Sustainable Intensification Of Agricultural Systems Research Articles

Phosphorus fertiliser application and the subsequent cadmium input in three provinces along Yangtze River region of China

ABSTRACT This study has undertaken an analysis of phosphorus fertiliser use in three provinces from 2010 to 2020: Sichuan, Hubei and Jiangsu along the Yangtze River basin. It was revealed that phosphorus fertiliser application rate of Hubei experienced the most significant reduction, and the application rate of Sichuan was the lowest, but its yield of different crops hardly decreased. The yield for all food crops by Jiangsu was highest, indicating the importance of strong economic development on sustainable agriculture practice. Cd input for Hubei was highest. In Jiangsu, Xuzhou, Lianyungang, and Suqian are the three cities applying the most phosphorus fertiliser, which also happen to be the cities with lowest GDP. The findings of this research could provide useful insights into the current practice of phosphorus fertiliser application in the main rice planting regions of China and facilitate the optimal use of global sustainable intensification of agricultural systems.

Drift reduction in orchards through the use of an autonomous UAV system

The demands of a growing population and a developing global economy will require an increase in agricultural yield of 70% over the next 30 years. However, achieving this goal is only possible with a sustainable intensification of agricultural systems. Spraying drones are one of the available technologies that could help meet this goal. Presently, the use of spraying drones is limited by both the legal framework and the lack of scientific knowledge about the drift they generate compared to conventional terrestrial spraying platforms. However, the flexibility that spraying drones provide, their characteristic vertical spraying, and the downwash airflow produced by the rotors might reduce drift. This study aimed to compare the drift generated by a conventional orchard sprayer to that generated by a spraying drone in a commercial superhigh-density olive orchard. Trials to assess the sedimented drift of both spraying platforms were conducted in the South Iberian Peninsula in 2022. Our results show that the drone sprayer required less than half the distance to sediment 90% of the sprayed volume compared to a conventional mist blower.

Efficiency of assimilating leaf area index into a soybean model to assess within-field yield variability

Methods for accurately estimating within-field yield are essential to improve site-specific crop management and resource use efficiencies, which would be a major step toward sustainable intensification of agricultural systems. We set out to assess the accuracy of within-field soybean yields predicted by two data assimilation methods and to assess these methods’ assimilation efficiency (AE). Yields were estimated by assimilating remotely sensed leaf area index (LAI) data from Sentinel-2 into a soybean crop growth model on a pixel basis. The LAI data was integrated into the model by Ensemble Kalman Filtering (EnKF) or by recalibrating with the Subplex algorithm (recalibration-based). An open-loop setting which only integrates information on the soil layers was used as a baseline scenario for quantifying the AE. We assessed both data assimilation techniques on eight fields (3067 pixels) in the Corn Belt region (Nebraska, Kansas and Kentucky) in the United States. The data set encompassed substantial variation in crop growth conditions: three growing seasons (2018, 2019 and 2020), rainfed and irrigated fields, and early and late planting dates. Ground truth yield acquired from combine monitors was used to validate the yield estimations. Agreement between predicted and observed yield at pixel level was two times higher for both data assimilation methods compared to the open-loop. The root mean square error (RMSE) was 476 kg.ha−1 (RRMSE of 10 %) in the recalibration-based method and 573 kg.ha−1 (RRMSE of 12 %) in the EnKF-based method. For both data assimilation methods, assimilating the LAI improved predictions for 68 % of the pixels. For a further 12 % of pixels, there was no accuracy improvement. For the remaining 20 %, AE was positive for one of the two assimilation methods. The high proportion of pixels with positive AE indicates the potential for overcoming the limitations in applying crop models at high spatial resolution by integrating a crop growth indicator. Assimilating an in-season indicator of crop growth (LAI) into a soybean model made it possible to adjust the simulation pathway, thereby greatly improving the accuracy of the yield estimations at the pixel level. This study elucidates the practical applications of data assimilation strategies for fine-scale within-field crop yield mapping.

