| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
a Lab. for Soil Sci. and Geol., P.O. Box 37, 6700 AA Wageningen, the Netherlands
b Inversiones Orlich S.A., San José, Costa Rica
* Corresponding author (jetse.stoorvogel{at}wur.nl).
Received for publication August 27, 2002.
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONSYSTEMS APPROACHESAPPLICATION OF PROTOTYPING IN...DISCUSSIONREFERENCES |
|---|
Abbreviations: NGO, nongovernmental organization • TCG, technical coefficient generator • YRU, yield registration unit
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONSYSTEMS APPROACHESAPPLICATION OF PROTOTYPING IN...DISCUSSIONREFERENCES |
|---|
The call for quantitative approaches has led to an increased use of simulation models. The models are, however, not able to address the integrated system and simulate only specific components of the system. Modeling results may be technically valid, but they are often not adopted because they do not fit into the overall socioeconomic setting (Lapar and Pandey, 1999; Batz et al., 1999; Abadi Ghadim and Pannell, 1999). On the other hand, farming systems research does fit into the socioeconomic setting, but does not, typically, include mechanistic simulation models and, as a result, is often location specific and descriptive (Dent and McGregor, 1994).
An alternative approach is to study the complete production system in close interaction with farmers. An example is presented by Vereijken (1997). He presents prototyping as an alternative to the more model-oriented and farming-systems approaches. Prototyping procedures have a participatory character in which scientists directly collaborate with farmers. Although the studies reported by Vereijken focus mainly on integrated and ecological arable farming systems, similar procedures are likely to be applicable to other production systems. Prototyping in cooperation with farmers has a number of clear advantages above straightforward science-driven research. Research will be directed to those issues (as identified by the farmer) that are most limiting at the farm level, and probably even more important, the complete system will be analyzed. In addition, continuous farmer participation is more likely to result in high adoption rates once innovative systems have been developed. The farms for which new systems have been developed will function as lighthouses in a region facilitating the adoption of new prototypes or parts of it to the region.
In this paper, we review the prototyping approach as a tool to develop new, sustainable agricultural systems or to adapt existing ones and compare it with more model-oriented approaches. For the sake of transparency and to structure the analysis, we follow four main pillars attributed to sustainable management (FAO, 1993): productivity, stability of production, soil and water quality, and socioeconomic feasibility. The productivity, both current and future, is the main objective for farmers. Off-farm effects are typically aspects that are only being considered when there is a certain level of environmental legislation. Although productivity plays a crucial role, we have to consider it in a socioeconomic context. Typically, farmers do not consider the different cropping systems on the farm in an isolated manner. Decisions will be taken at the farm level and imply continuous trade-offs between conflicting demands and objectives. The discussion is illustrated with a case study for the cultivation of banana (Gowen, 1995) in the northern Atlantic Zone of Costa Rica. The study focuses on a single plantation that was selected because the farmer was a forerunner and innovator in new developments.
|
SYSTEMS APPROACHES |
|---|
|
TOPABSTRACTINTRODUCTIONSYSTEMS APPROACHESAPPLICATION OF PROTOTYPING IN...DISCUSSIONREFERENCES |
|---|
As a result, we doubt whether crop growth simulation models should be used in an early phase of systems-oriented studies even though their important role in studying specific components of the system is acknowledged. Crop growth simulation models are, for example, successfully applied in decision support systems for agrotechnology transfer (Jones et al., 1998). The quantitative modeling approach is also applied to other components of the cropping system such as for pest management (Teng and Savary, 1992) and crop–weed interactions (Kropff and Lotz, 1992).
To solve part of the limitations of crop growth simulation models, TCGs are being developed (Hengsdijk et al., 1998, 1999; Habekotté, 1994). Technical coefficient generators are used as a model that integrates basic data on soils, crop protection agents, crop characteristics, and implements requirements for field operations by integrating simple calculation rules and explicit formulated assumptions in a spreadsheet format. Subsequently, the TCG generates technical coefficients describing the inputs and outputs of agricultural activities in an optimization model that optimizes the allocation of predefined agricultural activities in a region maximizing one or multiple goals, given a number of specific constraints. If sufficient survey and/or experimental data are available, the methodology can be applied for many more crops than the crop growth simulation models can handle, and the methodology can include many more processes. However, in many cases, the relations that are the backbone of the TCG are strictly empirical and do not allow for extrapolation to other areas.
