Global Cropping Systems Research Articles

Fertilizer dependency: a new indicator for assessing the sustainability of agrosystems beyond nitrogen use efficiency

Cropping systems depend on external nitrogen (N) to produce food. However, we lack metrics to account for society’s fertilizer dependency, although excessive increases in N application damage human and environmental health. The objective of this study is to propose a novel indicator, N fertilizer dependency, calculated as the ratio between human-controllable external inputs and total N inputs. Nitrogen fertilizer dependency has a solid mathematical base being derived from closing the nitrogen use efficiency (NUE) equation. This study also tests the value of the N fertilizer dependency concept at the cropping system (plant-soil) scale and at different spatial scales, from field to country, as a complementary indicator to promote sustainable production. The field experiments conducted with grain cereals as a main crop showed that when replacing the barley precedent crop with a legume, N fertilizer dependency accounted for soil legacy and was reduced by 15% in fertilized treatments. In a farm population, N fertilizer dependency ranged from 47 to 95% and accounted for the relevance of biological fixation and irrigation water N inputs, adding pertinent information to performance indicators (i.e., NUE). At the country scale, N fertilizer dependency showed different temporal patterns, depending mainly on the relevance of biological atmospheric N fixation. Nitrogen fertilizer dependency of global cropping systems has risen to ≈83% in the last five decades, even though the N exchange among regions has increased. Nitrogen fertilizer dependency has great potential to monitor the achievements of efforts aiming to boost system autonomy, and within similar agricultural systems, it can be used to identify practices that lead to a reduction of fertilizer needs. In summary, N fertilizer dependency is a new indicator to evaluate the agroenvironmental sustainability of cropping systems across the scales and provides a complementary dimension to the traditional indicators such as NUE, N output, and N surplus.

Responses of soil aggregation and aggregate‐associated nitrogen to straw return in China: Evidence from a meta‐analysis and a pot experiment

AbstractEnhancing soil structure and soil nitrogen availability is the key to sustainable agricultural development in global cropping systems. Straw return can affect soil aggregation, but the results of recent studies on the influence of straw return on soil aggregation are not consistent, and the distribution and availability of straw‐derived nitrogen in soils are still unclear. Here, a meta‐analysis of the effects of straw return on soil aggregation was conducted based on 57 studies published in China over the past 10 years. Moreover, combined with a pot experiment, the distribution and transfer characteristics of the two main wheat (Triticum aestivum L.)‐preceding crops, corn (Zea mays L.) and soybean (Glycine max L.) straw‐derived nitrogen in the soils were studied by using the 15N‐tracer method in the main wheat‐producing areas of China. 15N‐labeled straw was introduced into soils in pots at rates of 0.3% and 0.5% of the soil dry mass and incubated 60%–70% of the field water capacity throughout the entire growth period of wheat (220 days). A meta‐analysis revealed that straw return significantly improved the mass ratio of large macro‐aggregates (LM%) and small macro‐aggregates (SM%) but significantly decreased the mass ratio of micro‐aggregates (MI%) and silt plus clay‐size particles (CS%), with mean effect sizes of 36.27%, 9.06%, −8.26%, and −21.32%, respectively. The mean weight diameter (MWD) and geometric mean diameter (GMD) also increased by 21.48% and 15.64%, respectively. Compared with SM%, LM% made a greater contribution to the stability of soil aggregates. Moreover, only LM% showed a significant positive correlation with the corresponding aggregate‐associated nitrogen content, which was an important reason for the improvement in soil nitrogen availability after straw return. The positive effect of straw return on soil aggregation was greatest when the soil pH was close to 6.5–7.5, the average annual temperature was greater than 15°C, and the average annual rainfall was close to 800–1000 mm. The results of the pot experiment revealed that the proportions of straw‐derived nitrogen in >2 mm aggregates were 1.21–1.28, 1.50–2.23, and 1.34–1.74 times greater than those in 0.25–2, 0.053–0.25, and <0.053 mm aggregates, respectively. Moreover, the proportion of straw‐derived nitrogen content of aggregates of different particle sizes showed that the proportion of straw used to reach 0.5% of the soil dry weight was greater than 0.3%, which was 1.09–1.66 times greater, and that of soybean straw was significantly greater than that of corn straw, which was 1.50–2.28 times greater. At application rates of 60 g pot−1 and 100 g pot−1 straw, the absorption of soybean straw‐derived nitrogen by wheat was 1.83 and 2.15 times greater than that of corn straw‐derived nitrogen, respectively. In conclusion, straw return effectively improved soil aggregate stability and nitrogen availability, which was closely related to the increase in soil LM%. Soybean straw can stabilize soil aggregates better than corn straw, and its straw‐derived nitrogen is an important nitrogen source for subsequent wheat crops.

