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a Institut de l'Environnement et de Recherches Agricoles (INERA), 04 BP 8645, Ouagadougou 04, Burkina Faso
b West Africa Rice Development Association (WARDA), BP 96 St. Louis, Senegal (current address: International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines)
c An International Center for Soil Fertility and Agricultural Development (IFDC)–Africa Division, BP 4483, Lomé, Togo
d Université de Ouagadougou (UO), 03 BP 7021 Ouagadougou 03, Burkina Faso
* Corresponding author (zacharie.segda{at}messrs.gov.bf)
Received for publication November 14, 2004.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Abbreviations: AFR, alternative fertilizer recommendations • DS, dry season • EFR, existing fertilizer recommendations • FP, farmers' practice in terms of fertilizer use • IKS, indigenous soil potassium supply • INS, indigenous soil nitrogen supply • IPS, indigenous soil phosphorus supply • IS, indigenous soil nutrient supply • RF, recovery fraction of applied fertilizer nutrients • TFC, total fertilizer cost • WS, wet season • Ypot, yield potential
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Segda et al. (2004) conducted an agroeconomic characterization study in one of the most important rice irrigated schemes in eastern Burkina Faso (Bagré irrigation scheme) where development of irrigation is ongoing. The analysis found agronomic constraints similar to the situation in other schemes of the region. Farmers' net benefits to irrigated rice cropping were mostly positive in the dry season (DS) but often low or even negative in the wet season (WS). Yield gaps between average farmers' yield and best farmers' yield were high and indicated considerable scope for yield and profit increases in both seasons. The observed medium to low average yields are far below the level anticipated by authorities and irrigation scheme planners. Limited productivity combined with high input prices cause low profit margins, which subsequently reduce savings for maintenance of infrastructure and machines and the reimbursement of credit. At current productivity levels, the economic viability of the irrigation schemes in the Sahel can be questioned (Bélières et al., 1997). Productivity increases are necessary to maintain the economic sustainability of irrigated agriculture in the region.
Based on the agroeconomic characterization study, Segda et al. (2004) concluded that the most promising ways to achieve higher productivity and input use efficiency are (i) to improve timing and quality of crop management practices and (ii) to improve existing fertilizer recommendations (EFR). Fertilizer recommendations in Burkina Faso have not changed since introduction of irrigated rice and are presently uniform over large areas and cut across diverse climatic and edaphic environments. Especially the widespread use of compound fertilizers, not tailored to the needs of the rice crop, constitutes an obstacle for optimization of nutrient management. Other factors included problems with collective and individual planning of the cropping calendar for double cropping of rice (two rice crops on the same field per year) and the need to also attend to rainfed crops outside the scheme.
To improve existing crop and nutrient management recommendations and practices, an integrated approach is vital, taking the farmers' socioeconomic as well as biophysical environment into account. Nutrient management for rice should focus on developing fertilizer recommendations for spatial domains with relatively uniform agroecological characteristics, cropping practices, and socioeconomic conditions (Dobermann et al., 2002, 2003a, 2003b). To reach that goal with agronomic trials is rather costly and time-consuming, and simulation tools are increasingly used as a complement (Smaling, 1993). The present study used a framework for improved soil fertility management presented by Haefele et al. (2003b). This approach combines field data with simulation tools in a flexible framework. It helps the user to diagnose limiting factors as well as to develop soil fertility management strategies as a function of his or her goals, e.g., profit maximization, yield maximization, or risk minimization, given biophysical and socioeconomic settings.
This study intended to: (i) estimate climatic risk in Bagré for the two rice growing seasons and for different crop establishment modes and dates, (ii) develop agroeconomically sound fertilizer recommendations for a range of target yields using the framework presented by Haefele et al. (2003b), and (iii) evaluate such model-based alternative recommendations in farmers' fields.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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The climate is typical for the agroecological zone of the Sudan Savannah with average rainfall of 900 mm yr–1 in the WS from July to October, followed by a cold DS in November to February and a hot DS from March to June. Minimum air temperatures below 15°C occur in the cold DS, and maximum air temperatures above 40°C occur in the hot DS.