Global food crop redistribution reduces water footprint without compromising species diversity

Food crop yield and species diversity are critical for global population growth, undernourishment, and environmental burden. Crop redistribution is a practical solution to the sustainable intensification of agricultural systems by replacing existing crops with more suitable ones. Here we test this redistribution theory and its impacts on species diversity using six decades of data on the annual world production of 137 food crop products and their average water footprint (WFP). We find the global food crop effective species diversity had an increasing trend from 21 to 27 in recent six decades. Then, we develop a nutrient water footprint productivity index (WFPPI) to optimize crop distribution. Large calorie (+14%), mineral (+25%), and vitamin (+26%) production increases are possible from reshaping the global distribution of 100 crops within the current total WFP and area harvested. Wheat and paddy rice area can reduce by 31% and 34%, respectively, while increasing maize and soybean area by 18% and 40%, respectively. The global redistribution could feed an additional 866 million people while supplying 37% more than the caloric demand for the projected biofuel growth between 2020 and 2030 in the Net Zero Scenario. Such an optimization process does not entail a loss of crop species diversity. With a change of no more than 5%, the stability of the total area harvested for the four largest crops (wheat, maize, paddy rice, and soybeans) is critical for both production and species diversity of all crops. Our results suggest that global crop redistribution provides a promising solution to sustainable production.

Improved legume pastures increase economic value, resilience and sustainability of crop-livestock systems

CONTEXTWell-managed legume pastures play a crucial role in agricultural systems, contributing to strategies for the increasingly complex challenges of supplying meat and wool, improving soil fertility, increasing land use efficiency while minimising environmental impacts, and building system resilience. OBJECTIVEThis paper examines the potential for a range of improved annual legume pasture species to deliver multiple benefits such as extending the length of the growing the season and closing feed gaps, boosting crop yields and farm profits, and contributing to natural resource management. METHODSUsing MIDAS, a bioeconomic model of a crop-livestock farming system, we quantified the relative profitability and sustainability of five self-regenerating legume pasture scenarios − burr medic (Medicago polymorpha L.), bladder clover (Trifolium spumosum L.), French serradella (Ornithopus sativus L.), biserrula (Biserrula pelecinus L.) and common vetch (Vicia sativa L.) − against the baseline scenario of (mainly) subterranean clover (Trifolium subterraneum L.) for the medium-rainfall region of Western Australia. RESULTS AND CONCLUSIONSThe modelling indicated that profit gains of more than 25% were possible by using an improved self-regenerating legume option when compared to a subterranean clover-based pasture system. This could be achieved through greater utilisation of land under pastures and higher stocking rates while still maintaining a major cropping program. The whole-farm economic benefits of improved legume pastures resulted from land use adjustments to sustain more profitable cropping and livestock enterprises, and benefits were small at low stocking rates. The combination of additional feed at the start of the season and slower loss of energy values at the end of the season in the improved pasture scenarios was an important profit driver for the livestock enterprise. Other benefits included projected savings in nitrogen fertiliser for crops in rotation with the pasture, greater sheep carrying capacity, improved efficiencies in supplementary feed and labour costs per animal, lower groundwater recharge, and improved farm business resilience overall. Pastures with higher nutritional value could lead to reduced net emissions per DSE if they allow ruminants to reach finishing weight faster or improve reproductive efficiency. SIGNIFICANCEThis whole-farm study expands previous work by comparing a broad range of annual legume pasture species developed for the soils and climatic conditions of Western Australia. The general principles behind changes in land use revealed by the MIDAS modelling have wide application beyond this Australian region, confirming the potential role of well-managed legume pastures for achieving sustainable intensification of agricultural systems, while offering sufficient flexibility for grazing systems to cope with climate variability.

Development of a soil quality index for sequences with different levels of land occupation using soil chemical, physical and microbiological properties

