首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 15 毫秒
1.
The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to ‘take stock’ and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of ‘relevance’ and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process; (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socio-economic variability and change.  相似文献   

2.
Water scarcity is a major factor limiting food production. Improving Livestock Water Productivity (LWP) is one of the approaches to address those problems. LWP is defined as the ratio of livestock’s beneficial outputs and services to water depleted in their production. Increasing LWP can help achieve more production per unit of water depleted. In this study we assess the spatial variability of LWP in three farming systems (rice-based, millet-based and barley-based) of the Gumera watershed in the highlands of the Blue Nile basin, Ethiopia. We collected data on land use, livestock management and climatic variables using focused group discussions, field observation and secondary data. We estimated the water depleted by evapotranspiration (ET) and beneficial animal products and services and then calculated LWP. Our results suggest that LWP is comparable with crop water productivity at watershed scales. Variability of LWP across farming systems of the Gumera watershed was apparent and this can be explained by farmers’ livelihood strategies and prevailing biophysical conditions. In view of the results there are opportunities to improve LWP: improved feed sourcing, enhancing livestock productivity and multiple livestock use strategies can help make animal production more water productive. Attempts to improve agricultural water productivity, at system scale, must recognize differences among systems and optimize resources use by system components.  相似文献   

3.
In the 1970s and 1980s much progress has been made in studying agricultural production systems by using simulation modelling of agronomic processes. The International Benchwork Sites Network for Agrotechnology Transfer (IBSNAT) group in the USA and the group around Professor Kees De Wit in Wageningen were active in this new area of research which created an important ‘niche’ within the agricultural sciences because of its integrative, interdisciplinary character and its focus on quantitative, process-based approaches. A first joint scientific meeting of the two groups was held in Bangkok in 1991 (SAAD1 conference: Systems Analysis for Agricultural Development). At the SAAD2 conference at IRRI in 1995, in which also other groups took part, notably the Agricultural Production Systems Research Unit (APSRU) group from Australia, the International Consortium for Agricultural Systems Applications (ICASA) was established as a forum for researchers engaged in the study of agricultural systems at different spatial scales ranging from fields, farms to regions and beyond. The ICASA is an informal network with a focus on three major activities: (1) sharing experiences and joint development of compatible software allowing more widespread use of models having been developed by various member groups; (2) organization of joint courses on different aspects of dynamic modelling of agricultural production systems. There is an increasing interest in such courses, also in developing countries, and local researchers increasingly take an active part in them; and (3) joint research on projects dealing with dynamic characterization of agronomic production systems at different spatial scales. ICASA researchers take part in eco-regional methodology development, through projects that are funded by the Dutch and Swiss governments, with ISNAR acting as the administrative agency. ICASA intends to be an effective platform on which researchers, stakeholders and policy makers can interact.  相似文献   

4.
An entropy approach to spatial disaggregation of agricultural production   总被引：2，自引：0，他引：2  
While agricultural production statistics are reported on a geopolitical – often national – basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agroecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach, tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25–100 square kilometers in size. The information utilized includes crop production statistics, farming system characteristics, satellite-derived land cover data, biophysical crop suitability assessments, and population density. An application is presented in which Brazilian state level production statistics are used to generate pixel level crop production data for eight crops. To validate the spatial allocation we aggregated the pixel estimates to obtain synthetic estimates of municipality level production in Brazil, and compared those estimates with actual municipality statistics. The approach produced extremely promising results. We then examined the robustness of these results compared to short-cut approaches to allocating crop production statistics and showed that, while computationally intensive, the cross-entropy method does provide more reliable estimates of crop production patterns.  相似文献   

5.
Despite the fact that many smallholder farming systems in developing countries revolve around the interactions of crop and livestock enterprises, the modelling of these systems using combinations of detailed crop and livestock models is comparatively under-developed. A wide variety of separate crop and livestock models exists, but the nature of crop–livestock interactions, and their importance in smallholder farming systems, makes their integration difficult. Even where there is adequate understanding of the biophysical processes involved, integrated crop–livestock models may be constrained by lack of reliable data for calibration and validation. The construction from scratch of simulation models that meet the needs of one particular case is generally too costly to countenance. As for all modelling activity, the most efficient way to proceed depends on the nature of the systems under study and the precise questions that have to be addressed. We outline a framework for the integration of detailed biophysical crop and livestock simulation models. We highlight the need for minimum calibration and validation data sets, and conclude by listing various research problems that need attention. The application of robust and trustworthy crop–livestock models is critical for furthering the research agenda associated with animal agriculture in the tropics and subtropics.  相似文献   

6.
Mixed farming systems constitute a large proportion of agricultural production in the tropics, and provide multiple benefits for the world’s poor. However, our understanding of the functioning of these systems is limited. Modeling offers the best approach to quantify outcomes from many interacting causal variables in these systems. The objective of this study was to develop an integrated crop-livestock model to assess biophysical and economic consequences of farming practices exhibited in sheep systems of Yucatán state, Mexico. A Vensim™ dynamic stock-flow feedback model was developed to integrate scientific and practical knowledge of management, flock dynamics, sheep production, partitioning of nutrients, labor, and economic components. The model accesses sheep production and manure quantity and quality data generated using the Small Ruminant Nutrition System (SRNS), and interfaces on a daily basis with an Agricultural Production Systems Simulator (APSIM) model that simulates weather, crop, and soil dynamics. Model evaluation indicated that the integrated model adequately represents the complex interactions that occur between farmers, crops, and livestock.  相似文献   

7.
Arable land in western Kenya is under considerable pressure from increasing human population. Rural households depend on farming for at least part of their livelihood, and poverty rates are among the highest in Kenya. Land is often depleted of nutrients, and for most farmers, access to inputs and markets is poor. There is a need to identify options that are manageable within the context of the farmer’s resource base and the household’s objectives that could improve farm household well-being. In this study we integrated qualitative informal participatory approaches with quantitative mathematical programming and biophysical simulation modelling. Households in four sub-locations in Vihiga District were clustered and pilot cases identified. Meetings were held with farmers to elicit their perceptions of what their ideal farm would look like, and how its performance might compare with their own farm’s performance. With farmers’ help, a range of scenarios was analysed, relating to changes in current enterprise mixes, changes in current farm sizes, and changes in prices of staples foods and cash crops. A considerable mismatch was found between farmers’ estimates of their own farm’s performance, and what was actually produced. There seems to be a threshold in farm size of 0.4 ha, below which it is very difficult for households to satisfy their income and food security objectives. Even for larger farms whose households are largely dependent on agriculture, the importance of a cash crop in the system is critical. There is a crucial role for extension services in making farmers aware of the potential impacts on farm revenue of modest changes in their farm management systems. We are monitoring nine households in the district, whose farmers have made some changes to their system in an attempt to increase household income and enhance food security.  相似文献   

8.
Approaches to modular model development   总被引：9，自引：0，他引：9  
One of the main goals of the International Consortium for Agricultural Systems Applications (ICASA) is to advance the development and application of compatible and complementary models, data and other systems analysis tools. To help reach that goal, it will adopt and recommend modular approaches that facilitate more systematic model development, documentation, maintenance, and sharing. In this paper, we present criteria and guidelines for modules that will enable them to be plugged into existing models to replace an existing component or to add a new one with minimal changes. This will make it possible to accept contributions from a wide group of modellers with specialities in different disciplines. Two approaches to modular model development have emerged from different research groups in ICASA. One approach was developed by extending the programming methods used in the Fortran Simulation Environment developed in The Netherlands. This method is being used in revisions of some of the Decision Support Systems for Agrotechnology Transfer crop models. A simple example of this approach is given in which a plant growth module is linked with a soil water balance module to create a crop model that simulates growth and yield for a uniform area. The second approach has been evolving within the Agricultural Production Systems Research Unit group in Australia. This approach, implemented in software called Agricultural Production Systems Simulator, consists of plug-in/pull-out modules and an infrastructure for inter-module communication. The two approaches have important similarities, but also differ in implementation details. In both cases, avoiding reliance on any particular programming language has been an important design criterion. By comparing features of both approaches, we have started to develop a set of recommendations for module design that will lead to a ‘toolkit’ of modules that can be shared throughout the ICASA network.  相似文献   

