AQUAMAN: a web-based decision support system for irrigation scheduling in peanuts

Peanut (Arachis hypogaea L.) is an economically important legume crop in irrigated production areas of northern Australia. Although the potential pod yield of the crop in these areas is about 8 t ha(-1), most growers generally obtain around 5 t ha(-1), partly due to poor irrigation management. Better information and tools that are easy to use, accurate, and cost-effective are therefore needed to help local peanut growers improve irrigation management. This paper introduces a new web-based decision support system called AQUAMAN that was developed to assist Australian peanut growers schedule irrigations. It simulates the timing and depth of future irrigations by combining procedures from the food and agriculture organization (FAO) guidelines for irrigation scheduling (FAO-56) with those of the agricultural production systems simulator (APSIM) modeling framework. Here, we present a description of AQUAMAN and results of a series of activities (i.e., extension activities, case studies, and a survey) that were conducted to assess its level of acceptance among Australian peanut growers, obtain feedback for future improvements, and evaluate its performance. Application of the tool for scheduling irrigations of commercial peanut farms since its release in 2004-2005 has shown good acceptance by local peanuts growers and potential for significantly improving yield. Limited comparison with the farmer practice of matching the pan evaporation demand during rain-free periods in 2006-2007 and 2008-2009 suggested that AQUAMAN enabled irrigation water savings of up to 50% and the realization of enhanced water and irrigation use efficiencies.

Drought stress characterization of post-rainy season (rabi) sorghum in India

During the post-rainy (rabi) season in India around 3 million tonnes of sorghum grain is produced from 5.7 million ha of cropping. This underpins the livelihood of about 5 million households. Severe drought is common as the crop grown in these areas relies largely on soil moisture stored during the preceding rainy season. Improvement of rabi sorghum cultivars through breeding has been slow but could be accelerated if drought scenarios in the production regions were better understood. The sorghum crop model within the APSIM (Agricultural Production Systems sIMulator) platform was used to simulate crop growth and yield and the pattern of crop water status through each season using available historical weather data. The current model reproduced credibly the observed yield variation across the production region (R2=0.73). The simulated trajectories of drought stress through each crop season were clustered into five different drought stress patterns. A majority of trajectories indicated terminal drought (43%) with various timings of onset during the crop cycle. The most severe droughts (25% of seasons) were when stress began before flowering and resulted in failure of grain production in most cases, although biomass production was not affected so severely. The frequencies of drought stress types were analyzed for selected locations throughout the rabi tract and showed different zones had different predominating stress patterns. This knowledge can help better focus the search for adaptive traits and management practices to specific stress situations and thus accelerate improvement of rabi sorghum via targeted specific adaptation. The case study presented here is applicable to other sorghum growing environments. © 2012 Elsevier B.V.

Impacts and management of wild pigs Sus scrofa in Australia

Globally, wild or feral pigs Sus scrofa are a widespread and important pest. Mitigation of their impacts requires a sound understanding of those impacts and the benefits and limitations of different management approaches. Here, we review published and unpublished studies to provide a synopsis of contemporary understanding of wild pig impacts and management in Australia, and to identify important shortcomings. Wild pigs can have important impacts on biodiversity values, ecosystem functioning and agricultural production. However, many of these impacts remain poorly described, and therefore, difficult to manage effectively. Many impacts are highly variable, and innovative experimental and analytical approaches may be necessary to elucidate them. Most contemporary management programmes use lethal techniques to attempt to reduce pig densities, but it is often unclear how effective they are at reducing damage. We conclude that greater integration of experimental approaches into wild pig management programmes is necessary to improve our understanding of wild pig impacts, and our ability to manage those impacts effectively and efficiently.

Rural Income Generation and Diversification : A Case Study in Eastern Zambia

Rural income diversification has been found to be rather the norm than the exception in developing countries. Smallholder households tend to diversify their income sources because of the need to manage risks, secure a smooth flow of income, allocate surplus labour, respond to various kinds of market failures, and apply coping strategies. The Agricultural Household Model provides a theoretical rationale for income diversification in that rural households aim at maximising their utility. There are several elements involved, such as agricultural production for their own consumption and markets, leisure activities and income from non-farm sources. The aim of the present study is to enhance understanding of the processes of rural income generation and diversification in eastern Zambia. Specifically, it explores the relationship between household characteristics, asset endowments and income-generation patterns. According to the sustainable- rural-livelihoods framework, the assets a household possesses shape its capacity to seize new economic opportunities. The study is based on two surveys conducted among rural smallholder households in four districts of Eastern Province in Zambia in 1985/86 and 2003. Sixty-seven of the interviewed households were present in both surveys and this panel allows comparison between the two points of time. The initial descriptive analysis is complemented with an econometric analysis of the relationships between household assets and income sources. The results show that, on average, 30 per cent of the households income originated from sources outside their own agriculture. There was a slight increase in the proportion of non-farm income from 1985/86 to 2003, but total income clearly declined mainly on account of diminishing crop income. The land area the household was able to cultivate, which is often dependent on the available labour, was the most significant factor affecting both the household-income level and the diversification patterns. Diversification was, in most cases, a coping strategy rather than a voluntary choice. Measured as income/capita/day, all households were below the poverty line in 2003. The agricultural reforms in Zambia, combined with other trends such as changes in rainfall pattern, the worsening livestock situation and the incidence of human disease, had a negative impact on agricultural productivity and income between 1985/86 and 2003. Sources of non-farm income were closely linked to agriculture either upstream or downstream and the income they generated was not enough to compensate for the decline of agricultural income. Household assets and characteristics had a smaller impact on diversification patterns than expected, which could reflect the lack of opportunities in the remote rural environment.

Intensity, productivity and efficiency in agriculture in Finland and implications for N and P fertiliser management

The purpose of this study was to evaluate intensity, productivity and efficiency in agriculture in Finland and show implications for N and P fertiliser management. Environmental concerns relating to agricultural production have been and still are focused on arguments about policies that affect agriculture. These policies constrain production while demand for agricultural products such as food, fibre and energy continuously increase. Therefore the importance of increasing productivity is a great challenge to agriculture. Over the last decades producers have experienced several large changes in the production environment such as the policy reform when Finland joined the EU 1995. Other and market changes occurred with the further EU enlargement with neighbouring countries in 2005 and with the decoupling of supports over the 2006-2007 period. Decreasing prices a decreased number of farmers and decreased profitability in agricultural production have resulted from these changes and constraints and of technological development. It is known that the accession to the EU 1995 would herald changes in agriculture. Especially of interest was how the sudden changes in prices of commodities on especially those of cereals, decreased by 60%, would influence agricultural production. The knowledge of properties of the production function increased in importance as a consequence of price changes. A research on the economic instruments to regulate productions was carried out and combined with earlier studies in paper V. In paper I the objective was to compare two different technologies, the conventional farming and the organic farming, determine differences in productivity and technical efficiency. In addition input specific or environmental efficiencies were analysed. The heterogeneity of agricultural soils and its implications were analysed in article II. In study III the determinants of technical inefficiency were analysed. The aspects and possible effects of the instability in policies due to a partial decoupling of production factors and products were studied in paper IV. Consequently connection between technical efficiency based on the turnover and the sales return was analysed in this study. Simple economic instruments such as fertiliser taxes have a direct effect on fertiliser consumption and indirectly increase the value of organic fertilisers. However, fertiliser taxes, do not fully address the N and P management problems adequately and are therefore not suitable for nutrient management improvements in general. Productivity of organic farms is lower on average than conventional farms and the difference increases when looking at selling returns only. The organic sector needs more research and development on productivity. Livestock density in organic farming increases productivity, however, there is an upper limit to livestock densities on organic farms and therefore nutrient on organic farms are also limited. Soil factors affects phosphorous and nitrogen efficiency. Soils like sand and silt have lower input specific overall efficiency for nutrients N and P. Special attention is needed for the management on these soils. Clay soils and soils with moderate clay content have higher efficiency. Soil heterogeneity is cause for an unavoidable inefficiency in agriculture.

Liikennepolttoaineeksi tarkoitettu ohraetanoli, Suomen ohramarkkinat ja ilmastonmuutos

The aim of the thesis was to analyze the use of barley as an input for bioethanol production and the impacts the use has on the Finnish barley markets. Two main research questions were formulated. First, privately and socially optimal bioethanol production levels were examined. In the social optimum, the climate benefits of bioethanol production were considered. It was calculated that the production and use of bioethanol created smaller CO2 -emissions when compared with the production and use of gasoline. Second, the impacts of bioethanol production on farmland allocation and agricultural production were analyzed. In more detail, the second aim was to analyze the farmland allocation between wheat and barley cultivation and green set aside in the private and social optimum. An analytical model was produced to analyze the barley markets in Finland. To provide an empirical counterpart to this model, existing research data on bioethanol production and barley cultivation was used. The aim of the model was to analyze the supply and the demand as well as market equilibrium of barley. Furthermore, the model provided a framework for analyzing the differences between the private optimum and social optimum of bioethanol production in Finland. The demand for barley consists of animal feed demand and bioethanol demand. On the supply side, a heterogeneous model of farmland quality was used. With this framework, it is possible to analyze farmland allocation between barley and wheat cultivation and green set aside and how the climate benefits of bioethanol production affects the allocation. Moreover, the relative changes in barley price between the private and social optimum were analyzed. Based on the empirical analysis, the private optimum for barley based bioethanol production is 58 691 metric tons. However, the social optimum for barley based bioethanol production is 72 736 metric tons. The portion of farmland that is allocated to barley cultivation is increased if the climate benefits of bioethanol production are considered. In the private optimum, 1/19 of the total farmland is allocated to barley cultivation whereas in social optimum the share increases to 7/19. Furthermore, the increase in barley price between private and social optimum is rather modest. Total increase in price is only about 1,8 percent.

Suomen maatalouden tuottamat kasvihuonekaasujen päästöt eri politiikkaskenaarioissa

Climate change is the single biggest environmental problem in the world at the moment. Although the effects are still not fully understood and there is considerable amount of uncertainty, many na-tions have decided to mitigate the change. On the societal level, a planner who tries to find an eco-nomically optimal solution to an environmental pollution problem seeks to reduce pollution from the sources where reductions are most cost-effective. This study aims to find out how effective the instruments of the agricultural policy are in the case of climate change mitigation in Finland. The theoretical base of this study is the neoclassical economic theory that is based on the assumption of a rational economic agent who maximizes his own utility. This theoretical base has been widened towards the direction clearly essential to the matter: the theory of environmental eco-nomics. Deeply relevant to this problem and central in the theory of environmental economics are the concepts of externalities and public goods. What are also relevant are the problems of global pollution and non-point-source pollution. Econometric modelling was the method that was applied to this study. The Finnish part of the AGMEMOD-model, covering the whole EU, was used for the estimation of the development of pollution. This model is a seemingly recursive, partially dynamic partial-equilibrium model that was constructed to predict the development of Finnish agricultural production of the most important products. For the study, I personally updated the model and also widened its scope in some relevant matters. Also, I devised a table that can calculate the emissions of greenhouse gases according to the rules set by the IPCC. With the model I investigated five alternative scenarios in comparison to the base-line scenario of Agenda 2000 agricultural policy. The alternative scenarios were: 1) the CAP reform of 2003, 2) free trade on agricultural commodities, 3) technological change, 4) banning the cultivation of organic soils and 5) the combination of the last three scenarios as the maximal achievement in reduction. The maximal achievement in the alternative scenario 5 was 1/3 of the level achieved on the base-line scenario. CAP reform caused only a minor reduction when com-pared to the base-line scenario. Instead, the free trade scenario and the scenario of technological change alone caused a significant reduction. The biggest single reduction was achieved by banning the cultivation of organic land. However, this was also the most questionable scenario to be real-ized, the reasons for this are further elaborated in the paper. The maximal reduction that can be achieved in the Finnish agricultural sector is about 11 % of the emission reduction that is needed to comply with the Kyoto protocol.

Identifying risk-efficient strategies using stochastic frontier analysis and simulation: An application to irrigated cropping in Australia

In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.

Plantation crops

Plantation horticulture is an important part of the economic landscape of many tropical countries. Plantations were developed in association with colonial expansion and the original models were based on the production of monocrops which had a ready export market, using cheap or slave labour. Plantations in the twenty first Century are less likely environments for exploitation of human and environmental capital. They are however, linked to crop production on a large scale for produce to be sold, at profit, for export to distant markets rather than local sale. A range of crops can be broadly categorized into plantation crops. Plantations continue to be effective models for efficient agricultural production and will evolve in response to the continued demand for food, fruit, fibre, oil crops and timber from a growing population

The shifting influence of drought and heat stress for crops in Northeast Australia

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

Physiological basis of yield variation in response to row spacing and plant density of mungbean grown in subtropical environments

In this study, we investigated the extent and physiological bases of yield variation due to row spacing and plant density configuration in the mungbean Vigna radiata (L.) Wilczek variety “Crystal” grown in different subtropical environments. Field trials were conducted in six production environments; one rain-fed and one irrigated trial each at Biloela and Emerald, and one rain-fed trial each at Hermitage and Kingaroy sites in Queensland, Australia. In each trial, six combinations of spatial arrangement of plants, achieved through two inter-row spacings of 1 m or 0.9 m (wide row), 0.5 m or 0.3 m (narrow row), with three plant densities, 20, 30 and 40 plants/m2, were compared. The narrow row spacing resulted in 22% higher shoot dry matter and 14% more yield compared to the wide rows. The yield advantage of narrow rows ranged from 10% to 36% in the two irrigated and three rain-fed trials. However, yield loss of up to 10% was also recorded from narrow rows at Emerald where the crop suffered severe drought. Neither the effects of plant density, nor the interaction between plant density and row spacing, however, were significant in any trial. The yield advantage of narrow rows was related to 22% more intercepted radiation. In addition, simulations by the Agricultural Production Systems Simulator model, using site-specific agronomy, soil and weather information, suggested that narrow rows had proportionately greater use of soil water through transpiration, compared to evaporation resulting in higher yield per mm of soil water. The long-term simulation of yield probabilities over 123 years for the two row configurations showed that the mungbean crop planted in narrow rows could produce up to 30% higher grain yield compared to wide rows in 95% of the seasons.

The shifting influence of drought and heat stress for crops in Northeast Australia

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.