Jansen and Schipper (1995) go a step further and argue that many of the relations in TCGs are not known. They advocate static descriptions of agricultural systems in terms of an array of input and output coefficients instead of more dynamic approaches (like crop growth simulation models and TCGs), which are not feasible due to lack of comprehensive crop or farm management models.
Analyses based on TCG or static descriptions have a number of serious constraints. The technical coefficients are limited to the characterization of actual management systems or minor adaptations of actual systems whereas completely different systems often materialize when prototyping procedures are followed. Such results are beyond the reach of TCGs.
Integrated Approaches
Bawden (1992) and Vereijken (1997) advocate an integrated approach toward agricultural research. Their analysis can be visualized applying the scheme of Hoosbeek and Bryant (1992) that will be illustrated later in this paper. They classify research procedures in a three-dimensional space where the vertical axis represents the spatial scale hierarchy, and in the horizontal plane, different research procedures are identified. Two perpendicular axes, one ranging from qualitative to quantitative and the other from empirical to mechanistic, describe the horizontal plane. Bouma and Hoosbeek (1996) define different knowledge levels within each plane thus obtained: K1, application of user expertise; K2, expert knowledge; K3, use of comprehensive statistical models; K4, complex, mechanistic models; and K5, detailed methods, including modeling, that focus on a single component of the system (often with a disciplinary character).
Many studies that resulted in low adoption rates were performed at the K3 through K5 levels without considering the K1 and K2 level. The difference with the studies of Brawden and Vereijken is that they include these other knowledge levels and, as a result, link up with the problems as the farmer experiences them. Integrated approaches move through the three-dimensional space as it is described above, applying tools at different knowledge and hierarchical levels. We refer to the combination of research procedures as research chains (e.g., Bouma and Droogers, 1999). For example, policymakers deal with a general environmental problem at the regional level induced by pesticide use and subsequent leaching to surface waters. They analyze the problem considering the K1 level. If they perceive the problem to be relevant, they may consult a number of experts who may have a look at the processes behind the problem and may even consider the implications for farmers (K2 level at the farm level). Subsequently, they may select a number of representative soil profiles and carry out detailed analyses using mechanistic simulation models (K5 level at the plot level). Finally, the results can be translated back to the policymaker at the regional level (K2 at the regional level).
A Proposal for the Implementation of Prototyping
Before starting the prototyping methodology, a farm or a limited number of farms needs to be selected. This selection process is key to the success of the prototyping exercise. The conditions on the farm need to be representative for a large enough group of farms. At the same time, the willingness of the farmer to participate in such a research endeavor is similarly important, and in this context, we look for specific types of farmers that are forerunners and play an important role in the farmer community.
The procedure for the implementation of prototyping includes four major steps:
The first step is based on a discussion among farmer, scientist, and possibly extension officers. This discussion forms the basis for a joint learning process that starts with the identification of research priorities and results in a rather descriptive and qualitative analysis of the production system at the K1/K2 level. This analysis may lead the identification of an array of specific problems in the production process. The discussion is always structured around the four pillars for sustainable management.
A second step deals with the identification and implementation of specific research activities at the knowledge levels that are considered relevant. This may include general monitoring of labor input for different activities at the K2 level but also detailed measurement on soil processes and the modeling of these processes at the K4/K5 levels. Research activities may be performed with a limited amount of feedback to the farm (depending on the knowledge level and character of the activity). However, all research output needs to be translated into a format that can be discussed with the farmer and fits within the scheme devised in the first step of the procedure.
The third step is again at the K1/K2 level to discuss research results with the farmer and extensionists and formulate possible changes in farm management. Depending on the outcomes, one may need to go back to Step 2 for additional research activities or one may decide to actually implement changes in farm management.
Research activities like the above can only be performed for one or a limited number of farms. At the end of the day, however, we deal with more general problems in a given area and the newly developed ideas included in the alternative prototypes for agricultural management need to be transferred to other farmers in the region. This fourth step can be difficult, but it can build on prior experience. Since the management alternatives have been developed in on-farm studies and in close cooperation with a farmer, the step to other farms is relatively small because farmers will adopt practices that they can identify with. However, one can wonder whether the prototype will function as a lighthouse by itself and spread technology as the lighthouse spreads light. In many cases, this process needs to be facilitated. Extension services from the private and public sector can play a key role here. On the other hand, the process can also be facilitated by organizing farmer's meetings where farmers get the opportunity to make critical comments and share their own experiences.
The rather abstract procedure, described above, will now specifically be illustrated for a Costa Rican banana plantation.
|
APPLICATION OF PROTOTYPING IN A COSTA RICAN BANANA PLANTATION |
|---|
|
TOPABSTRACTINTRODUCTIONSYSTEMS APPROACHESAPPLICATION OF PROTOTYPING IN...DISCUSSIONREFERENCES |
|---|
|
|
Productivity
Banana productivity is typically measured in boxes per hectare. Each box includes a minimum of 18.14 kg of fresh banana. The banana plantation produced 2719 boxes per hectare in 1996, which is far above the average for the plantations in the area of 2273 boxes per hectare per year (Sanchez and Zuñiga, 1999). Nevertheless, the farmer was convinced that production could be improved to more than 3000 boxes per hectare per year. However, this would require a constant record of the status of the plantation and its productivity. In Costa Rica, banana plantations comprise an intensive cable infrastructure for the transport of agricultural inputs and the harvest. Farmers use the word cable for the area for which the harvest is being transported via a particular physical cable. The plantation maintained an extensive record of productivity figures per cable that showed significant variation in productivity throughout the plantation. In addition, the database contained georeferenced data for chemical analysis of both soils and leaves and past management.
The high productivity levels in the banana plantations can only be maintained if nutrients taken up from the soil are replenished. Limited data are available on the soil nutrient balance under banana, and few fertilizer experiments have been performed. As a result, it is extremely difficult to establish good quantitative fertilizer recommendations. Corbana uses two general recommendations: one for the eastern side of the Atlantic Zone with volcanic ash soils and a separate one for the western side of the Atlantic Zone with soils of sedimentary origin (López and Espinoza, 2000).
Stability of Productivity
Banana plantations have been present in the Atlantic Zone since the construction of the railroad at the end of the 19th century (Soto, 1992). Management in the banana plantations changed significantly since then. Many plantations have been producing banana for more than 30 yr without presenting a negative effect on the production in the long run. The plantations in the south of Costa Rica are an exception—Cu toxicity occurred after the continuous application of Cu-based fungicides (Thrupp, 1988). Typically, soil organic matter contents are maintained, and soil structure is found to be favorable (especially if one would compare it with the compacted soil structure often found under pasture). However, the risk of soil nutrient depletion (including macro- and microelements) does exist and needs constant attention.
Soil and Water Quality
The continuous monoculture of banana is extremely vulnerable for burrowing nematodes like Radopholus similis (Robinson, 1996). If not controlled properly, nematode infestation leads to significant yield loss (Araya, 1995). Although research for biological control of nematodes shows some promise for the future, currently the only option for farmers to control nematodes is through the application of nematocides, which are often extremely toxic. In Costa Rica, nematocides are applied routinely in 4- or 6-mo cycles in a granular form applied near the plants' pseudostem. Available nematocides are alternated frequently to prevent rapid degradation by soil microflora or resistance buildup by the nematode (Gowen, 1995). The perhumid climate, with 3000 to 5000 mm of average annual rainfall, favors leaching of agrochemicals but at the same time leads to extreme dilution. The location of the banana plantations upstream of an area with protected marsh areas makes the discussion on contamination even more relevant (Stoorvogel and Eppink, 1995).
Other agrochemicals were found to be less important in the context of soil and water quality. Herbicides were in the process of being terminated on the plantation, and fungicides are generally not as toxic as the nematocides. Although there is no direct proof between the use of agrochemicals and environmental effects in Costa Rica, in other countries, direct effects on aquaculture have been reported (Colburn, 1997).
