Evaluation of a new cropping option using a participatory approach with on-farm monitoring and simulation: a case study of spring-sown mungbeans

In the northern Australian cropping region, mungbean is commonly sown as an opportunity crop, usually on low soil water after a winter cereal, and consequently has a reputation for being a low yielding, high risk crop. Yield prospects could be improved and risks reduced if it was sown on soils with a higher soil water content, for instance in spring after a winter fallow. However, there is a lack of experience and confidence in alternative roles for mungbean in the farming system. This paper describes a research approach involving researchers, farmers, advisers, and grain traders in which on-farm monitoring of spring-sown commercial crops and cropping systems simulation with APSIM were used to explore yield prospects for a spring-sown crop after a winter fallow. The key elements of the approach are: (1) identification of possible options through simulation of scenarios, (2) testing the new practice with innovative farmers, and (3) monitoring of the management and performance of commercial crops and comparing yields with benchmarks estimated with a model. In this case, after 2 years of on-farm testing, spring-sown mungbean has been shown to have a potential for high returns in the northern cropping systems

Systems research helping to meet the needs and managing the trade-offs of a changing world

Facing the challenges of an increasing world population, a changing climate and ever depleting resources, agricultural is one of the few options for meeting the demand of food security. It is necessary to apply a dynamic and systematic approach to effectively manage the complex agri-eco production and green processing systems. Indeed, farming systems approach for appropriate technology development and simulation modeling is a result of adopting the system thinking by the agricultural research community..

Expanding supply of improved seed to farmers in northern Ghana to increase food security

The global problem of food security is particularly acute in many parts of west Africa, where food production needs to increase to meet growing demand. The ‘Green Revolution', where improved crop varieties are matched with improved management practices (particularly fertilisers), has been very successful in increasing food production in many parts of the world. However, in much of west Africa farmers have not adopted improved crop varieties. There are many reasons behind this lack of implementation, such as access to finance, access to improved varieties, access to market and government policy constraints. One major roadblock to adoption of improved varieties identified in Savelugu, northern Ghana, was a lack of sufficient improved cowpea seed (an important cash crop). In northern Ghana there are very few certified seed producers, mainly due to the highly regulated certification process. More than 90% of seed is traded between farmers in an ‘informal' seed market. In trials conducted in the Savelugu region improved, certified, cowpea varieties consistently outperformed farmer varieties and at field days farmers showed a strong preference for improved varieties.In the Savelugu region we worked with an Innovation Platform on a pilot system where one seed producer contracted ‘out‐growers' to produce certified seed, while the seed producer performed the certification processes and provide the required inputs and technical support. These out‐growers were situated in villages around Savelugu, where they were able to use the informal supply chain to deliver 20 additional tonnes of certified seed to farmers in the first year of operation

The growth and development of pearl millet as affected by plant population

Pearlmillet (Pennisetum americanum (L.) Leeke) was grown at ICRISAT, Hyderabad, India at 20 densities ranging from 50 000 to 400 000 plants ha−1 using a Nelder fan design. Studies were made on the effect of population on the distribution of plant dry weight, leaf area, grain yield and yield components throughout the season. The first effect of increasing population was evident at panicle initiation (<6% final dry weight produced) where dry weight accumulation in the main axis was unaffected but that in the tillers was reduced. Subsequently, the increased plant population resulted in reductions of 77% in total weight per plant, 66% in leaf area per plant and 59% in tiller number per plant at 50% anthesis. Thedevelopmentof green leaf area per plant followed the same trend over the range of populations, so that leaf area index ranged with increasing population from 2.9 to 6.7 at 50% anthesis; severe leaf senescence occurred in the latter part of grain filling. As population increased, thedevelopmentof tillers terminated earlier in thegrowthofthe plant, resulting in a reduced tiller survival rate and therefore reduced productive head numbers per plant. Grain yield per plant declined owing to the reduced head numbers and also to lower seed numbers per head. Seed size remained largely unchanged. Population influenced plant yield chiefly through the highly responsive yield fraction of tillers, asthe yield ofthe main axis was relatively stable. Grain yield ha−1 increased to a maximum at 150 000 plants ha−1, which was maintained through to 400 000 plants ha−1 due to the large degree of plasticity in productive tiller number per plan

Simulating growth, development, and yield of tillering pearl millet I. Leaf area profiles on main shoots and tillers

