Of Prod Npl cost/acre SB cost/acre Seed cost/acre Urea cost/acre

11 DAP/NP cost FYM cost/acre Hoe cost/acre Hr cost/acre Coll cost/acre CFFMr/acre Irr cost/acre L cost/acre Tax/acre Total cost/acre Total Rev/acre Net Rev/acre Where JSCM= Watercourse mid at Joe Sheikh Canal, KRCM= Watercourse mid at Kabul River Canal, NP1 = Normal plough, SB = seed bed preparation, DAP/NP = Di Ammonium Phosphate/Nitrophos, FYM = Farmyard Manure, Hoe = Hoeing, Hr = Harvesting, Coll = collection, CFFMr = Cost from field to market, Irr = Irrigation, L = Loading Table: 5 Yield Cost and Revenue of Sugarcane at Tail Areas of JSC and KRC JSC T KRC T Overall Yield/acre Cost Of Prod 130

12 Npl cost/acre SB cost/acre Seed cost/acre Urea cost/acre DAP/NP cost FYM cost/acre Hoe cost/acre Hr cost/acre Coll cost/acre CFFMr/acre Irr cost/acre L cost/acre Tax/acre Total cost/acre Total Rev/acre Net Rev/acre Where JSCT= Watercourse tail at Joe Sheikh Canal, KRCT= Watercourse tail at Kabul River Canal, NP1 = Normal plough, SB = seed bed preparation, DAP/NP = Di Ammonium Phosphate/Nitrophos, FYM = Farmyard Manure, Hoe = Hoeing, Hr = Harvesting, Coll = collection, CFFMr = Cost from field to market, Irr = Irrigation, L = Loading. 131

13 Comparing Yields, Costs and Revenues of Sugarcane Across Head, Mid and Tail Locations Using Dummy-Variable Econometrics Techniques In order to see whether yields, costs and revenues of sugarcane crops differ across head, mid and tail locations and the differences are statistically significant, we used the dummy-variable econometrics approach, specified in 3.1. The empirical results are given and discussed in the following paragraphs. Yield The empirical results of an overall case, where both watercourses have been taken as a single case, are provided, as follows. Y = DM 41.14DT (273.2) (-6.45) (-14.49) (4.1) The estimated model (4.1) reflects that yields of sugarcane crop at mid and tail are and mounds less than yields at the head locations, where the average yield is maunds per acre. The results further reflect that differences in yields are statistically significant. When yields at JSC and KRC watercourses are separately taken, the results differ slightly, but trends remain almost the same. Y (JSC) = DM DT (133.36) (-5.02) (-9.74) (4.2) Y (KRC) = DM DT (198.1) (-4.38) (-10.97) (4.3) Net Revenue The empirical results of the same model tried to differentiate net revenue (profit) across head, mid and tail locations are provided, as follows. 132

14 NR = DM DT (44.4) (1.63) (1.84) (4.4) It appears that net revenues to the growers are Rs per acre at head in an overall case, and are higher by Rs and Rs per acre over the mid and tail locations, respectively. The position in case of the two watercourses under study is as follows. NR (JSC) = DM + 92DT (23.00) (0.064) (0.134) (4.5) NR (KRC) = DM DT (41.00) (0.08) (0.288) (4.6) Net revenue at both JSC and KRC mid and tail locations are higher than that of head, and also seem increasing when one travels along head-to-tail location; however, the differences are not statistically significant. The results given in 4.1 through 4.3 indicate that yields of sugarcane crop along watercourses from head-to-tail decrease in an overall, as well as, in the two cases of watercourses, if taken separately, while net revenue adopt opposite direction (4.4 through 4.6), that is, these increase along the way from head-to-tail. The increase in net revenue, in spite of the decreases in yield per acre, may occur due either to the relatively high prices or low cost or both. Hence, we need to analyze what happens to prices and costs while traveling along the watercourses from head-to-tail. Price As reflects from 4.7 through 4.9, prices enhance all along from head-to-tail directions on the two watercourses, in both an overall and separately dealt cases. P = DM DT (28.91) (2.54) (8.83) (4.7) P (JSC) = DM + 25DT 133

15 (17.13) (2.47) (7.28) (4.8) P (KRC) = DM DT (65.42) (3.61) (17.21) (4.9) It should be noted that increases in sugarcane price along the watercourses are statistically significant. A graphical analysis of prices and yields, carried out for an overall case in Figure I, reflects the same pattern. Cost C = DM DT (71.4) (-4.74) (-1.80) (4.10) C (JSC) = DM 1864DT (42.00) (-2.88) (-6.34) (4.11) C (KRC) = DM DT (52.80) (-2.97) (-7.19) (4.12) The costs differentiated over the head, mid and tail locations through models given in 4.10 through 4.12 reveal that costs reduce along head-to-tail and reductions occurred are statistically significant. These reductions occur in an overall case as well as in the two watercourses cases. Sugarcane Production and its Determining Factors The empirical results of the dummy-variable models discussed above indicate that net revenues (profits) from sugarcane production along watercourses from head-to-tail increase; however, the increase in net revenues are not due to higher yields, but are due to higher prices and lower costs of production along head-to-tail direction. Lowered cost of production may be due to low use of required inputs, which further reduce the yields in mid and tail areas. However, before going in to detailed analysis of cost and 134