Socioeconomic Acceptability
The socioeconomic setting is complex. Banana producers have to deal with an export market that requires them to follow certain standard management practices. In the case of the independent producers who sell to the large exporting companies, the farmers have to follow the guidelines given by the companies. On the other hand, there is a strong environmental lobby but with very little legislative support. Finally, there is the objective of each individual entrepreneur to produce in a cost-effective manner and to increase profits. The development of alternative management practices has to consider this important context. Farmers deal in different ways with the production environment. The Rebusca plantation used to export with a few other independent producers to Europe to avoid the monopoly of the large multi-nationals. Other independent farmers comply with the multinationals and follow their guidelines. Contracts are extremely complex as prices of banana vary throughout the year, production quota are defined, and farmers have to have a continuous production with peaks that do not correspond with the biophysical conditions but with the international market. At the same time, we see that the golden times are over. Like many producers of agricultural crops, the banana producers observe decreasing profit margins, and the production has to be very cost-effective. This makes farmers rather risk adverse. There is no room to experiment and to take risks that the production will decline. Management at the Rebusca plantation is very much aware of the difficult situation. However, in contrast to other farmers who are very conservative, they organize discussion sessions with Corbana researchers and extension officers from the private sector to keep updated on new developments and implement them if the developments are considered to be promising. One should note that in many cases this is based on the judgment of the producer as scientific proof is often lacking. To follow exactly the production of the plantation, management kept detailed records on input use and production. Table 1 shows an overview of the cost involved to produce a box of banana. This type of data provided insight in the production process and to see where potential gains could be reached.
|
Past Land Use
The productivity figures for the Rebusca plantation show that productivity has gone up steadily since its establishment in 1990. Besides improved farm management, the intensification of the drainage system and the improved soil conditions appear to be major causes. When the Rebusca plantation was established in 1990, soil structure was not very favorable as a result of the continuous pasture system and the sensitivity of the soil toward compaction (Spaans et al., 1989). The topsoil was found to be compacted under the prior pasturing system. In addition, the subsoil in the poorly drained, backswamp area was found to have a blocky structure with few pores. Since 1990, topsoil structure improved significantly as a result of continuous addition of crop residues and the lack of the trampling effect of animals. With the development of an intensive drainage system, the soil structure in the subsoil started to improve slowly. Nowadays, soil structure can be considered to be favorable in the upper 50 cm throughout the plantation. Soil fertility has been maintained in the plantation with constant organic matter contents (Fig. 3) . An exception was found for soil acidity. The long-term chemical analysis showed that soil acidity was going up, probably caused by the intensive fertilization. Large differences in soil acidity were found between the fertilization band around the plants where typically soil fertility samples were taken and the areas in between plants. A research project at Corbana was dealing with this problem. Given the trend in soil properties, there seems no reason to suspect a decrease in productivity in future.
|
|
The yield units, i.e., the spatial units that supply bunches to one specific train, vary in size and location between harvests. To compare and aggregate yields on different days, it is necessary to disaggregate the data into standard yield registration units (YRUs). The stable YRUs are spatially defined and measure approximately 20 by 100 m. Disaggregation is done by assuming that the yield of a particular train is a good estimate for the central YRU in the yield unit. Subsequently, a surface trend through the YRUs is estimated and corrected for the total measured yield of the cable. This procedure generates yield data per YRU that can easily be aggregated over time, whereas the spatial units are now constant (Fig. 4b).
The spatial variation includes a limited number of discrete soil units and an almost continuous varying yield throughout the YRUs in the plantation. To facilitate interpretation of yield maps, so-called problem areas are identified, on which production is below the soil potential. As a first step, the average yield per soil unit is calculated for a specific yield map. Yield registration units include one or more soil types. The yield in a YRU (YYRU in kg ha–1) is the weighed average of the production of the different soil types in the YRU (YS,YRU in kg ha–1):
 |
s). This can be done by solving the optimization problem where the mean yields for the different soil types are estimated so that
 |
 |
By subtracting the map with the expected yields from the actual yield map, a new map is created that represents the deviation from the expected yields. This map can be classified according to the criteria for problem areas (for example: >20% below the average yield). Likewise, it may be interesting to identify the areas that perform above average and check the reason for their excellence. This can be done following the same procedure but with different classification criteria (for example: YRUs with a yield of >20% above their expected yield). An example of such a map is shown in Fig. 4c.