The sustainable intensification of agricultural systems through crop rotations and/or the use of winter service crops can contribute to the diversification of the systems. This alteration of the surface layer creates conditions that favor an increase in the diversity of soil microbial communities, which improves the recovery capacity of the edaphic system, thereby contributing beneficial effects to plants, soil, and ecosystem. Our objectives were: 1) to evaluate the effect of crops sequences on soil chemical, physical and microbial parameters, and 2) to develop a soil quality index (SQI) from a minimum set of indicators for cropping sequences with different levels of land occupation. A long field experiment under no-tillage was established in 2006, where soil samples were collected during three agricultural seasons (2015, 2016, and 2017). We compared the effects of four different crop sequences that included soybean (S), maize (M) and wheat (W), and also incorporated wheat as a winter cover crop (CC), being S-S, CC/S, M-W/S, and W/S-CC/M. We found that sustainable management practices, crop rotation and inclusion of CC increased soil organic carbon. The highest basic infiltration rate and lowest penetration resistance values were found for double-cropped wheat/soybean-winter cover crop/maize (W/S-CC/M), the most intensified sequence. The average microbial biomass carbon level for soybean monoculture, was reduced by 32 % compared to maize-double-cropped wheat/soybean in the three agricultural seasons, while the metabolic coefficient in soybean monoculture and winter cover crop/soybean was significantly higher. In soybean monoculture, hydrolysis of fluorescein diacetate was decreased by 28.5 %, while dehydrogenase activity was increased by 43 % with respect to double-cropped wheat/soybean-winter cover crop/maize. The abundance of fungal and bacterial communities did not reveal significant variations between sequences by quantitative PCR analysis. The SQI was constructed by selecting a minimum set of indicators based on soil chemical, physical and microbial parameters. The parameters selected by the model were soil organic carbon, total organic nitrogen, basic infiltration rate, microbial respiration and hydrolysis of fluorescein diacetate, that revealed the differences among crop sequences in response to land occupation. The inclusion of different crops increased the SQI in comparison with soybean monoculture. The double-cropped wheat/soybean-winter cover crop/maize system improved the SQI by 73 % compared to soybean monoculture. Our findings show that crop sequences with high soil occupation improved their chemical and physical properties, as well as increasing the abundance and functionality of the microbial community, which is related to a better SQI.

Harnessing belowground processes for sustainable intensification of agricultural systems

Increasing food demand coupled with climate change pose a great challenge to agricultural systems. In this review we summarize recent advances in our knowledge of how plants, together with their associated microbiota, shape rhizosphere processes. We address (molecular) mechanisms operating at the plant–microbe-soil interface and aim to link this knowledge with actual and potential avenues for intensifying agricultural systems, while at the same time reducing irrigation water, fertilizer inputs and pesticide use. Combining in-depth knowledge about above and belowground plant traits will not only significantly advance our mechanistic understanding of involved processes but also allow for more informed decisions regarding agricultural practices and plant breeding. Including belowground plant-soil-microbe interactions in our breeding efforts will help to select crops resilient to abiotic and biotic environmental stresses and ultimately enable us to produce sufficient food in a more sustainable agriculture in the upcoming decades.

Integrating inductive and deductive analysis to identify and characterize archetypical social-ecological systems and their changes

Archetype analysis is a key tool in landscape and sustainability research to organize social-ecological complexity and to identify social-ecological systems (SESs). While inductive archetype analysis can characterize the diversity of SESs within a region, deductively derived archetypes have greater interpretative power to compare across regions. Here, we developed a novel archetype approach that combines the strengths of both perspectives. We applied inductive clustering to an integrative dataset to map 15 typical SESs for 2016 and 12 social-ecological changes (1999–2016) in Andalusia region (Spain). We linked these types to deductive types of human-nature connectedness, resulting in a nested archetype classification. Our analyses revealed combinations of typical SESs and social-ecological changes that shape them, such as agricultural intensification and peri-urbanization in agricultural SESs, declining agriculture in natural SESs or population de-concentration (counter-urbanization) in urban SESs. Likewise, we identified a gradient of human-nature connectedness across SESs and typical social-ecological changes fostering this gradient. This allowed us to map areas that face specific sustainability challenges linked to ongoing regime shifts (e.g., from rural to urbanized systems) and trajectories towards social-ecological traps (e.g., cropland intensification in drylands) associated with decreasing human-nature connectedness. This provides spatial templates for targeting policy responses related to the sustainable intensification of agricultural systems, the disappearance of traditional cropping systems and abandonment of rural lands, or the reconnection of urban population with the local environment, among others. Generally, our approach allows for different levels of abstraction, keeping regional context-specificity while linking to globally recognisable archetypes, and thus to generalization and theory-building efforts.

Towards optimal use of phosphorus fertiliser

Because phosphorus (P) is one of the most limiting nutrients in agricultural systems, P fertilisation is essential to feed the world. However, declining P reserves demand far more effective use of this crucial resource. Here, we use meta-analysis to synthesize yield responses to P fertilisation in grasslands, the most common type of agricultural land, to identify under which conditions P fertilisation is most effective. Yield responses to P fertilisation were 40–100% higher in (a) tropical vs temperate regions; (b) grass/legume mixtures vs grass monocultures; and (c) soil pH of 5–6 vs other pHs. The agronomic efficiency of P fertilisation decreased for greater P application rates. Moreover, soils with low P availability reacted disproportionately strong to fertilisation. Hence, low fertiliser application rates to P-deficient soils result in stronger absolute yield benefits than high rates applied to soils with a higher P status. Overall, our results suggest that optimising P fertiliser use is key to sustainable intensification of agricultural systems.