Challenging glyphosate resistance EPSPS P106S and TIPS mutations with soybean competition and glyphosate: implications for management.

Eleusine indica (L.) Gaertn. (goosegrass) is a major weed in global cropping systems. It has evolved resistance to glyphosate due to single Pro-106-Ser (P106S) or double Thr-102-Ile + Pro-106-Ser (TIPS) EPSPS target site mutations. Here, experiments were conducted to evaluate the single effect of soybean competition and its combined effect with a glyphosate field dose (1080 g ae ha-1 ) on the growth and fitness of plants carrying these glyphosate resistance endowing target site mutations. TIPS E.indica plants are highly glyphosate-resistant but the double mutation endows a substantial fitness cost. The TIPS fitness penalty increased under the effect of soybean competition resulting in a cost of 95%, 95% and 96% in terms of, respectively, vegetative growth, seed mass and seed number investment. Glyphosate treatment of these glyphosate-resistant TIPS plants showed an increase in growth relative to those without glyphosate. Conversely, for the P106S moderate glyphosate resistance mutation, glyphosate treatment alone reduced survival rate, vegetative growth, aboveground biomass (34%), seed mass (48%) and number (52%) of P106S plants relative to the glyphosate nontreated plants. However, under the combined effects of both soybean competition and the field-recommended glyphosate dose, vegetative growth, aboveground biomass, seed mass and number of P106S and TIPS plants were substantially limited (by ≤99%). The ecological environment imposed by intense competition from a soybean crop sets a significant constraint for the landscape-level increase of both the E.indica single and double glyphosate resistance mutations in the agroecosystem and highlights the key role of crop competition in limiting the population growth of weeds, whether they are herbicide-resistant or susceptible. © 2022 Society of Chemical Industry.

Different soil particle size changes the 15N retention in soil and 15N utilization by maize

Improving soil structure is key to improving soil quality and nitrogen utilization efficiency (NUE) in global cropping systems. Soil sieving is a direct means of dividing soil activity into components with different practical functional significance. In order to have a more intuitive understanding of nutrient turnover and NUE under different soil particle sizes, we identified the key soil particle sizes that affect N cycling in cropping systems. An in-situ field experiment was conducted in Mollisol for three years using the 15N isotope tracer technique to examine the effect of soil structure on maize growth, nutrient uptake, and 15NUE. We artificially destructed the soil structure by sieving it into four particle size classes: (i) unsieved soil (CK), (ii) <0.5 mm size (A), (iii) 0.5–2 mm size (B), and (iv) 2–5 mm size (C). Then each year, the physical properties of the soil, 15N loss and retention rate (15NRR), the 15NUE, 15N absorption, and distribution, as well as maize growth and yield, were measured. The results showed that the 0.5–2 mm size (B) and 2–5 mm size (C) improved soil physical properties and increased the uptake of 15N by maize (especially in the leaves and grains), thereby increasing maize yield. The B and C particle sizes had lower soil 15NRR and higher alkaline hydrolysable N content than the other treatments in the depth. We concluded that the B sieving treatment is the key aggregate fraction to increasing maize 15NUE and yield and minimizing the negative effects on soil N retention capacity. Furthermore, the B treatment is key to affecting crop nutrient absorption and utilization.

Harvest weed seed control: impact on weed management in Australian grain production systems and potential role in global cropping systems

The introduction of harvest weed seed control (HWSC) techniques and associated machinery has enabled the routine use of an alternative weed control technology at a novel weed control timing in global grain cropping fields. Driven by the significant threat of widespread populations of annual ryegrass (Lolium rigidum) with multiple-herbicide resistance, in the 1990s Australian growers and researchers developed techniques to target, at grain harvest, the seed production of annual ryegrass and other important weed species. The HWSC approach to weed management is now routinely used by a majority of Australian grain producers as an integral component of effective weed control programs. Here we detail the development and introduction of current HWSC systems and describe their efficacy in Australian grain production systems. The use of HWSC has likely contributed to lower annual ryegrass population densities and thus mitigated the impacts of herbicide resistance as well as slowing further evolution of resistance. In addition, low weed densities enable the introduction of site-specific weed control technologies and the opportunity to target specific in-crop weeds with non-selective alternative weed control techniques. With an awareness of the evolutionary potential of weed species to adapt to all forms of weed control, there is an understanding that HWSC treatments need to be judiciously used in grain cropping systems to ensure their ongoing efficacy. The successful use of Australian developed HWSC systems has attracted global interest and there is now a considerable international research effort aimed at introducing this alternative weed control approach and timing into the world’s major cropping systems.

Funneliformis mosseae Improves Growth and Nutrient Accumulation in Wheat by Facilitating Soil Nutrient Uptake under Elevated CO2 at Daytime, Not Nighttime.