Irrigation for the Bagré scheme is gravity driven and is supplied from the Nakambe River (formerly White Volta). Cultivation of the first irrigation scheme started in 1997, in which the present study was conducted (Nimatoulaye scheme or V1, with a total area of 106 ha). The main crop is irrigated rice, which is cultivated in the WS (main sowing time from July to August) and the hot DS (main sowing time from January to February). Almost 100% of the irrigated area is cropped twice a year. Direct seeding and transplanting are both practiced. Existing fertilizer recommendations are 300 kg ha–1 "cotton fertilizer" (N–P2O5–K2O, 12–24–12) applied basally or shortly after transplanting and 100 kg ha–1 urea (46–0–0) in the WS or 150 kg ha–1 urea in the DS. Recommended total NPK dose therefore is 82–31–30 kg ha–1 and 105–31–30 kg ha–1 in the WS and DS, respectively. Urea is recommended to be topdressed in two equal splits at early tillering and panicle initiation. Dominating cultivars are FKR19 (TOX 728-1) and FKR14 (4418). Apart from irrigated rice, most farmers grow rainfed maize (Zea mays L.), millet [Pennisetum glaucum (L.) R. Br.], or sorghum [Sorghum bicolor (L.) Moench] in the surroundings of the scheme during the WS, and some farmers grow vegetables during the DS. Most farmers also have some livestock (cattle).
Simulation Tools
Two simulation tools were used to develop AFR. The rice phenology model RIDEV (Dingkuhn, 1997) assists in the optimal timing of crop management interventions, and a modified version of QUEFTS (Janssen et al., 1990) called FERRIZ is used to calculate N, P, and K doses for specific target yields. The framework and the simulation tool FERRIZ are described in detail by Haefele et al. (2003b). A short description of the models is given below.
RIDEV
The rice phenology model RIDEV (Rice Development) was developed by Dingkuhn (1997). It provides a time axis from germination to maturity depending on daily minimum and maximum temperatures and varietal constants. Furthermore, the percentage of spikelet sterility resulting from extreme temperatures can be estimated. Inputs for the model are daily minimum and maximum air temperature, photothermal constants of the cultivar used, sowing date, and establishment method (transplanting or direct seedling). The model was developed and validated for Sahel and Sudan Savannah regions and repeatedly used to analyze and improve farmers' crop management practices (e.g., Wopereis et al., 2003).
Actual weather data from the survey site were not available. Historical data (1969–1978) from the closest weather station (Fada N'Gourma, 12°05' N, 0°26' E; located at about 75 km from Bagré) were used for the simulations. Photo-thermal constants were chosen from a cultivar similar to the one mainly used by farmers (i.e., short duration cultivar IR13240-108-2-2-3 which resembles farmers' cultivar TOX 728-1).
FERRIZ
The model FERRIZ (Haefele et al., 2003b) is a modified version of the empiric and static model QUEFTS (Janssen et al., 1990). It can be used to estimate rice yields based on indigenous soil nutrient supply (IS) and potential yield (FERRIZ_Y) or to calculate N, P, and K doses for specific target yields depending on IS and potential yield (FERRIZ_F).
Potential yield can be estimated using simulation models, like the ORYZAS model (Dingkuhn and Sow, 1997) as proposed by Haefele et al. (2003b), or estimated from best farmer yields or from yields obtained at research stations under high-input conditions and optimal crop management. In our case, the ORYZAS model could not be used due to missing weather data on solar radiation. Dingkuhn and Sow (1997) observed a relationship between simulated potential grain yield (Ypot at 14% moisture) and geographical latitude separately for the DS and WS. Following that relationship, we estimated that average Ypot for sowing in February (DS) is about 9 t ha–1, and average Ypot for sowing in July (WS) is about 8 t ha–1.