Pearl millet (Pennisteum americanum L.) is an essential crop in farming systems of the dry areas of the semi-arid tropics and its tillering habit is an important adaptive feature. This is the first paper in a series aiming at developing and validating a pearl millet simulation model that recognises tillers as functional entities, analogous to intercrops. The objective of this paper is to quantify the effects of total leaf number per axis (TLN), cultivar, plant density and axis number on parameters that are used to simulate potential leaf area per plant. Four cultivars with different phenology and tillering habit were grown under well-watered and well-fertilised conditions at two locations in India, covering a range of daylengths and plant densities. For selected plants, the area of fully expanded leaves was measured non-destructively. A bell-shaped function adequately described the relationship between individual leaf area and leaf position on an axis. Its shape was determined by the position (X0) and area (Y0) of the largest leaf and by the breadth and skewness of the leaf area profile curve. TLN affected all four parameters, although the association with Y0 was weak. Cultivar only affected Y0, suggesting that parameterising new cultivars is straightforward. The observed density effect confirmed that competition for light between axes started during stem elongation. The results highlighted the consistent differences between leaf area profiles of main shoots and tillers. For a high-tillering crop like pearl millet, modelling leaf area dynamics through individual leaves is justified, as this approach can potentially deal with cultivar and environmental effects on tillering

How farming systems simulation can aid the development of more sustainable smallholder farming systems in southern Africa

Over the past 20 years, farming systems modelling has become an accessible tool for developing intervention strategies targeted at smallholder farmers in southern Africa. Applying the Agricultural Productions Systems sIMulator (APSIM) to credibly simulate key soil and crop processes in highly constrained, low yielding maize/legume systems has led to four distinct modes of use: (i) to add value to field experimentation and demonstration; (ii) in direct engagement with farmers; (iii) to explore key system constraints and opportunities with researchers and extension agencies; and (iv) in the generation of information for policy makers, bankers and insurance institutions. Examples of application in each of these modes are presented. Despite being demonstrated as an excellent tool for developing intervention strategies and extension material, the use of simulation is limited by a lack of competent local users. Better co-operation within the simulation community, sharing of climate, soil and crop parameterisation and validation datasets, and focussing of efforts on using models to benefit smallholder farmers are suggested as ways of increasing the use and relevance of simulation. Substantial investment in the training of agriculturalists and the further science development of systems simulation is required to tackle the enormous challenges facing agricultural development in the region

Employee Stock Ownership and Financial Performance in European Countries: The Moderating Effects of Uncertainty Avoidance and Social Trust

This study investigates how the effect of employee stock ownership on financial performance may hinge on the diverse cultural and societal contexts of European countries. Based on agency and national culture theories, we hypothesize that the positive relationship between employee stock ownership and return on assets (ROA) is stronger in those nations with lower uncertainty avoidance and higher social trust. Using a multisource, time‐lagged, large‐scale dataset of 1,741 firms from 21 countries in Europe, our multilevel, random coefficient modeling analysis found evidence for these hypotheses, suggesting that uncertainty avoidance and social trust serve as important contextual cues in predicting the linkage between employee stock ownership and financial performance. Our supplemental analysis with distinction between the managerial and nonmanagerial employee stock ownership further indicates managerial employee stock ownership has a direct positive effect on ROA. Although nonmanagerial employee stock ownership had a nonsignificant association with ROA, the relationship was positive and significant when uncertainty avoidance was low and social trust was high. This research contributes to the existing literature by illuminating some of the contextual influences altering the effectiveness of employee stock ownership. Our findings also offer practical suggestions for effectively using employee stock ownership

Predicting growth and development of pigeonpea: flowering response to photoperiod

Data from sowing-date and other experiments conducted for nine cultivars at three locations ranging from 18300S to 278150N were analysed for photoperiod response. All cultivars were found to have a qualitative response to photoperiod. The results of the analysis show that cultivars previously reported to be "relatively insensitive" to photoperiod were, in fact, highly sensitive. Flowering in short-duration cultivars was delayed by up to a 100 days when daylength in the photoperiod-inductive phase exceeded a critical value. Medium- and long-duration cultivars delayed flowering by over 150 days in response to photoperiod. A model was able to predict this wide range in flowering dates

Predicting growth and development of pigeonpea: a simulation model

A simulation model of pigeonpea is described that is designed to simulate the development, growth, nitrogen accumulation and yield of a wide range of maturity types from extra-short to medium-duration in response to weather, soil conditions and agronomic management. Parameters of the model for phenological development, leaf area expansion, radiation interception, biomass accumulation and partitioning, crop water use, root growth and water extraction, and nitrogen accumulation are derived from published studies. In addition, the calibration exercise is described to derive the parameters accounting for the effect of plant population density on leaf area expansion. The model was tested on 38 data sets, not previously used to derive model parameters, collected at Patancheru, India. Data sets encompassed a wide range of plant type, sowing density, and seasons, grown on Alfisol and Vertisol soil types under dryland and irrigated conditions. The time to flowering and maturity from the extra-short to medium-duration types were simulated well, explaining 96 and 92% of the variance (RMSD=4.3 and 9.8 days), respectively. Total aboveground biomass was simulated with less accuracy, explaining 74% of the variance (RMSD=2056 kg ha-1) and grain yield was simulated explaining 76% of the variance (RMSD=332 kg ha-1). There remains scope for model improvement in the areas of waterlogging and testing on crop N accumulation. This pigeonpea module, when coupled with other crop, soil and management modules can be used to address a range of cropping systems issues