The concurrent effect of elevated CO2 (eCO2) concentrations and arbuscular mycorrhizal fungi (AMF) on plant growth, carbon (C), nitrogen (N), phosphorus (P) and potassium (K) accumulations in plant and soil is largely unknown. To understand the mechanisms of eCO2 and mycorrhization on wheat (Triticum aestivum) performance and soil fertility, wheat seedlings were grown under four different CO2 environments for 12 weeks, including (1) ambient CO2 (ACO2, 410/460 ppm, daytime/nighttime), (2) sole daytime eCO2 (DeCO2, 550/460 ppm), (3) sole nighttime eCO2 (NeCO2, 410/610 ppm), and (4) dual or continuous daytime/nighttime eCO2 ((D + N)eCO2, 550/610 ppm), and with or without AMF (Funneliformis mosseae) colonization. DeCO2, NeCO2 and (D + N)eCO2 generally significantly increased shoot and root biomass, plant C, N, P and K accumulation, soil invertase and urease activity, but decreased shoot and root N, P and K concentrations, and soil available N, P and K. Compared with non-AMF, AMF effects on above-mentioned characteristics were significantly positive under ACO2, DeCO2 and (D + N)eCO2, but negative on plant biomass, C, N, P and K accumulation under NeCO2. Overall, AMF colonization alleviated soil nutrient constraints on plant responses to DeCO2, while NeCO2 decreased AMF’s beneficial effects on plants. These results demonstrated that an integration of AMF’s benefits to plants under factual field DeCO2 and/or NeCO2 will be critical for managing the long-term consequence of future CO2 rising on global cropping systems.

The adaptive value of flowering time in wild radish (Raphanus raphanistrum)

AbstractHarvest weed seed control (HWSC) is a weed management technique that intercepts and destroys weed seeds before they replenish the soil weed seedbank and can be used to control herbicide-resistant weeds in global cropping systems. Wild radish (Raphanus raphanistrum L.) is a problematic, globally distributed weed species that is considered highly susceptible to HWSC, as it retains much of its seed on the plant during grain harvest. However, previous studies have demonstrated that R. raphanistrum is capable of adapting its life cycle, in particular its flowering time, to allow individuals more time to mature and potentially shed seeds before harvest, thereby evading HWSC interception. This study compared the vegetative growth plus physiological and ecological fitness of an early-flowering R. raphanistrum biotype with an unselected genetically related biotype to determine whether physiological costs of early flowering exist when in competition with wheat (Triticum aestivum L.). Early flowering time adaptation in R. raphanistrum did not change the relative growth rate or competitive ability of R. raphanistrum. However, the height of first flower was reduced in the early flowering time–selected population, indicating that this population would retain more pods below the typical harvest cutting height (15 cm) used in HWSC. The presence of wheat competition (160 to 200 plants m−2) increased flowering height in the early flowering time–selected population, which would likely increase the susceptibility of early-flowering R. raphanistrum plants to HWSC. Overall, early-flowering adaption in R. raphanistrum is a possible strategy to escape being captured by the HWSC; however, increasing crop competition is likely to be an effective strategy to maintain the effectiveness of HWSC.

Canopy photosynthesis of six major arable crops is enhanced under diffuse light due to canopy architecture.

Diffuse radiation generally increases photosynthetic rates if total radiation is kept constant. Different hypotheses have been proposed to explain this enhancement of photosynthesis, but conclusive results over a wide range of diffuse conditions or about the effect of canopy architecture are lacking. Here, we show the response of canopy photosynthesis to different fractions of diffuse light conditions for five major arable crops (pea, potato, wheat, barley, rapeseed) and cover crops characterized by different canopy architecture. We used 13years of flux and microclimate measurements over a field with a typical 4year crop rotation scheme in Switzerland. We investigated the effect of diffuse light on photosynthesis over a gradient of diffuse light fractions ranging from 100% diffuse (overcast sky) to 11% diffuse light (clear-sky conditions). Gross primary productivity (GPP) increased with diffuse fraction and thus was greater under diffuse than direct light conditions if the absolute photon flux density per unit surface area was kept constant. Mean leaf tilt angle (MTA) and canopy height were found to be the best predictors of the diffuse versus direct radiation effect on photosynthesis. Climatic factors, such as the drought index and growing degree days (GDD), had a significant influence on initial quantum yield under direct but not diffuse light conditions, which depended primarily on MTA. The maximum photosynthetic rate at 2,000µmolm-2 s-1 photosynthetically active radiation under direct conditions strongly depended on GDD, MTA, leaf area index (LAI) and the interaction between MTA and LAI, while under diffuse conditions, this parameter depended mostly on MTA and only to a minor extent on canopy height and their interaction. The strongest photosynthesis enhancement under diffuse light was found for wheat, barley and rapeseed, whereas the lowest was for pea. Thus, we suggest that measuring canopy architecture and diffuse radiation will greatly improve GPP estimates of global cropping systems.