Parameters for maximum dilution and maximum accumulation of rice N, P, and K uptake were included according to Witt et al. (1999) and Haefele et al. (2003a). Using data from farmers' surveys conducted under a wide range of environmental and crop management conditions, both studies defined borderlines of maximum dilution (d) and accumulation (a) of nutrients in modern rice cultivars as follows: aN = 42 kg paddy kg–1 N uptake and dN = 96 kg paddy kg–1 N uptake, aP = 206 kg paddy kg–1 P uptake and dP = 622 kg paddy kg–1 P uptake, and aK = 36 kg paddy kg–1 K uptake and dK = 115 kg paddy kg–1 K uptake.
Recovery fractions (RF) are defined as the amount of fertilizer nutrient taken up by the crop divided by the amount of fertilizer applied. In all FERRIZ_F simulations for the calculation of fertilizer doses, RF of N was set to 0.45 kg kg–1, RF of P was set to 0.25 kg kg–1, and RF of K was set at 0.45 kg kg–1. These values represent average values observed in various field surveys (e.g., Witt and Dobermann, 2001; Haefele, 2001).
Indigenous soil N, P, and K supplies and responses to N, P, and K fertilizer application were determined using a fertilizer trial conducted in a farmer's field in the Nimatoulaye irrigation scheme during the 1999 DS (February sowing) and the 1999 WS (July sowing). Experimental treatments were chosen to provide optimal concentrations of two elements, whereas the remaining element was increased stepwise (Table 1). A randomized complete block design with four replications and 13 different treatments was installed. Each subplot had a size of 6 by 4 m. The short-duration cultivar FKR14 (4418) was used and transplanted at a density of 25 hills m–2. Fertilizer treatments were applied to the same plots in both seasons in a continuous rice–double cropping system. Nitrogen was applied as urea (46% N), P as triple superphosphate (20% P), and K as KCl (50% K). Phosphorus and K were broadcast with the first N application (14 d after transplanting). The remaining two N splits were applied at panicle initiation and heading with doses according to Table 1. Grain yield was determined from a 6-m2 area in the center of each subplot. Grain moisture content at harvest was determined with the Kett grain moisture tester Riceter J.P. Results from this trial were used to estimate nutrient (N, P, and K) uptake in the subplots without N (0N subplot), without P (0P subplot), and without K (0K subplot) from DS grain yield at 3% moisture, using conversion factors determined by Dobermann et al. (2003a)(2003b). The conversion factor for N is 13.4 kg of N per 1000 kg of grain yield, the conversion factor for P is 2.9 kg P per 1000 kg of grain yield, and the conversion factor for K is 15.8 kg of K per 1000 kg of grain yield. Such estimates have a precision of about ±5 to 10 kg N ha–1, ±2 to 3 kg P ha–1, and ±10 to 20 kg K ha–1 (Dobermann et al., 2003a, 2003b). The N uptake thus calculated in the 0N omission plot was considered a proxy for the indigenous soil supply of N (INS), the P uptake calculated for the 0P plot was considered a proxy for the indigenous soil supply of P (IPS), and the K uptake calculated for the 0K plot was considered a proxy for the indigenous soil supply of K (IKS).
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FERRIZ_F was used to calculate fertilizer doses for target yields ranging from 6.0 to 8.0 t ha–1 in 0.5 t ha–1 intervals in the DS (Ypot = 9.0 t ha–1) and from 5.0 to 7.0 t ha–1 in the WS (Ypot = 8.0 t ha–1). Total N, P, and K uptake at harvest were estimated as well. Fertilizer costs were based on average prices for the 2003 and 2004 WS and DS of the most commonly applied fertilizers in the Bagré plain, i.e., urea (FCFA 247 kg–1, containing 46% N) and "cotton fertilizer" (FCFA 257 kg–1, containing 12% N, 10.5% P, and 10% K). The paddy price depends on the milling recovery rate, and the producers of Bagré achieved an average price of FCFA 101 per kg of paddy over the four growing seasons in 2003 and 2004. The average exchange rate of the West African currency FCFA to the U.S. dollar in the period 1 January 2003 to 31 December 2004 was US$ 1.00 = FCFA 554.