16 production components, we first apply another econometrics technique to reconfirm that yields and costs decrease when one proceed along head-to-tail direction. Y = t (113.40) (-0.24) (4.13) C = t (25.13) (-0.14) (4.14) The estimated models 4.13 and 4.14 are, in fact, trend-variable econometrics models, wherein trend variable t has been used to capture whether yields and cost of each successive farmer along head-to-tail decrease or increase. The results reinforce our earlier findings that both yields and costs decrease, however, the decreases in both the cases have now been turned out to be statistically non-significant (on the basis of t-ratios). Determination of Yield In order to identify the major contributory factors towards yields, we tried the following econometrics models Y = FU LU OC (0.13) (3.13) (2.57) (4.24) R 2 = 0.61 F calculated = 31.7 (4.15) Y (JSC) = FU LU AOC (-0.08) (2.57) (2.41) (2.82) R 2 = 0.63 F calculated = (4.16) Y (KRC) = FU LU AOC (-1.61) (1.74) (1.44) (4.31) 135

17 R 2 = 0.72 F calculated = 2.88 (4.17) Models 4.15 through 4.17 attempts to identify and capture the effects of major determinants of production/yields per acre of sugarcane. Amongst the three major explanatory variables tried {namely fertilizer used (FU), labor days employed (LU) and costs incurred on all other inputs (AOC)}, all have been turned out to be statistically significant contributory factors. Results suggest that an additional labor-day employed contributes additional 2.24 mounds to the yield per acre, followed by 0.44 mounds and 0.32 mounds additional yields per acre contributed, respectively, by an additional rupee spent on other inputs and an additional kg of fertilizer used. About similar results are obtained in case of JSC; however, KRC exhibits somewhat different results. In KRC case, expenditure on other items seems to exert statistically more strong results than the two other explanatory variables included. Determination of Cost of Production Major important inputs like fertilizers (F), Farm yard manure (FYM), seed (S) and labor (L) along with expenses on all other items were used as explanatory variables an econometrically estimated cost of production function; the results are provided, as follows. C = F FYM L S Others (0.74) (4.28) (0.96) (2.97) (5.91) (4.70) R 2 = 0.81 F calculated = 52.8 (4.18) C (JSC) = F FYM L S Others (1.24) (3.51) (0.68) (0.004) (1.86) (2.84) R 2 = 0.57 F calculated = 8.34 (4.19) C (KRC) = F FYM L S Others (1.86) (7.34) (2.28) (12.35) (24.7) (6.65) R 2 = 0.89 F calculated = 532 (4.20) Cost of production of sugarcane seems to be statistically significantly determined by fertilizers, labor, seed and other items and non-significantly by farm yard manure, in an 136

18 overall case. Farm yard manure appears significant contributory factor only in case of KRC. All the included explanatory variables appear statistically significant in determining cost of production in KRC watercourses commanded areas. In case of JSC watercourses, farm yard manure and labor remain insignificant. SUMMARY, CONCLUSION AND RECOMMENDATIONS This chapter deals with the summary of the results, conclusions drawn and recommendations framed for general implementation. There are three different sections; the first present summary of the findings, the second conclusions drawn and the third the recommendations framed. Summary of Findings 1. On average, the yield per acre of sugarcane crop estimates at 451 mounds; while it is 453 mounds and 450 mounds per acre at KRC watercourses and JSC watercourses commanded areas, respectively. Head and mid of the JSC watercourse gives higher yields than that of KRC watercourse. While at tail, KRC watercourse exceeds JSC watercourse, where per acre yield is 443 and 432 mounds per acre, respectively. 2. A comparison of cost per acre shows that costs at KRC watercourse (Rs. 9986) are slightly higher than JSC watercourse commanded areas (Rs.9606). Costs at head and tail of KRC watercourse are Rs and Rs.8746 against Rs and Rs.7912, respectively, at JSC watercourse. 3. Gross revenues at head and mid of Joe Sheikh Canal are Rs and Rs per acre, respectively, and are higher than that of Kabul River Canal (Rs and Rs.22830). At tail, Kabul River Canal s total revenue (Rs.22945) exceeds that of Joe Sheikh Canal (Rs.21686). 4. Net revenues at the head, mid and tail locations of KRC watercourse are Rs.12202, and 14198, respectively, against Rs.13455, and of that of JSC. The overall average net revenues at head, mid and tail have been Rs.12530, Rs and Rs per acre. 5. The dummy variable econometrics techniques used to differentiate yields, cost, prices and net revenues across head, mid and tail locations helped analyzed that yields of sugarcane crop at mid and tail were and mounds lower than yields at the head locations, where the average yield was 471 mounds per acre. The results further reflect that differences in yields were statistically significant. When yields at JSC and KRC 137

