Elsevier

Agricultural Systems

Volume 184, September 2020, 102896
Agricultural Systems

Cropping system yield gaps can be narrowed with more optimal rotations in dryland subtropical Australia

https://doi.org/10.1016/j.agsy.2020.102896Get rights and content

Highlights

  • This research has produced the first regional-scale maps of cropping systems yield gaps.

  • Productivity of cropping in Australia's subtropical grain zone is only 34% of its potential.

  • Profit-risk trade-offs may be responsible for growers choosing less productive rotations.

  • These maps and trade-off charts may be useful to engage stakeholders about cropping system design.

Abstract

Closing the gap between yields currently achieved on farms and those that can potentially be achieved with best practice and current technology (the yield gap) is a key strategy to intensify grain production without expanding cropland. Much research has been done to quantify the yield gap of wheat, maize and rice globally and of wheat, barley, canola, sorghum and pulse crops in Australia. However, crops are grown in rotations (recurring crop sequences) that vary in their cropping intensities and in the diversity of their species. Little is known about yield gaps at the cropping system level, especially in regions where there are many possible combinations of crop types and fallow periods. This prompted us to investigate crop rotations in Australia's subtropical grains region where current crop rotations include winter and summer cropping with cereal, pulse and oilseed crops interspersed with fallow periods ranging from nil to 18 months duration. To determine the system level yield gaps, we simulated the water-limited yield potential of 26 locally practiced crop rotations for over 800 weather stations by up to 3 soil types per station. We captured the impact of climate variability with 30–35 years by 2–7 fields per rotation for each site. We expressed the results in terms of energy, protein and revenue per hectare per year and mapped the results of the optimal rotations over the cropping zone. Surprisingly, a single rotation (sorghum/fallow/mungbean/wheat/fallow/chickpea rotation; with 4 crops in 3 years, balanced between summer and winter crops and between cereal and pulse crops) was optimal for revenue over almost the whole subtropical grain zone. Using revenue as the metric for yield gaps at statistical local area scale we found, over the whole subtropical zone, a mean revenue gap of 970 $/ha/yr. This represents a relative revenue (Revenue% = 100 x (actual revenue/water-limited revenue)) of 34% which is much lower than expected from the 40–60% relative yields achieved by individual crops. We investigated whether growers may select rotations that have lower revenue than the optimal rotation in response to economic factors such as profit and risk. We found that for much of the area the same rotation that optimised revenue also optimised profit. However, for some of the cropping zone, particularly in the south western portion, a different, less intensive and more winter dominant, rotation was most profitable. Similarly, risk averse farmers may choose less productive and profitable rotations with less risk.

Introduction

Yield gap analyses of individual crops have been used to estimate opportunities to increase crop production and identify opportunities for sustainable intensification of crop production at field to global scales (van Ittersum et al., 2013; Fischer, 2015; Gobbett et al., 2017; van Ittersum et al., 2016). Using a standard protocol and a network of international collaborators, the Global Yield Gap Atlas has analysed and mapped 84% of the global maize, 70% of global rice and 45% of global wheat production areas (www.yieldgap.org, last accessed 24 December 2019). The protocol is predicated on a crop by crop analysis with the cropping system represented by the cropping intensity (number of crops per year) that is used to calculate yield potential. The yield gaps of all major crops in Australia have similarly been mapped (Hochman et al., 2016; www.yieldgapaustralia.com, last accessed 24 December 2019) with an assumed cropping intensity of one crop per year. However, while individual crops are grown in cropping systems (made up of crop sequences or crop rotations), little work has been carried out to understand the impact of choices growers make among these sequences or rotations on the yield gap of a cropping system rather than assuming that the overall yield gap is the sum of yield gaps of individual crops.

In China's Hebei Plain, where continuous wheat/maize cropping (with a cropping intensity of 2 crops per year) is the dominant cropping system, a survey of 362 farms in six counties found that the aggregate production of continuous wheat–maize crops grown in the 2004–2005 season averaged 14,105 kg/ha. That was 72% of the average production recorded from on-farm trials conducted in each of the six counties and 60% of the simulated average production potential for the Hebei Plain in the same season (Liang et al., 2011). An analysis of a number of alternatives to the wheat-maize cropping system on a site in the North China Plain showed that, under current growing conditions, sustainable groundwater use and improved water use efficiency could be achieved with 2 crops/year under a minimal irrigation system or with less intensive cropping systems under full irrigation. However, in all cases the current system was the most productive in terms of yields/ha/yr (Yan et al., 2020).

