Global banana disease management - getting serious with sustainability and food security

Much research in understanding plant diseases has been undertaken, but there has been insufficient attention given to dealing with coordinated approaches to preventing and managing diseases. A global management approach is essential to the long-term sustainability of banana production. This approach would involve coordinated surveys, capacity building in developing countries, development of disease outbreak contingency plans and coordinated quarantine awareness, including on-line training in impact risk assessment and web-based diagnostic software. Free movement of banana plants and products between some banana-producing countries is causing significant pressure on the ability to manage diseases in banana. The rapid spread of Fusarium oxysporum f. sp. cubense 'tropical race 4' in Asia, bacterial wilts in Africa and Asia and black leaf streak [Mycosphaerella fijiensis] in Brazil and elsewhere are cases in point. The impact of these diseases is devastating, severely cutting family incomes and jeopardising food security around the globe. Agreements urgently need to be reached between governments to halt the movement of banana plants and products between banana-producing countries before it is too late and global food security is irreparably harmed. Black leaf streak, arguably the most serious banana disease, has become extremely difficult to control in commercial plantations in various parts of the world. Sometimes in excess of 50 fungicide sprays have to be applied each year. Disease eradication and effective disease control is not possible because there is no control of disease inoculum in non-commercial plantings in these locations. Additionally, there have been enormous sums of money invested in international banana breeding programmes over many years only to see the value of hybrid products lost too soon. 'Goldfinger' (AAAB, syn. 'FHIA-01'), for example, has recently been observed severely affected by black leaf streak in Samoa. Resistant cultivars alone cannot be relied upon in the fight against this disease. Real progress in control may only come when the local communities are engaged and become actively involved in regional programmes. Global recommendations are long overdue and urgently needed to help ensure the long-term sustainable utilisation of the products of the breeding programmes.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

Breedcow and Dynama software redevelopment

The project renewed the Breedcow and Dynama software making it compatible with modern computer operating systems and platforms. Enhancements were also made to the linkages between the individual programs and their operation. The suite of programs is a critical component of the skill set required to make soundly based plans and production choices in the north Australian beef industry.

ACIAR Scoping study for Improved food security and livelihoods in rural Zimbabwe

A short project to provide input to planning a project aimed at improving food security and rural livelihoods in Zimbabwe.

NEESTIMATOR v2: re-implementation of software for the estimation of contemporary effective population size (N-e) from genetic data

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

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.

Reconfiguring agriculture through the relocation of production systems for water, environment and food security under climate change

The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations. The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.