Fertilization
With the existing variability in soil conditions and banana production, it is obvious that, because of different soil conditions, one single fertilizer recommendation will lead to suboptimal fertilization in large parts of the plantation. How do we determine optimal fertilizer recommendations on a site-specific basis within a commercial plantation? Crop growth simulation models that simulate nutrient-limited yields (as used by Van Alphen and Stoorvogel, 2000) are not available for the banana crop. Existing information from fertilizer experiments is scarce and not specific for the conditions on the plantation. As a result, fertilizer recommendations are mainly based on expert knowledge and have a highly general character (López and Espinoza, 2000). Due to the perennial character of the crop, experimentation is difficult, and full-fledged experiments as proposed by Colwell (1994), for example, have never been performed. Still some experiments are clearly needed, and they were designed here to be part of the prototyping exercise, as follows.
Three main soil types were identified during the soil survey of the plantation (Kooistra et al., 1997). In each of the soil types, three blocks were identified of approximately 0.25 ha. Since the experiment is performed in a commercial plantation, no changes were made in the type of fertilizer. Fertilizer doses in the plots were 75, 100, and 150%, respectively, of current fertilization. During the experiment, crop performance, nutrient leaching, and soil moisture were monitored. The experiment started in April 1998 and continued till February 2000. Differences in fertilization were applied since June 1998. Bunches in each of the plots were harvested, and the characteristics were registered in terms of weight, number of hands, and calibration. Leaf and soil samples were taken at the beginning of the experiment and after 6 mo. Three soil pits were dug in each of the nine plots.
Soil water was sampled from the vadose zone using rhizons. In each of the pits, two rhizons were installed at a depth of 80 cm approximately 60 cm in the side of the pit. One rhizon was located close to the banana plant, and the other is placed between two plants. The rhizons were used to sample water from the vadose zone every 2 wk. The two samples from a pit were pooled to one composite sample. The samples were subsequently analyzed for pH, NO–3, P, Ca, and Mg.
Soil water movement was simulated with LEACHM (Wagenet and Hutson, 1989). The hydraulic characteristics of the soils on the plantation are characterized in terms of the Van Genuchten parameters (Kooistra et al., 1997). Nutrient leaching was calculated by multiplying the simulated water flow at 80-cm depth with the measured nutrient concentrations in soil water. The experiment resulted in specific fertilizer recommendation for the three soil types varying from a 20% reduction in fertilization in a poorly drained soil while maintaining yields to a 35% increase in another, more favorable soil with increasing yields. Yields were the same, but leaching of nutrients, calculated by the models, was reduced by 18 and 2% respectively, indicating not only significantly lower costs and a significant improvement of fertilizer use efficiency but also providing clear documentation of minimal leaching of nutrients to the groundwater.
Nematode Control
From an economic perspective, current management with routine application of alternating nematocides controls the pest at relatively little cost (see Table 1). Degradation rates of nematocides in the vadose zone are fast preventing a buildup. The toxicological effects of nematocides on soil fauna may result in a decrease in biological activity and thus in a degradation of soil structure. However, even old plantations with prolonged use of nematocides do not show a reduction in the quality of soil structure. On the other hand, the perhumid conditions may result in nematocide leaching through the soil toward groundwater and surface water. This certainly needs attention to answer environmental concerns.
In the environmental lobby, pesticide leaching from banana plantations has been mentioned several times. However, researchers from the National University sampled surface waters but did not find consistent elevated levels of nematocides in surface waters (Castillo et al., 2000). Given the perhumid conditions in the study area and the typical peaky discharge in the rivers, nematocides may still leach from the banana plantations but remain undetected. Given the fact that more intensive measurement schemes would be extremely costly, a simulation study, building on validated experiments elsewhere, was considered to be the most appropriate tool (at K5 level). Ethoprop [O-ethyl S,S-dipropyl phosphorodithioate], commercialized as Mocap, is one of the commonly applied nematocides in Costa Rica. It has been classified as a "Ia type" pesticide by the World Health Organization, indicating its extreme toxicity. A limited number of measurements for ethoprop fixation and degradation were done since accurate data for the tropics were lacking. The risk for nematocide leaching in the Rebusca plantation was found to be minimal (Stoorvogel et al., 1999). Extremely high organic matter contents in combination with short degradation rates resulted in degradation of ethoprop before it could be leached from the root zone. However, hot spots with increased leaching risk were found on locations with more sandy deposits and with high groundwater levels (Fig. 5) . Leaching of ethoprop varied between 0% of applied ethoprop in the low-risk areas up to 15% of applied ethoprop in the high-risk areas. In the latter, application should be avoided as risks of groundwater pollution would be too high. Alternatives have to be found, but restriction of measures to these areas only is quite significant from an operational and economic point of view.