A yield frontier analysis of data from a detailed longitudinal survey of 94 farmers' fields over 7 seasons in Australia's subtropical grain zone was used to compare the productivity of individual crops with the productivity of crop rotations in these fields. Three production criteria were used to compare the crop rotations: revenue, metabolisable energy yield, and crude protein yields. While the revenue from 36% of the individual crops in the study was found to be more than 80% of their production frontier values, only 29% of whole crop rotations achieved this benchmark. Similar results were achieved when crops and Crop rotations were evaluated in terms of their metabolisable energy and crude protein yields. It was concluded in that study that in order to increase the agronomic efficiency of this portion of Australia's subtropical grain zone, attention should be focussed on the intensity and configuration of crop rotations and on the management of fallows in addition to the management of individual crops (Hochman et al., 2014).

More recently (Guilpart et al., 2017) defined the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. They identified two case study locations in Bangladesh where expected improvements in crop production from changes in cropping intensity were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. Similarly, in an Indonesian case study, additional yield benefits were identified from closing system gaps. However such opportunities may be limited by extra input requirements and/or increasing risk (Agus et al., 2019).

Yield gaps of individual crops are usually described in terms of grain yields. However, simply summing the yields of different crops to describe system production is not ideal for cropping systems with multiple crops that have different yield potentials and different intrinsic nutritional and market values (e.g. sorghum versus chickpea). Here we seek to evaluate crop rotations in terms of multiple production indicators such as energy, protein and revenue. Food energy production is a key indicator of global food security where global demand for food is routinely assessed in energy units. Once energy requirement is satisfied, attention shifts to nutritional value where protein content is a key indicator (FAO et al., 2019). However, higher food prices are associated with higher protein content and lower carbohydrate content such that the dollar values of crops tend to reflect their overall food value (Brooks et al., 2010). Hence, revenue which is a highly relevant measure of production to growers, is arguably also a useful integrator of the values of energy and protein (as well as oil) contents of crops.

To date there has been no attempt to map system yield potential, actual system yields and system yield gaps at regional or national scale. Here we present a cropping system yield gap analysis of the Subtropical Grain Zone of Australia. This region takes in central and southern Queensland through to northern New South Wales as far south as Dubbo. Most rainfall in this northern region tends to be over the summer months, allowing for dryland summer crop production, but with the high moisture-storing capacity of the clay-based soils of this region, supplemented by some winter rainfall, crops that grow during the winter are also successfully produced. Summer dominance of rainfall decreases from north to south while the average annual rainfall tends to decrease from east to west.

Here we evaluated all crop rotations in terms of productivity indicators such as energy, protein, revenue, profit and downside risk. An analysis of environmental indicators such as nitrate leached and greenhouse gas emissions was also conducted, and production-environment trade-offs were also investigated. These results will be presented in a subsequent publication. We expressed the system yield gap by comparing farmers' actual output, as expressed in the data on total revenue obtained from the production of all crops per Statistical Local Area (SA2), with the simulated revenue surface created from the rotation with the highest revenue of the 26 rotations at each of the weather stations and soil types in the cropping land use areas of the same SA2s. Additionally, we compared revenue, the production/food security indicator, against indicators of profit and risk imperatives to gain insights into why growers may deliberately choose crop rotations that result in less than optimal revenue.

Section snippets

Materials and methods

When designing crop rotations to suit their environments, growers make choices among several system “levers”, or strategic management decisions, available to them. These include system complexity (number of different crops in a rotation), cropping intensity (number of crops per year in a rotation), crop types (cereal crops, pulses, oil crops) and growing season (summer versus winter crops). Their rotations also need to accommodate considerations of weed management, build-up of crop diseases, as

Results and discussion

The twenty-six rotations selected from the focus group interviews (Table 2) are not comprehensive but represent current practice by “leading” growers in different parts of the subtropical cropping zone. These rotations exhibited a considerable degree of diversity in terms of the levers available to growers in designing these rotations. Average cropping intensity was 0.96 with a range of 0.5 to 1.33 crops per year; average crop diversity was 3.04 with a range of 2 to 4 crops per rotation. Winter

Conclusions

This study represents the first attempt to map yield gaps of cropping systems, rather than of individual crops. Crop production expressed as revenue per hectare per year in Australia's subtropical grain zone over a 28-year period (1988–2016) was found to be only 34% of the water limited potential of the optimal rotations in the same statistical local area. This revenue gap is much larger than implied by the sum of yield gaps of individual crops in the same cropping zone. This is a surprising

Declaration of Competing Interest

The authors declare no conflict of interest.

Acknowledgments

We are grateful for the support of the Chinese Academy of Sciences (CAS) and Commonwealth Scientific and Industrial Research Organisation of Australia (CSIRO) through the CAS-CSIRO collaborative project: “Improving crop yield potential under water and climatic constraints in the North China Plain and Australia's northern grain zone”. We also acknowledge the contribution of the Grains Research and Development Corporation (GRDC) Australia, through the Northern Farming Systems Project (CSA00050)

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