9.
《Agricultural Systems》2005,83(2):135-151
The traditional code-based modelling approach in agriculture and ecology has many strengths, particularly in terms of model flexibility, efficiency and power. Nonetheless code-based programming is a specialist skill and a barrier to simulation modelling to most scientists and students. Icon-based modelling systems on the other hand are easy to use and learn and have opened up simulation modelling to a much broader group of researchers. However there are limitations to the flexibility of these modelling systems and sometimes the size and complexity of models that can be constructed in them.One approach by which researchers can gain the best of both types of models is by linking icon-based models to code-based models within a modular modelling framework. By developing largely self-contained modules that communicate with other modules solely by means of defined input/output variables, modules can be developed in an easy to use icon-based modelling system and subsequently `plugged in' to a larger code-based model. In this paper, we demonstrate this approach using VensimTM to develop a new seed bank module for the Agricultural Production Systems Simulator (APSIM). In an example application we compare the persistence of two hypothetical annual pasture plants with differing life histories under two contrasting farming systems.This approach has the benefits of: (i) rapid and efficient model development that allows specialist scientists and programmers to focus on their respective areas of expertise; (ii) ongoing maintenance and development of modules by science specialists without need for constant recourse to programmers; (iii) ease of sharing, exchange and comparison of icon-based modules between researchers; and, (iv) ease of communication of model structure.  相似文献   

10.
GAMEDE is a stock-flow dynamic simulation model designed with farmers to represent dairy farm functioning and the consequences of the farmer’s daily management decisions for whole-farm sustainability. Sustainability is evaluated according to its three pillars: technico-economic viability, respect for environment, and social liveability. The model provides original information for a better understanding of the processes regulating nitrogen dynamics within the farm, and the factors determining farmers’ decisions and practices. Model implementation experiments have revealed that GAMEDE is also a useful tool to support discussions and to generate knowledge exchange among various stakeholders who play an important role in the development of farm sustainability: farmers, extension agents and researchers.While a majority of researchers and advisers are specialised and a majority of farmers fix their attention on specific and narrow themes of farm management, such a comprehensive model can help stakeholders complement their knowledge to gain a holistic view of the farming system. This holistic and integrated view is crucial: (i) for researchers who wish to explain diversity in farming systems and understand decisional and biophysical processes and their interrelated effects operating in such complex agro-ecosystems, (ii) for advisers whose aim is to define alternative management strategies applicable in practice, i.e. taking into account farm specificities, and (iii) for farmers who must choose practices compatible with their resources, assets, constraints and objectives.Holism can also improve versatility and thus the generic character of models. Issues are narrowly specified and greatly vary both among categories of stakeholders (e.g. scientists versus farmers) and within each category (e.g. among farmers). A comprehensive model that: (i) details all farm management operations, and (ii) represents their effects on different spatio-temporal levels and on the three sustainability dimensions, is more likely to respond to the various issues facing different stakeholders. We argue that capacity of models to respond to stakeholders’ questions has to be considered in future evaluations of decision support systems.  相似文献   

11.
《Agricultural Systems》2002,74(1):141-177
FARMSCAPE (Farmers', Advisers', Researchers', Monitoring, Simulation, Communication And Performance Evaluation) is a program of participatory research with the farming community of northeast Australia. It initially involved research to explore whether farmers and their advisers could gain benefit from tools such as soil characterisation and sampling, climate forecasts and, in particular, simulation modelling. Its current focus is facilitating the implementation of commercial delivery systems for these same tools in order to meet industry demand for their access. This paper presents the story of what was done over the past decade, it provides performance indicators of impact, it reflects on what was learnt over this period and it outlines where this research is likely to head in the future.Over the past 10 years, the FARMSCAPE team employed a Participatory Action Research approach to explore whether farmers could value simulation as a decision support tool for managing their farming system and if so, could it be delivered cost-effectively. Through farmer group engagement, on-farm trials, soil characterisation, monitoring of crops, soils and climate, and sessions to apply the APSIM systems simulator, FARMSCAPE represented a research program on decision support intervention. Initial scepticism by farmers and commercial consultants about the value of APSIM was addressed by testing its performance both against measured data from on-farm trials and against farmers' experiences with past commercial crops. Once this credibility check was passed, simulation sessions usually evolved into participants interactively inquiring of the model the consequence of alternative management options. These ‘What if’ questions using APSIM were contextualised using local climate and soil data and the farmer's actual or proposed management rules.The active participation of farmers and their advisers, and working in the context of their own farming operations, were the key ingredients in the design, implementation and interpretation of the FARMSCAPE approach to decision support. The attraction of the APSIM systems simulator to farmers contemplating change was that it allowed them to explore their own system in a manner equivalent to learning from experience. To achieve this, APSIM had to be credible and flexible. While direct engagement of farmers initially enabled only a limited number of beneficiaries, this approach generated a commercial market for timely and high quality interactions based on soil monitoring and simulation amongst a significant sector of the farming community. Current efforts are therefore focused on the training, support and accreditation of commercial agronomists in the application of the FARMSCAPE approach and tools.The FARMSCAPE approach to decision support has come to represent an approach to guiding science-based engagement with farm decision making which is being tested nationally and internationally.  相似文献   

12.
  相似文献   

13.
Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems.