|
The productivity data confirmed a large variation in productivity within the plantation. The problem areas identified by the decision support system resulted in the start of an intensive system of renewal of plant material, indicating the broad focus that the overall analysis had taken: Not all problems are related to soil aspects! Although soil differences between the northern and the southern part of the plantation were minimal, there was a consistent variation in productivity. When the plantation was established in 1991, different sources of plant material were used. The northern part was planted with material from an old plantation in the zone while the southern part was planted with second-generation tissue culture producing significantly better. Since 2 yr, almost 10% of the plantation is renewed on a yearly basis, with new plants derived from tissue culture. The impact of renewal is clear, resulting in extremely vigorous plants compared with other parts of the plantation and an approximate 20% increase in productivity.
Fertilization of the plantation seems to be effective. However, there is a possible overfertilization in some areas that seem to have a lower productivity due to other factors (soil structure, texture, and plant material). This is confirmed by the fertility and leaching experiment. A site-specific fertilizer recommendation has therefore now been developed. The experiment clearly changed the attitude with respect to plantation management. The single fertilizer recommendation is seen as a product of the past and is replaced by a site-specific analysis of fertilizer requirements.
Locally, risks for nematocide leaching do occur. However, given the cost of nematode control (see Table 1) and the relatively small area with an elevated risk, the farmer decided not to change his management with respect to nematode control. This illustrates one element of the prototype process: The farmer remains autonomous and may or may not follow certain recommendations. Given the potential risks, nematocide applications will have to take place with extreme caution in the sandy areas, mentioned above, but we have to realize that if proper management takes place, results show that concentrations in groundwater and surface water in the Rebusca plantation are likely to remain below the current thresholds set for drinking water. At the same time, the nematocide companies are developing a new system for the application of nematocides denominated in plant. In this system, a small hole of approximately 2 cm in diameter is made in the pseudostem of a recently harvested shoot. A sachet with a well-defined quantity of nematocide is placed in this hole. Test results by the industry show that the system is very effective; it is currently being tested in part of the La Rebusca plantation as an on-farm trial. The results are promising for both nematode control as well as the environment (no leaching) and human health (no direct contact with the nematocides).
Research activities resulted in a new view on banana management that is defined in a prototype that includes detailed monitoring of productivity on a site-specific basis, renewal of plant material, and the development of new site-specific strategies to banana management, particularly in terms of fertility management. Farmer involvement was substantial in each step and sometimes decisive. The prototyping procedure illustrates that both researchers and farmers contribute their particular expertise in a joint, common context in a different manner as the different steps unfold. Specialist researchers on certain aspects, be it soil fertility or pesticide leaching, perform the type of specialized experiments they usually perform in their discipline. Now, however, this work fits much better into a broader context as described by the farmer than is usually the case. This helps them to focus their experiments better, thereby improving impact. Farmer's input is therefore highly valuable. Farmers, on the other hand, cannot possibly have expertise on fertilizer leaching or pesticide decomposition in soils. Here, obviously, input from science is crucial. This is often ignored when farmer's expertise is glorified as a cure for all ills by some of our colleague scientists.
Step 4: Extension of Promising Results to Other Farms
For the extrapolation of the results to other farms, a trust fund has jointly been established by the owner of the Rebusca Plantation and by Corbana. The trust fund, denominated Fundiap (Fundación para la Investigación de Agricultura de Precisión), is structurally supported by research at Wageningen University. This research agreement is an expression of what we see as agronomic research in a postmodern society in which networks of scientists and stakeholders interact together. The approach of the trust fund is based on the importance of the spatial variability in banana plantations and the effectivity to adapt management to these local differences. The case study at the Rebusca plantation has proven to be an excellent example of low-tech precision agriculture and has drawn the interest of several plantations. As such, prototyping is an excellent tool to tackle a regional level problem. A conference was organized at Corbana at which representatives of producers, the research community, the environmental lobby, and Corbana were present. The meeting was the first time that such an open forum was established in which research lines and innovations in the banana sector were discussed. This was seen by all as an excellent example of research being presented in a setting of joint learning and negotiation.
