Evaluation of Crop Production and Water Use Efficiency of Autumn-Sown Annual Forage Crops on the Rainfed Region of Loess Plateau China

The Loess Plateau is one of the most important rainfed regions in China, but rainfall is the most significant factor limiting crop production. In this region rainfall from July to September accounts for 56% of the annual total, providing enough water resources for the growth of autumn-sown crops. Although increasing forage production with autumn sown crops is considered an important means of balancing crop forage and livestock management, suitable species with high yields and good water use efficiency (WUE) are not well defined. The relationship between yield and water use efficiency has been shown to vary with plant species and harvest time (Siahpoosh et al. 2011), indicating that good water management can increase yields. It is therefore necessary to establish efficient water management strategies to increase the yield of autumn-sown crops. The objective of this study was to evaluate annual production of forage crops under autumn sowing conditions and identify their optimal WUE, based on crop production and evapo-transpiration (ET)

Relation of Residue Biomass after Defoliation to Regrowth Dry Matter, WSC and Grain Yield of Winter Wheat

The importance of defoliation height on final yield in dual-purpose wheat is inconsistent. In one study no difference in final wheat yield following a severe grazing at 2 cm compared to light grazing at 6 cm was found (Dann et al. 1983). In contrast, clipping at 3 cm above ground level significantly reduced grain yield compared to 7 cm (Arzadun et al. 2006). An explanation for these inconsistent results may be an underestimation of the value of the remaining biomass and its role in the regrowth process (Fulkerson and Donaghy 2001). In this study, the percentage of residue biomass remaining after defoliation was considered when examining the effect of defoliation height on dry matter accumulation and water-soluble carbohydrate (WSC) during wheat regrowth on the Loess plateau, China

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

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

Effects of post harvest drying on the yield of tea tree oil (Melaleuca alternifolia)

Drying tea tree leaf on the stem increased the oil content from 5.8% to 7.4% yield v/dw. This increase is not a result of changing moisture content but appears to be due to an active form of postharvest oil uptake or production. The value to oil producers of drying and storing leaf prior to distillation is a more efficient distillation system. At present, distillation occurs as close as possible to foliage harvest with the aim of reducing any chance of oil volatilization. These results show that the need for immediate distillation of cut foliage is unnecessary, as the delay would actually improve the yield rather than reduce it. For the industry these results could change the accepted methods of production. To date each producer had to have their own distillation plant as a way of avoiding distillation delays and the need for carting wet leaf material. Since drying leaves on the stems of the tree increases the oil yield and since the removal of leaves from the stem is easily accomplished when the leaves are dried, producers need only have storage and leaf stripping facilities. This would enable pure leaf to be transferred cheaply to a central distillery when a sufficient load is achieved

Whole-farm economic, risk and resource-use trade-offs associated with integrating forages into crop-livestock systems in western China

Substantial initiatives are occurring in developing countries to integrate forage crops into crop-livestock systems to improve farmer livelihoods and reduce soil erosion. In particular, government authorities in western China focus on improving farmer livestock profits through greater forage crop production. We examined the whole-farm profit, downside risk, labour-use efficiency and feed balance effects of forage crop intensification on two simulated crop-livestock farm types in western China. Our methodology combined crop and livestock simulation modelling with whole-farm stochastic budgeting to capture both price and climate variability. We modelled the whole-farm effects of (1) introducing either forage vetch (. Vicia sativa), forage oats (. Avena sativa), or grain soybean (. Glycine max) into current wheat (Triticum aestivum)-maize (. Zea mays) systems and (2) replacing maize in current wheat-maize systems with either forage wheat, forage maize, or forage soybean. System intensification through incorporating a forage crop into current grain-cropping systems can increase average simulated profits without increasing downside risk on the simulated farms. As opposed to adding a forage crop into current grain-cropping systems, replacing a grain crop with a forage crop in current grain-cropping systems had a negative effect on profits, downside risk, and labour-use efficiency. Trade-offs existed between labour-use efficiency and profit as forage intensification increased labour demands. These effects were context specific, with greater positive profit effects of forage intensification for the higher-rainfall farm type. Overall, forage intensification in these systems benefited the households, but adoption will depend on household preferences and local agro-ecological and market factors. We demonstrated the importance of exploring proposed intensification options across different locations to capture impacts across diverse contexts. Providing these context-specific insights and exploring trade-offs within systems can help better understand livelihood improvement pathways. In locations with strong competing uses for labour, developing labour-saving practices appears critical

Whole-farm effects of livestock intensification in smallholder systems in Gansu, China

Simulation models can help to identify the whole-farm economic and biophysical impacts of smallholder farmers altering their farming systems. Incorporating long-term climate-induced variability in crop and livestock production enables the implications for agricultural household income and risk to be explored over a range of seasonal conditions. In this study, a simulation model is used to answer the following question: can reducing the area used for grain production by allocating more land to lucerne (Medicago sativa) and increasing livestock numbers improve total net farm income, reduce income variability and maintain grain self-sufficiency for farmers in the Qingyang Prefecture of Gansu Province, China? This was examined for three representative farm types found in the region: a low land-labour ratio farm household, a subsistence-oriented farm household, and a livestock-focused farm household.The Integrated Analysis Tool (IAT), a simulation model of a household farming system, was used to combine crop and forage production simulations, a livestock production model and a household socio-economic model to explore the impact of changes to farming systems over a 40. year simulation period. Data from 90 surveyed households were used to define the structure of the three farm household types and to calibrate the IAT model specifically for Qingyang Prefecture.Additional livestock increased total household net incomes, increased net livestock incomes and reduced net crop incomes for the subsistence-oriented and livestock-focused farm households. For these households, the greater commitment to livestock also reduced grain self-sufficiency due to increased frequency of purchasing grain for home-consumption. Nevertheless, additional livestock reduced income variability for these households whilst improving total net income.The methodology used is useful for understanding changes in farming systems as it focuses on the feasibility and profitability of alternative enterprise mixes and incorporates climate variability. The results support current debates on targeting livestock policies towards smallholders as subsistence-oriented farm households appear to be the largest beneficiaries from livestock interventions. The analysis demonstrates that tradeoffs between net income and grain self-sufficiency are important for households, especially when they are moving from subsistence-based to market-based production

APSIM - evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics