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A major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments is important. Mechanistic crop models are a major tool for such predictions, but calibration of crop phenology models is difficult and there is no consensus on the best approach. We propose an original, detailed approach for calibration of such models, which we refer to as a calibration protocol. The protocol covers all the steps in the calibration workflow, namely choice of default parameter values, choice of objective function, choice of parameters to estimate from the data, calculation of optimal parameter values, and diagnostics. The major innovation is in the choice of which parameters to estimate from the data, which combines expert knowledge and data-based model selection. First, almost additive parameters are identified and estimated. This should make bias (average difference between observed and simulated values) nearly zero. These are "obligatory" parameters, that will definitely be estimated. Then candidate parameters are identified, which are parameters likely to explain the remaining discrepancies between simulated and observed values. A candidate is only added to the list of parameters to estimate if it leads to a reduction in BIC (Bayesian Information Criterion), which is a model selection criterion. A second original aspect of the protocol is the specification of documentation for each stage of the protocol. The protocol was applied by 19 modeling teams to three data sets for wheat phenology. All teams first calibrated their model using their "usual" calibration approach, so it was possible to compare usual and protocol calibration. Evaluation of prediction error was based on data from sites and years not represented in the training data. Compared to usual calibration, calibration following the new protocol reduced the variability between modeling teams by 22% and reduced prediction error by 11%. [ABSTRACT FROM AUTHOR]

Achieving SDG2 (zero hunger) in a situation of rapid global population growth requires a continued focus on food production. Farming not merely needs to sustainably produce nutritious diets, but should also provide livelihoods for farmers, while retaining natural ecosystems and services. Rather than focusing on production principles, this article explores the interrelations between farms and farming systems in the global food system. Evaluating farming systems around the world, we reveal a bewildering diversity. While family farms predominate, these range in size from less than 0.1 ha to more than 10,000 ha, and from hand hoe use to machine-based cultivation, enabling one person to plant more than 500 ha in a day. Yet, farming in different parts of the world is highly interdependent, not least because prices paid for farm produce are largely determined by global markets. Furthermore, the economic viability of farming is a problem, globally. We highlight trends in major regions of the world and explore possible trajectories for the future and ask: Who are the farmers of the future? Changing patterns of land ownership, rental and exchange mean that the concept of 'what is a farm' becomes increasingly fluid. Next to declining employment and rural depopulation, we also foresee more environmentally-friendly, less external input dependent, regionalised production systems. This may require the reversal of a global trend towards increasing specialisation to a recoupling of arable and livestock farming, not least for the resilience it provides. It might also require a slow-down or reversal of the widespread trend of scale enlargement in agriculture. Next to this trend of scale enlargement, small farms persist in Asia: consolidation of farms proceeds at a snail's pace in South-east Asia and 70% of farms in India are 'ultra-small' – less than 0.05 ha. Also in Africa, where we find smallholder farms are much smaller than often assumed (< 1 ha), farming households are often food insecure. A raft of pro-poor policies and investments are needed to stimulate small-scale agriculture as part of a broader focus on rural development to address persistent poverty and hunger. Smallholder farms will remain an important source of food and income, and a social safety net in absence of alternative livelihood security. But with limited possibilities for smallholders to 'step-up', the agricultural engine of growth appears to be broken. Smallholder agriculture cannot deliver the rate of economic growth currently assumed by many policy initiatives in Africa. [ABSTRACT FROM AUTHOR]

Crop yield must increase to keep pace with growing global demand. Past increases in crop production have rarely been attributable to an individual innovation but have occurred when technologies and practices combine to form improved farming systems. Inevitably this has involved synergy between genotypic and management improvements. We argue that research focused on developing synergistic systems that overcome clear production constraints will accelerate increases in yield. This offers the opportunity to better focus and multiply the impact of discipline-focused research. Here we use the rainfed grain production systems of south-eastern Australia as a case study of how transformational change in water productivity can be achieved with research focused on genotype × management synergies. In this region, rainfall is low and variable and has declined since 1990. Despite this, growers have maintained yields by implementing synergistic systems combining innovations in (i) soil water conservation, (ii) crop diversity, (iii) earlier sowing, and (iv) matching nitrogen fertilizer to water-limited demand. Further increases are emerging from synergies between genetic improvements to deliver flowering time stability, adjusted sowing times, and potential dual-purpose use. Collaboration between agronomists, physiologists, and crop breeders has led to development of commercial genotypes with stable flowering time that are in early phases of testing and adoption. [ABSTRACT FROM AUTHOR]

Using participatory action research methods, we co-developed climate risk management approaches with participating farmers as part of a large project in India on climate adaptation to climate change in Asia (ACCA). The key components of this work involved village level meteorological data recording and reporting, formation and development of farmer climate clubs, on-farm participatory research testing a range of sowing and irrigation practices in response to weather patterns, and preparation and dissemination of agro-meteorological advisories. This research catalysed the development of the CLimate Information Centre concept (CLIC), further evolving into the development of an ICT platform of software and hardware that integrated the ACCA project results, biweekly agro-meteorological advisory bulletins and static agronomy information. An evaluation of the CLICs was undertaken based on a survey of 330 farmers in eight CLICs villages in Telangana state in southern India. The evaluation considered aspects such as the frequency of visits to CLICs, farmer perceptions on usefulness of information, any changes in knowledge and practice due to CLICs visits, and satisfaction with the CLICs as a source of information. On average 80 percent of the surveyed farmers had visited CLICs during the period. Farmers highlighted the important contribution of the agronomy videos they watched, access to agro-meteorological bulletins, information on pests, and weather forecast information. These contributed to various types of benefits they derived including an average cost savings of US$ 4 – 64 per hectare/year. While the current version of CLICs has shown promise and relevance for small holders, they need to be further developed into small business centres that function as a knowledge and provision hub for various agriculture inputs and providing climate information as an important service. This will serve as a self-sustaining financial model for CLICs rather than climate information as the only source of information service that is currently the case. [ABSTRACT FROM AUTHOR]

Soil sodicity, acidity, and salinity are important soil constraints to wheat production in many cropping regions across Australia, and the Australian agricultural industry needs accurate information on their economic impacts to guide investment decisions on remediation and minimize productivity losses. We present a modelling framework that maps the effects of soil constraints on wheat yield, quantifying forfeited wheat yields due to specific soil constraints at a broad spatial scale and assessing the economic benefit of managing these constraints. Of the three soil constraints considered (sodicity, acidity, and salinity), sodicity caused the largest magnitude of yield gaps across most of the wheat‐cropping areas of Australia, with an average yield gap of 0.13 t ha−1yr−1. Yield gaps due to acidity were more concentrated spatially in the high‐rainfall regions of Western Australia, Victoria, and New South Wales, and averaged 0.04 t ha−1yr−1 across the wheat‐cropping areas of Australia, whereas the yield gap due to salinity was estimated to be 0.02 t ha−1yr−1. The lost opportunity associated with soil sodicity for wheat production was estimated to be worth A$1,300 million per annum, for soil acidity, A$400 million per annum, and for salinity, A$200 million per annum. The results of this work should prove useful to guide national investment decisions on the allocation of resources and to target areas where more detailed information would be required in order to reduce the yield gap associated with soil constraints on wheat yields in Australia. [ABSTRACT FROM AUTHOR]

Engineering perishable crops for use in indoor farms promises to expand the adoption of this high-yielding, efficient means of food production. [ABSTRACT FROM AUTHOR]

Global food security requires that grain yields continue to increase to 2050, yet yields have stalled in many developed countries. This disturbing trend has so far been only partially explained. Here, we show that wheat yields in Australia have stalled since 1990 and investigate the extent to which climate trends account for this observation. Based on simulation of 50 sites with quality weather data, that are representative of the agro-ecological zones and of soil types in the grain zone, we show that water-limited yield potential declined by 27% over a 26 year period from 1990 to 2015. We attribute this decline to reduced rainfall and to rising temperatures while the positive effect of elevated atmospheric CO2 concentrations prevented a further 4% loss relative to 1990 yields. Closer investigation of three sites revealed the nature of the simulated response of water-limited yield to water availability, water stress and maximum temperatures. At all three sites, maximum temperature hastened time from sowing to flowering and to maturity and reduced grain number per m2 and average weight per grain. This 27% climate-driven decline in water-limited yield is not fully expressed in actual national yields. This is due to an unprecedented rate of technology-driven gains closing the gap between actual and water-limited potential yields by 25 kg ha−1 yr−1 enabling relative yields to increase from 39% in 1990 to 55% in 2015. It remains to be seen whether technology can continue to maintain current yields, let alone increase them to those required by 2050. [ABSTRACT FROM AUTHOR]

We used a participatory approach and a rural livelihoods framework to explore the knowledge and capacity of southeast Queensland graziers to adapt to climate change. After being presented with information on climate change projections, participants identified biophysical and socio-economic opportunities and challenges to adaptation. Graziers identified key opportunities as components of resilience (incremental change), and in many cases were options that they had some knowledge of either from their own region or elsewhere in the grazing industry. The major constraint to adaptation was the lack of financial capital: with low profitability of the industry and high land costs restricting their capacity to diversify and exploit economies of scale. These constraints were exacerbated by the pressure many graziers experienced from the demand for land as a result of urban expansion. While the focus of the workshop was on the impact of climate change and capacity to adapt, many of the issues raised by graziers were pressures not solely related to climate change. Adaptation needs to be considered in light of the appropriate level (resilience-transition-transformation) and spatial scale (field to region) required to tackle the issues identified. Policy needs to support good natural resource management, rural amenity, and food and fibre production close to urban population and markets in the face of urban encroachment. [ABSTRACT FROM AUTHOR]

Global food security requires eco-efficient agriculture to produce the required food and fiber products concomitant with ecologically efficient use of resources. This eco-efficiency concept is used to diagnose the state of agricultural production in China (irrigated wheat-maize double-cropping systems), Zimbabwe (rainfed maize systems), and Australia (rainfed wheat systems). More than 3,000 surveyed crop yields in these three countries were compared against simulated grain yields at farmer-specified levels of nitrogen (N) input. Many Australian commercial wheat farmers are both close to existing production frontiers and gain little prospective return from increasing their N input. Significant losses of N from their systems, either as nitrous oxide emissions or as nitrate leached from the soil profile, are infrequent and at low intensities relative to their level of grain production. These Australian farmers operate close to eco-efficient frontiers in regard to N, and so innovations in technologies and practices are essential to increasing their production without added economic or environmental risks. In contrast, many Chinese farmers can reduce N input without sacrificing production through more efficient use of their fertilizer input. In fact, there are real prospects for the double-cropping systems on the North China Plain to achieve both production increases and reduced environmental risks. Zimbabwean farmers have the opportunity for significant production increases by both improving their technical efficiency and increasing their level of input; however, doing so will require improved management expertise and greater access to institutional support for addressing the higher risks. This paper shows that pathways for achieving improved eco-efficiency will differ among diverse cropping systems. [ABSTRACT FROM AUTHOR]

Fallows are widespread in dryland cropping systems. However, timely information about their spatial extent and location remains scarce. To overcome this lack of information, we propose to classify fractional cover data from Sentinel-2 with biased support vector machines. Fractional cover images describe the land surface in intuitive, biophysical terms, which reduces the spectral variability within the fallow class. Biased support vector machines are a type of one-class classifiers that require labelled data for the class of interest and unlabelled data for the other classes. They allow us to extrapolate in-situ observations collected during flowering to the rest of the growing season to generate large training data sets, thereby reducing the data collection requirements. We tested this approach to monitor fallows in the northern grains region of Australia and showed that the seasonal fallow extent can be mapped with >92% accuracy both during the summer and winter seasons. The summer fallow extent can be accurately mapped as early as mid-December (1–4 months before harvest). The winter fallow extent can be accurately mapped from mid-August (2–4 months before harvest). Our method also detected emergence dates successfully, indicating the near real-time accuracy of our method. We estimated that the extent of fallow fields across the northern grains region of Australia ranged between 50% in winter 2017 and 85% in winter 2019. Our method is scalable, sensor independent and economical to run. As such, it lays the foundations for reconstructing and monitoring the cropping dynamics in Australia. [ABSTRACT FROM AUTHOR]