In this paper, we outline the basis for climate prediction, with emphasis on the El Niño-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction.

In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based on simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications — all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction.

We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential.  相似文献   


14.
This study is an ex ante analysis of multiple goal feasibility of forage shrub plantations in the context of a sheep and wheat agropastoral system. The goals imposed on the system were ‘farmer's income’ represented by gross margin, ‘regional balance of payments's represented by added foreign currency value per unit area and local currency cost of the added value, and ‘employment’ represented by size of farm unit. The socio-economic scenario is appropriate for a semi-arid Mediterranean environment where rural areas are close to urban centres of population and industry. Under such conditions, multiple goal feasibility of shrub plantations was limited by added foreign currency value and farm size in extensive systems, and by gross margin and cost of the added value in intensive systems. Improved ewe productivity improved overall feasibility. Feed substitution per se could not justify forage shrub plantations, but even a small improvement in the weaning rate consequent on the addition of a forage shrub component would greatly increase multiple goal feasibility, particularly in more intensive systems. However, it needs to be shown that such improvement can indeed be achieved in practice.  相似文献   

15.
In trying to respond to societal demands for sustainable development, farming systems worldwide face a range of environmental, technical and economic challenges. These challenges call for renewed methodologies that can be used to support farmers in designing innovative agricultural production systems at the farm level. This paper aims to analyze the various methods described in scientific literature. The review is based on the analysis of 80 reference papers published in international scientific journals between 1999 and 2010. We focused in particular on the purpose of the research, which fell into two broad categories: “design” and “design support”. We also examined the use of models to represent production systems and to evaluate ex-ante the impact of innovations on these systems’ functioning and performance. In so doing, we developed a classification system to organize the studies into five sub-categories according to the type of methodology followed, namely: prototyping and design modelling for design orientated studies; participation, support modelling and advisory for design-support orientated studies. We found that very few studies attempt to address the three main components of an innovation process in agricultural production systems (biotechnical processes, farm management, and advisory services) within a single research framework. We therefore developed such a framework by connecting the design and design support orientations together with biotechnical research and conducting integrated research both at farm and advisory service levels.  相似文献   

16.
 Crop-livestock farms are complex systems. The interactions operating in such systems involve decisional, biophysical, structural, and environmental factors. Moreover, as farmers face a large range of management options, tools are needed to support their decision-making to enable them to reach production levels meeting their objectives and compatible with their human and physical resources, while controlling their effects on the environment. Gamede, a whole-dairy-farm model, has been developed to explore this complexity and to represent dynamically the effect of management decisions on biomass and nitrogen flows and on numerous sustainability indicators, such as milk and forage crop productivity, labour requirements, nitrogen balance, and nitrogen efficiency.This article describes the integration of six modules accounting for biophysical processes in a dairy farm (forage production; forage conditioning; herd demography; milk, excreta and animal biomass productions; grazing, quality of fertilisers; and nitrogen gaseous emissions) together with a decision system accounting for the farmer’s strategy and technical operations. Most of the six biophysical modules incorporate mathematical models from the literature, but the decision system stems from our own original work.Six commercial farms with different structures, agro-climatic conditions and management strategies were used for validation. The model can explain the differences found in their sustainability indicators at the year scale. The intra-year variability of the main biomass stocks and flows is also well explained. This quantitative validation was completed by a qualitative validation from researcher, adviser and farmer points of view, including simulations of prospective scenarios.  相似文献   

17.
This paper combines an agricultural production decision support tool, GrassGro, with economic risk efficiency theory to examine several cattle feeding options that include various grazing systems for three climatic environments in Saskatchewan, Canada. Historical weather data were used to simulate a distribution of forage and cattle production data for each of several grazing systems during a 21-year period, 1978–1998. Price variability was included by varying year 2000 prices using historical price margin changes between the buying and selling weights of cattle. The risk efficiency analysis was completed using the Mean Standard Deviation (MSD) framework, and stochastic dominance principles.