The outcome of the FERRIZ_F simulations allowed the development of AFR. FERRIZ_Y was then used to estimate yields and yield differences that can be expected from EFR and from the AFR in both WS and DS.
Validation Trials
Three fertilizer treatments were tested with seven farmers in the 2003 DS (February sowing), 14 farmers in the 2003 WS (July sowing), 17 farmers in the 2004 DS (February sowing), and 12 farmers in the 2004 WS (July sowing):
Farmers typically used short-duration rice cultivar TOX 728-1, or similar short-stature, high-yielding cultivars. In each rice field (typically about 1 ha in size), three subplots of 10 by 10 m were installed to evaluate AFR, EFR, and FP. For AFR and EFR, all management practices were left to the farmer, except fertilizer applications. For FP, all management practices, including fertilization, were left to the farmer. At maturity, rice yields were obtained from a 6-m2 surface area in the center of each subplot, and yields were corrected for 14% moisture. Profit margins from fertilizer use were determined for each treatment using prices for each season. Paddy rice price was FCFA 102 kg–1 during the 2003 DS and 2003 WS, FCFA 87 kg–1 during the 2004 DS, and FCFA 111 kg–1 during the 2004 WS. Urea price was FCFA 237 kg–1 during the 2003 DS, FCFA 230 kg–1 during the 2003 WS, and FCFA 260 kg–1 in 2004. The complex cotton fertilizer price was FCFA 237 kg–1 during the 2003 DS, FCFA 250 kg–1 during the 2003 WS, and FCFA 270 kg–1 in 2004.
Financial calculations were made on a per-crop basis following Dobermann et al. (2002) using FCFA as standard currency:
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The incremental profitability of AFR (dGRF) was determined as the difference in gross returns above fertilizer costs between AFR and FP and between AFR and EFR:
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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RIDEV Simulations
Table 2 shows optimal practices according to RIDEV for rice cultivar TOX 728-1. Mean values for simulations conducted at 7-d intervals over a period of 10 yr are presented. The simulations address the dominant crop establishment techniques in each season, which are direct seeding in the DS and transplanting in the WS (Segda et al., 2004). The table shows best timing of crop management interventions as a function of sowing date (or transplanting) and indicates the risk of temperature-induced yield losses. Transplanting after 3 August must be avoided. Assuming a preparation phase of about one month for the WS and a DS crop duration of 120 d, the DS crop should be established by mid-February latest to avoid dangerous delays of the onset of the WS. The WS crop could then be harvested beginning of December.
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For the same target yield, higher fertilizer doses have to be applied when Ypot is lower (Table 3). For high target yields, N, P, and K have to be applied, whereas only N application is needed for low target yields. For optimal profit (marginal rate of return = 0), up to FCFA 135000 must be invested in fertilizer in the DS, which is above the investment made by most farmers. According to the field survey, farmers in Bagré spend on average FCFA 95000 (maximum FCFA 125000) for total fertilizer costs (Segda et al., 2004). The comparison of applied N, P, and K and aboveground plant uptake at the target yield indicates negative P and K balances for all simulation scenarios when complete grain and straw removal is assumed (Table 3).
The outcome of the FERRIZ_F simulations illustrates the importance of N fertilizer as compared with P and K in Bagré. Alternative fertilizer recommendations were then derived based on estimated yield, NPK balance, costs, and simplicity. We decided to reduce the NPK fertilizer dose as compared with EFR by 100 kg ha–1 and to increase the urea dose by 100 kg ha–1. This does not entail increased costs but gives extra weight to N as compared with P and K.
Alternative fertilizer recommendations, therefore, were defined as 116 kg N ha–1, 21 kg P ha–1, and 20 kg K ha–1 for the WS and 139 kg N ha–1, 21 kg P ha–1, and 20 kg K ha–1 for the DS.
To compare the performance of the AFR versus the EFR, FERRIZ_Y was used to simulate yield and plant uptake with the same input data as above. Simulation results are given in Table 4. Existing fertilizer recommendations differ for the DS and WS (105 kg N ha–1, 31 kg P ha–1, and 30 kg K ha–1 in the DS and 82 kg N ha–1, 31 kg P ha–1, and 30 kg K ha–1 in the WS), assuming a lower Ypot in the WS, but reduce only the N dose. Simulated yields with the higher dose were about 6.5 t ha–1, whereas the lower dose resulted in yield estimates of about 6.0 t ha–1. Nitrogen and P uptake were always below the applied amount, whereas K uptake was more than three times higher.
Alternative fertilizer recommendations increased estimated yields by 0.4 to 0.5 t ha–1 as compared with EFR. The balance between nutrients applied and plant uptake became more positive for N, balanced for P, and even more negative for K. Simulations were also conducted for DS growing conditions, using the AFR developed for the WS; as farmers were reluctant to accept the "high" AFR doses, they preferred to use AFR developed for the WS for both seasons (see below). In this case, AFR yields were comparable to EFR yields, but at substantially lower costs.
Validation Experiments
The performance of EFR and AFR and farmers' practice were compared during the DS and WS of 2003 and 2004 (Table 5). Farmers decided to test only the AFR developed for the WS in both seasons; AFR developed for the DS were considered not within financial reach of most farmers. The amount of fertilizer applied by the farmers themselves was indeed considerably lower than AFR and EFR rates. Farmers applied about 80 kg N ha–1, 16 kg P ha–1, and 16 kg K ha–1, but there was a large variability among farmers in terms of timing and dosage used (details not shown). Total fertilizer cost was about 30000 FCFA ha–1 higher for AFR as compared with FP. Total fertilizer cost for AFR was substantially lower than EFR in the DS and about the same in the WS. Gross returns above fertilizer cost were most interesting for AFR, with differences between AFR and EFR ranging from 54600 to 111700 FCFA per season and those between AFR and FP ranging from 34400 to 147300 FCFA per season. Over the four seasons, EFR increased gross returns above fertilizer costs by an average of about FCFA 90000 or about US$ 160 per season as compared with both farmers' practice and actual recommendations.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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The fertilizer trial used in this study was conducted in a farmer's field, thereby reflecting the influence of farmer crop management practices on soil fertility. Significant fertilizer responses were only observed for N and P (Fig. 1). Clear yield increases due to N and P application and no or little effects of K application were observed repeatedly in several irrigation schemes in the West African Sahel and Savanna regions (Wopereis et al., 1999; Haefele, 2001; Haefele et al., 2003b). Buri et al. (1999) reported high soil K levels for most flood plains in the same region. Considerable soil K reserves and little effect of farmer's fertilizer management (largely without K application) on extractable soil K in a Sahelian flood plain were shown by Haefele (2001). Highest yields in the trial were achieved with 120 kg N ha–1 and 39 kg P ha–1 in the DS and 120 kg N ha–1 and 26 kg P ha–1 in the WS.
Based on the NPK omission plots in the trial and empirical factors for NPK uptake in such plots (Dobermann et al., 2003b), IS for NPK was estimated. Indigenous N supply estimated for the trial site was very close to the average INS measured in the 1999–2000 survey for farmers' fields (Segda et al., 2004). No survey measurements for IPS and IKS were available.
Estimates of IS for N, P, and K and other input parameters (potential yield, fertilizer recovery fractions, and input prices) allowed to calculate economically optimal yields and determine fertilizer doses for specific target yields with FERRIZ_F (Table 3). The dominant N limitation is showing clearly in the simulations, but they also indicate that at current IS levels, no P or K application would be necessary up to target yields of 6.5 t ha–1. Such a strategy would be highly beneficial in the short term (low costs and high target yield), but comparison of nutrient input and plant uptake shows that this would result in negative P and K balances.
Knowing the low soil P reserves and their rapid depletion in West African flood plains (Buri et al., 1999; Haefele et al., 2004), a balance between P application and plant uptake was targeted for the site-specific nutrient management recommendations (Table 3). In comparison with existing recommendations, this can be achieved with lower compound fertilizer doses, allowing an increased N dose at identical cost levels.