Australia's farmers are among the most efficient in the world, despite a relatively large gap between potential and achieved water-limited grain yield. With wheat yield gaps typically > 1.7 t/ha or 50% of the water-limited yield, it is important to investigate the degree to which this gap may be attributable to (rational) subprofit-maximising input levels in response to risk and risk aversion in many major grain-growing regions, particularly those with lower and more variable rainfall. Here, we use a set of 14 case study sites across the Australian wheatbelt to examine the risk-return profile of several agronomic management practices and show the extent to which the farmers' risk attitude determines their decision-making. Using a novel profit-risk-utility framework that incorporates crop simulation, probability theory, finance techniques and risk-aversion analysis, we were able to better demonstrate how farmers might select practices that manage economic risk across sites ranging from low to high rainfall. Results varied with risk preference and yield potential. However, there are real opportunities to close the yield gap by adopting non-limiting or near non-limiting nitrogen fertiliser practices and controlling fallow weeds. We show for the first time that yields associated with current best practice can be surpassed for most levels of risk aversion by adopting an emergent practice of optimising the site-specific time of sowing and matching variety to time of sowing. For some sites and risk profiles, the emerging best practice package which includes additional N fertiliser is also profitable under risk. We also propose a modified integrated framework for yield gaps. Here, we distinguish allocative input constrains due to risk aversion from those due to access to resources, and we account for an innovation gap where the current agronomic frontier is shifted upwards by growers successfully, implementing new technologies that are not yet part of current best practice. [ABSTRACT FROM AUTHOR]

Empirical yield estimation from satellite data has long lacked suitable combinations of spatial and temporal resolutions. Consequently, the selection of metrics, i.e., temporal descriptors that predict grain yield, has likely been driven by practicality and data availability rather than by systematic targetting of critically sensitive periods as suggested by knowledge of crop physiology. The current trend towards hyper-temporal data raises two questions: How does temporality affect the accuracy of empirical models? Which metrics achieve optimal performance? We followed an in silico approach based on crop modelling which can generate any observation frequency, explore a range of growing conditions and reduce the cost of measuring yields in situ. We simulated wheat crops across Australia and regressed six types of metrics derived from the resulting time series of Leaf Area Index (LAI) against wheat yields. Empirical models using advanced LAI metrics achieved national relevance and, contrary to simple metrics, did not benefit from the addition of weather information. This suggests that they already integrate most climatic effects on yield. Simple metrics remained the best choice when LAI data are sparse. As we progress into a data-rich era, our results support a shift towards metrics that truly harness the temporal dimension of LAI data. [ABSTRACT FROM AUTHOR]

Achieving sustainable global food security for a rapidly growing world population is one of the greatest challenges of our time. Producing more food efficiently by closing the yield gaps is regarded as a promising solution to address this challenge without further expanding farming land. However, there is limited understanding of the causes contributing to yield gaps. The present study aimed to comprehensively examine three dimensions of the causes for the wheat yield gaps in Australia: farm management practices, farm characteristics and grower characteristics. Computer-assisted telephone interviews of 232 wheat producers from 14 contrasting local areas were conducted. The data collected on these three dimensions were used to develop a comprehensive framework to understand causes of yield gaps. Results reveal significant differences between farms with smaller yield gaps and those with greater yield gaps in relation to farming management as well as farm and grower characteristics. Findings further underline that farms with smaller yield gaps are likely to be smaller holdings growing less wheat on more favourable soil types, are more likely to apply more N fertiliser, to have a greater crop diversity, to soil-test a greater proportion of their fields, to have fewer resistant weeds, to adopt new technologies, and are less likely to grow wheat following either cereal crops or a pasture. They are more likely to use and trust a fee-for-service agronomist, and have a university education. The dynamic relationships between grower characteristics and farm management practices in causing yield gaps are further highlighted through a path analysis. This study is the first to demonstrate that yield gaps are the result of the intertwined dynamics between biophysical factors, grower socio-psychological characteristics and farm management practices. Socio-psychological factors not only directly contribute to yield gaps, but they also influence farm management practices that in turn contribute to yield gaps. Our findings suggest that, to close wheat yield gaps, it is important to develop integrated strategies that address both socio-psychological and farm management dimensions. [ABSTRACT FROM AUTHOR]