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONSYSTEMS APPROACHESAPPLICATION OF PROTOTYPING IN...DISCUSSIONREFERENCES |
|---|
|
This has led to the application of a range of different research techniques. Studying a perennial, tropical cropping system seriously limits the application of many tools that have been developed in agricultural research in temperate regions. Such tools were found to be unavailable, or they were clearly unsuitable. Crop growth simulation models were not available in this case, and this holds true for many other crops as well, and quantitative data on input–output relations are lacking. A quantitative analysis in terms of input–output relations like the one done in the TCG by Hengsdijk et al. (1998) and summarized in Table 2 for the current banana management system does not yield useful data for the development of improved systems at the farm level. The dynamics of the system cannot be captured in an array of coefficients. Careful identification of research needs at the K1 level and specific research at other knowledge levels is an essential element of the prototyping exercise. In addition, the interpretation of research results into suggested management practices that are subsequently being discussed with the farmer is one step beyond common practice in the research community. We believe that the integral analysis of the system, as presented, is preferable to the rather static approaches based on technical coefficients. We feel that the problem identification through the prototyping procedure is much more effective than large-scale exercises to develop research strategies within the research community (e.g., Persley and George, 1996).
|
The methodology to describe actual cropping systems in terms of technical coefficients is functional and pragmatic. The descriptions in terms of technical coefficients are ideal for the analysis using optimization models to define alternative land use options in a region (Bouman et al., 1998). However, agricultural production systems are dynamic, and farmers take day-to-day decisions on the basis of external factors. As a result, it is necessary to carry out a more detailed analysis at the farm level of which results can be aggregated at the regional level. The perceived environmental problems in the banana sector lead to emotional calls for a reduction of the area under banana without any hard data. It is, therefore, more fruitful to develop sustainable systems using a prototyping approach.
The basis of the prototyping analysis was described in the beginning of this paper as a problem at the regional level. Although the focus of the analysis from the researchers' perspective may be on the regional problems, the farmer will want to focus on his/her specific problems. Although the negotiation processes between farmer and researcher are essential, it is important to realize that at the end of the prototyping exercise, the prototypes can be described in terms of technical coefficients and, as such, form new input for the regional land use models. The regional analysis may next evaluate the potential impact of the extension of the new technologies and is important to evaluate whether the extension (and all the required resources) would be worthwhile.
The research chains that describe the prototyping procedure run through the different scale levels. It is important to recognize that problems at the regional level also need to address the farm level. At that level, the final decisions on land allocation and land management are taken. A good illustration of such an approach is implemented in the trade-off analysis model (Stoorvogel et al., 2004). The trade-off analysis model is a regional model to quantify trade-offs between sustainability indicators and to predict the effects of policy and technology interventions on these trade-offs. The core of that particular analysis is an econometric simulation model that simulates the decisions about land allocation and management at the field level.
Finally, on the relation with policy issues, even though Costa Rica has a well-deserved reputation for environmental awareness, legislation and enforcement of rules and regulations hardly takes place because of lack of personnel and funds. This is even more true in other developing countries where formal rules and regulations may not even exist. As mentioned above, environmental NGOs are quite vocal on the world scene and have an effect on global trade. Producers cannot ignore this. Our prototyping exercise illustrates an intriguing development, also seen elsewhere, that economic and environmental interests are combined in a win-win arrangement. Rather than only enforce environmental regulations, governments would be well advised to stimulate the type of interaction among farmers, researchers, and extension agents that has been demonstrated in this prototyping exercise. The result is likely to be much more effective from an environmental point of view than nonparticipatory and top-down enforcement of rules and regulations, as has recently been demonstrated in the Netherlands for manure regulations (Sonneveld and Bouma, 2003).
|
ACKNOWLEDGMENTS |
|---|
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONSYSTEMS APPROACHESAPPLICATION OF PROTOTYPING IN...DISCUSSIONREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  C. M. Cherr, J. M. S. Scholberg, and R. McSorley Green Manure Approaches to Crop Production: A Synthesis Agron. J., February 7, 2006; 98(2): 302 - 319. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||