Opportunities and challenges for harvest weed seed control in global cropping systems.

The opportunity to target weed seeds during grain harvest was established many decades ago following the introduction of mechanical harvesting and the recognition of high weed-seed retention levels at crop maturity; however, this opportunity remained largely neglected until more recently. The introduction and adoption of harvest weed seed control (HWSC) systems in Australia has been in response to widespread occurrence of herbicide-resistant weed populations. With diminishing herbicide resources and the need to maintain highly productive reduced tillage and stubble-retention practices, growers began to develop systems that targeted weed seeds during crop harvest. Research and development efforts over the past two decades have established the efficacy of HWSC systems in Australian cropping systems, where widespread adoption is now occurring. With similarly dramatic herbicide resistance issues now present across many of the world's cropping regions, it is timely for HWSC systems to be considered for inclusion in weed-management programs in these areas. This review describes HWSC systems and establishing the potential for this approach to weed control in several cropping regions. As observed in Australia, the inclusion of HWSC systems can reduce weed populations substantially reducing the potential for weed adaptation and resistance evolution. © 2017 Society of Chemical Industry.

An analysis of methodological and spatial differences in global cropping systems models and maps

AbstractAimAgricultural practices have dramatically altered the land cover of the earth, but the spatial extent and intensity of these practices is often difficult to catalogue. Information on the distribution and performance of specific crops is often only available through national or subnational statistics. Recently, however, there have been multiple independent efforts to incorporate the detailed information available from statistical surveys with supplemental spatial information to produce a spatially explicit global dataset specific to individual crops. While these datasets provide decision makers with improved information on global cropping systems, the final global cropping maps differ substantially from one another. This study aims to explore and quantify systematic similarities and differences between four major global cropping systems products and the subsequent implications for analyses dependent on those models.LocationThis study was conducted at a global scale.MethodsEach global cropping systems model was assessed by latitude as a measure of biophysical plausibility and each pair of models was compared using a Gaussian filter to remove trivial spatial discrepancies. Model disagreement was explored in relation to the interdependent input data of each model pair with a particular focus on cropland extent. The influence of the observed model differences on subsequent analyses was demonstrated using model‐dependent estimates of the yield gap as an example.ResultsThe results of our analysis indicate that the choice of cropping systems model is non‐trivial: considerable differences exist between model‐specific estimates of the yield gap across nearly all climate zones and the average model difference exceeds the average estimated yield gap in certain regions. The differences in crop‐specific harvested area and yield products of each model are significant, and mostly result from differences in the input datasets and downscaling methodologies. In particular, the choice of dataset on cropland extent proved to be influential regardless of the downscaling process employed.Main conclusionsDiscrepancies in the final products of cropping systems models are currently poorly understood, but have implications for basic policy decisions relating to agricultural production and food security. The considerable disagreement between models serves as a reminder of the ongoing challenges to the creation of spatially explicit estimates of harvested area and yield based on crop statistics. Our analysis helps shed light on the importance of model choice by demonstrating the implications for further analyses that depend on cropping systems models, and works to overcome these challenges by characterizing model‐dependent differences in harvested area and yield.

A Comparative Analysis of Global Cropping Systems Models and Maps

Agricultural practices have dramatically altered the Earth’s land cover, but the spatial extent and intensity of these practices is often difficult to catalogue. Cropland accounts for nearly 15 million square kilometers of Earth’s land cover — amounting to 12 percent of the planet’s ice-free land surface — yet information on the distribution and performance of specific crops is often available only through national or subnational statistics. Although remote-sensing products offer spatially disaggregated information, those currently available on a global scale are ill suited for many applications due to the limited separation of crop types within the area classified as cropland. Recently, however, the field has seen multiple independent efforts to incorporate the detailed information available from statistical surveys with supplemental spatial information to produce a spatially explicit global dataset specific to individual crops for the year 2000. Although these datasets provide analysts and decision makers with improved information on global cropping systems, the final global cropping maps differ from one another substantially. This study aims to explore and quantify systematic similarities and differences between four major global cropping systems products: the dataset of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000), the spatial production allocation model (SPAM), the global agroecological zone (GAEZ) dataset, and the M3 dataset developed by Monfreda, Ramankutty, and Foley. The analysis explores not only the final cropping systems maps but also the interdependencies of each product, methodological differences, and modeling assumptions, which will provide users with information vital for discerning between datasets in selecting a product appropriate for each intended application.