19 watercourses were separately taken, the results differed slightly, but trends remained almost the same. Net revenues were Rs per acre at head in an overall case, and were higher by Rs and Rs per acre over the mid and tail locations, respectively. Net profits at both JSC and KRC mid and tail locations were also higher than that of head. It appeared that yields of sugarcane crop along watercourses from headto-tail decrease in an overall, as well as, in the two cases of watercourses, if taken separately, while net profits adopt opposite direction, that is, these increase along the way from head-to-tail. 6. The increases in net revenues, in spite of the decreases in yields per acre, occurred due to the relatively high prices and low cost at mid and tail areas. Prices were found higher at lower areas (mid and tail of watercourses) and differences were quite significant statistically. Costs were found lowered at lower locations and reductions were statistically significant. Such reductions occurred in an overall case, as well as, in the two watercourses under study. 7. Amongst the three major explanatory variables tried {namely fertilizer used (FU). Labor days employed (LU) and costs incurred on all other inputs (AOC)}, all were turned out to be statistically significant contributory factors towards yields per acre in an overall case. About similar results were obtained in case of JSC; however, KRC exhibited somewhat different results. In KRC case, expenditure on other items seemed to exert statistically more strong results than the two other explanatory variables included. 8. Major important inputs like fertilizers (F), farm yard manure (FYM), seed (S) and labor (L) along with expenses on all other items were tried to explain costs of production. Cost of Production of sugarcane seemed to be statistically significantly determined by fertilizers, labor, seed and other items and non-significantly by farm yard manure, in an overall case. Farm yard manure appeared significant contributory factor only in case of KRC. All the included explanatory variables appeared statistically significant in determining cost of production in KRC watercourses commanded area. In case of JSC watercourse, farm yard manure and labor remain insignificant. 138

20 Conclusions On the basis of above discussion, it is concluded that net revenue from sugarcane production increase along watercourses from head-to-tail; however, the increases in net revenues are not due to higher yields, but are due to higher prices and lower costs of production along head-totail direction. It is further concluded that yields per unit areas decreased along head-to-tail of the watercourses. Fertilizers, labor days employed and costs incurred on all other inputs seem to determine yields. However, KRC exhibits somewhat different results, where items/factors other-than-fertilizers and mandays seem to exert statistically more strong results than the two other explanatory variables included. Recommendations 1. Efforts to increase yields of sugarcane per unit area should be carried out, with special emphasis on mid and tail sections of the watercourse. 2. Improved infra structure and proper marketing facilities need to be provided for reducing cost. 3. Proper management and even distribution of irrigation water should be ensured for enhancing yield. 4. This type of research should be replicated in other areas to ascertain and find out whether the findings that yields become lower at lowered terraces along watercourses are universally valid or are specific to the KRC-plus-JRC area studied. 139

21 References Ahmad Z., S.Khan, S. Rehman and G. Ahmad (1995) Effect of nitrogen levels and setts density on various agronomic characteristics of sugarcane Pakistan Sugar Journal. Shakarganj Mills Ltd., Toba Tek Sing Road, Jhang Pakistan. 9(3): Ali F. G., A. Mahboob, M. Saeed, and A. Shahid (2001). Bio-mass production and its partitioning in sugarcane under different moisture regimes and fertilizer levels Pakistan Sugar Journal Shakarganj Mills Ltd., Toba Tek Sing Road, Jhang Pakhistan 16(4): Aslam Javed M., K. Abdullah, K. Imtiaz Ahmed, M. Ashraf, M. Aquil Siddiqui, D. Nazir Ahmed, M. Hussain Khanzada, and K. Raziullah (2000). Prospects of enhancement of cane yield and sugar recovery of sugarcane crop in Pakistan Shakargank Sugar Research Institute, Jhang, Pakhistan. 15 (6): Damodar, N. G. (1995). Regression on Dummy Variables Basic Econometrics, Third Edition, Chapter -15, P-499 Faqir Gulzar A., C. Arshad Ali, and M. Awaz Iqbal (2000) Improvement of cane Yield and quality by proper harvest schedule Workshop proceedings R & D activities on sugarcane crop in Pakistan Shakargank Sugar Research Institute, Jhang, Pakhistan. 15 (6): Govt of Pakistan (1999) Area and Production of sugarcane in Pakistan Agricultural Statistics of Pakistan Ministry of Food, Agriculture and Livestock Islamabad P.28 Government of Pakistan (2000) Agriculture Statistics of Pakistan Government of Pakistan, Ministry of Food, Agriculture and Livestock Division (Economic wing), Islamabad Imran M, A. Shaukt M. Ilyas A. Ishtiaq I, Muhammad, S. Ayaz, I. Muhammad, and I. Ahmad (2000) A glance at the agro economic study of sugar intercropping with three other crop Pakistan Sugar Journal. Shakarganj Mills Ltd. Toba Tek Sing Road, Jhang Pakistan 15(1): Malik N.A. (1993) Response of Sugarcane cultivar to different doses of NPK fertilizer in Somalia Pakistan Sugar Journal. 140