A relative increase of N was repeatedly recommended and successfully tested in West African irrigated rice-based systems (Wopereis et al., 1999; Donovan et al., 1999; Haefele et al., 2000, 2002), and the simulations show that this strategy increases profits over the existing recommendation, especially at higher Ypot. The simulations also show that mainly N needs to be adjusted to Ypot, whereas P and K doses can be maintained stable. This opens the way to real-time N management strategies. Adjustment of N doses to rice crop appearance (i.e., leaf color chart) was successfully tested in Asia (Balasubramaniam et al., 1999) and has high potential in African environments too. Even though the compound fertilizer dose was reduced, the P dose is still high and close to the dose achieving optimal responses in the fertilizer trial (Fig. 1).
As average farmers' yield increases from the current level of about 3.6 (WS) to 4.9 (DS) t ha–1 to the simulated yield of 6.5 to 6.9 t ha–1, actual P balances will still remain positive. The K balance based on K input and plant K uptake became more negative as compared with the existing recommendation, but it assumes complete straw removal, no other K inputs, and average yields close to 6.5 to 6.9 t ha–1. Considerable K inputs can be expected from dust deposition (Hermann, 1996), and remaining stubbles as well as straw application (in the form of compost or manure) can reduce the negative balance considerably. Together with the high soil K reserves discussed above and the current absence of K response, a strategy of slow soil K mining seems more adequate than a soil K maintenance strategy. Saving the investment for soil K maintenance in the near future might help African rice farmers to compete better with cheap imports. Higher K doses would become adequate when K responses can be observed and when farmers reach a higher productivity level.
The simulated yield and profitability gains were more than confirmed in farmers' fields during four consecutive growing seasons. In all seasons, AFR yields were considerably higher than EFR or FP yields, and yield gains were significant (p < 0.05) in 2004 (Table 5). Yield gains from AFR were larger than simulated, probably because for AFR, fertilizer N was applied in three splits, ensuring better balanced crop nutrition as compared with farmer practice and EFR where only two N splits were used. Similar results were obtained by Wopereis-Pura et al. (2002). Monitoring INS, IPS, and IKS every 5 to 10 yr with omission plots in farmers' fields as proposed by Dobermann et al. (2003a) and the framework presented here may serve to readjust AFR in the future.
Segda et al. (2004) found low economic returns to investment in fertilizer, particularly in the WS (Segda et al., 2004). It was concluded that suboptimal timing of crop management practices and suboptimal fertilizer management were the most important single factors contributing to the observed low efficiency. This is especially true for the WS sowing date as can be seen from Table 2. Relatively small delays in crop establishment can cause significant yield losses. Sowing after the first week in August increased the risk of cold sterility tremendously. The RIDEV simulation results were confirmed by the low yields of farmers with late sowing in the WS (Segda et al., 2004), and cold sterility due to late sowing date might be the main reason for low economic returns of many farmers in the WS. This confirms results reported by Nebié (1995), who set 15 August as a threshold date for transplanting. Without knowledge of these processes, it is extremely difficult for farmers to relate the occurrence of low minimum temperatures around panicle initiation with spikelet sterility. With a tight cropping calendar for rice double cropping and additional activities in surrounding rainfed fields, delays in establishment are easy to understand. Since such delays can have tremendous effects, farmers must understand the consequences of a late start in the WS to react adequately. The frequent occurrence of cold damage in the simulations over 10 yr indicate that in the case of a delay, not growing rice seems the better alternative. Spikelet sterility due to high daily maximum temperatures in the DS as reported from irrigated schemes further north (e.g., the Office du Niger in Mali; Dingkuhn and Sow, 1997) does not seem to be an important problem in the region. Nevertheless, farmers should establish the DS crop in January or mid-February latest since delayed start of the DS is in most cases directly related to a late start of the WS. RIDEV-derived recommendations on optimal timing of crop management practices during the season (Table 2) can further contribute to higher fertilizer efficiency and should be part of integrated crop management options. Such approaches were successful in similar rice-based systems in West Africa (Kebbeh and Miézan, 2003).
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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ACKNOWLEDGMENTS |
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