Results of the study suggested that feeding systems, which included grazing, were economically competitive with traditional feedlot feeding systems and grain farming. Finishing cattle on pasture with the addition of a barley supplement was an attractive option, especially when high pasture productivity can be achieved. In all locations, more intense systems that included pasture fertilization and provision of an energy supplement, improved production and risk efficiency. Although the average net returns of all these feeding simulations were negative, the returns of traditional grain crops were even more negative. It is these negative returns in grain operations that lead to the incentive for producers to diversify into cattle production. Despite the negative net returns, the cash flow (range −$15.59 to $407.54 ha−1) was mostly positive in all three locations.  相似文献   


18.
The idea of the decision support system (DSS) for farmers remains an enigma. Clever technology to bridge the gap between agricultural science and farming practice still seems appropriate. Many more of the conditions for success appear to exist today than ever before. Yet the DSS has yet to significantly colonise farm decision making practice. This paper comes late in a long program of research conducted to see if, and under what conditions, computer simulation of farming scenarios, on which a DSS generally depends, can be valued by farmers.The research approach used an unconventional prototypic information system (IS), comprising local measurements, models, and facilitated discussions that evolved in an action research program. The aim has been to elucidate the means by which successful simulation-based decision support intervention can take place and why it usually does not. This required a significant expansion of the researchers’ concept of the farm as a system to include the farmer’s internal system of practical knowing and learning. This paper reports on a cognitive framework model with transactions at interfaces with both the production system and the analytical IS. Its coarse structure is the classical perception-action cycle influenced by goals and outcome feedback. In the highly uncertain production environment of Australian dryland farming, personal judgement plays a significant mediating role between perception and action, and theory of a continuum between the judgement modes of intuition and analysis adds to framework structure. Further structure comes from the theoretical distinctions between holistic and arbitrary intuition, and between causal and probabilistic analysis. Analytic interventions influence: (a) awareness of current situation conditions and (b) expectations of future conditions and action outcomes, and these serve as primary cognitive resources for evaluation of possible actions in planning and decision making. A theory that matches our research experience in bridging the gap between analytic intervention and intuitive practice posits that virtual situations simulated with analytic models and outputs represented graphically can facilitate vicarious experiential learning. This dovetails with theory concerning the education of intuition.The paper concludes by applying criteria from the field of cognitive engineering to test whether the framework presents a concept of mind that is workable for informing practical model-based research and development aimed at supporting farmers’ judgments and decisions.  相似文献   

19.
Epistics is a model combining a biophysical and a decisional model designed to generate irrigation and N fertilisation schedules in apple orchards. These techniques were chosen since they are key elements in the management of fruit tree cropping systems. The biophysical model representing water and N dynamics in orchards was based on the water and N dynamics of Stics and was completed using a crop water and N requirement estimation method adapted to orchards. It was linked to an agronomic decision rule in a combined model able to generate N fertilisation and irrigation schedules. The Epistics evaluation process dealt with numerical evaluation of state variables (water and N soil content) and qualitative evaluation of model-generated schedules. The numerical evaluation, which concerned the biophysical model of Epistics, was performed on the basis of (i) soil nitrate and water content at the end of winters 2002 and 2003, and on (ii) nitrate and water dynamics during spring and summer 2003. The mean Root Mean Squared Error (RMSE) between observed and simulated values at the end of winter was 3.3% water per horizon and 56 kg N/ha, which is relatively good owing to the high spatial and temporal variability of soil water and nitrate content. The qualitative evaluation of generated schedules was performed during interviews with farmers. Farmers were asked to evaluate the model with reference to their own practices. A sharp difference between farmers and the model concerned the beginning of the irrigation period. This suggested that the model should take into account the constraints imposed by scab and codling moth control practices and irrigation rounds. The difference between model-generated and farmers’ fertilisation practices suggested that the model may take plot vigour into account in the fertilisation decision rule. Such a study is a first step towards the design of models linking sound agronomic decision rules to crop modelling and representing interactions between practices.  相似文献   

20.
Historically, Central American small farmers have been trapped in a state of poverty with little know-how, ways or means with which to change their status. The CATIE's Small Farmers' Production Systems Research Program (SFPS) has a long-term goal of helping the small farmers of Central America to search for ways in which to improve their economic and social situation. This project is identifying and defining pathways that lead to this goal. While objectives in the present short-term Small Farmers' Production Systems Research project are somewhat limited, they form part of longer range objectives intended to help the small farmers not only with problems in their crop-animal production and marketing systems but also with their entire farming systems, which include field and vegetable crops, animal production and perennial tree crops.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号