Sustainable Intensification of Rice-Based Systems with Potato in Eastern Indo-Gangetic Plains

In many parts of Asia food security and poverty remain issues even though arable land is available to produce nutritious food. Sustainable intensification of agricultural systems has been proposed to produce more outputs on same land area whilst minimizing environmental degradation. Tradeoffs, however, are inevitable and evidence thereof is scant. In this study, we analyze effects of sustainable intensification of rice-based systems with potato and focus on the Eastern Indo-Gangetic Plains of India and Bangladesh. A literature review, expert consultation, and an economic surplus exercise are used to address our objective. We find that sustainable intensification has a huge potential and positive welfare effects. Socio-economic tradeoffs, especially for labour, need to be considered and balanced out. Increasing input efficiency for instance by improving farming practices may reduce negative environmental effects.

Modelling crop diversification and association effects in agricultural systems

The need to redesign more sustainable agricultural systems able of producing more, especially through intercropping or agroforestry, cannot be achieved without taking into account the essential aspect of production variability. Yet, although many studies have focused on the effect of intercropping on overall production, the particular issue of production variability in such systems remains relatively unstudied. The approach we propose, for a shift towards sustainable intensification of agricultural systems, considers the dual dimensions of yield and risk in a combined framework for the assessment and the comparison of two diversification strategies: (i) a simple diversification strategy (SDS) considered as an increasing number of crops grown on separate plots within a farm and (ii) an intercropping strategy (IC) considered as a within-plot increased diversity, where more than one species is grown at the same time and place. The two perspectives examined here were Modern Portfolio Theory and Land Equivalent Ratio. The former quantifies the effect of diversification on risk, the latter measures the effect of association on production. This research merges both approaches in a combined framework in order to assess intercropping system performances. By applying our framework to cases selected from the literature, we explored and compared the potential benefits of these two strategies in terms of yield and risk. Results showed that intercropping, in addition to being interesting with regard to yield, can have an additional risk reduction effect compared to a simple diversification strategy. Conversely, some crop mixtures maintained or even increased yield variability. Our work contributes to a better understanding of the possible impacts of diversification strategies on trade-offs between yield and risk, but also underlines the importance of taking yield variability into account in further studies.

Global assessment of agricultural system redesign for sustainable intensification

The sustainable intensification of agricultural systems offers synergistic opportunities for the co-production of agricultural and natural capital outcomes. Efficiency and substitution are steps towards sustainable intensification, but system redesign is essential to deliver optimum outcomes as ecological and economic conditions change. We show global progress towards sustainable intensification by farms and hectares, using seven sustainable intensification sub-types: integrated pest management, conservation agriculture, integrated crop and biodiversity, pasture and forage, trees, irrigation management and small or patch systems. From 47 sustainable intensification initiatives at scale (each >104 farms or hectares), we estimate 163 million farms (29% of all worldwide) have crossed a redesign threshold, practising forms of sustainable intensification on 453 Mha of agricultural land (9% of worldwide total). Key challenges include investment to integrate more forms of sustainable intensification in farming systems, creating agricultural knowledge economies and establishing policy measures to scale sustainable intensification further. We conclude that sustainable intensification may be approaching a tipping point where it could be transformative.

Sustainable intensification of agricultural systems in Iran for adaptation to climate change: opportunities and challenges

Sustainable intensification of agricultural systems in Iran for adaptation to climate change: opportunities and challenges

Agronomic and environmental causes of yield and nitrogen use efficiency gaps in Chinese rice farming systems

Abstract Yield (YG) and nitrogen use efficiency (NUE) gap analysis is a key tool in addressing the sustainable intensification of agricultural systems. Distinguishing and quantifying the underlying agronomic and environmental causes of these gaps is as important as estimating their magnitude. We applied a field experimental framework that allowed us to partition YGs and NUE gaps due to crop management, climatic factors and/or inherent soil productivity. YG and NUE gaps were determined as the differences between yields and NUE under standard farm practices and the attainable yield and NUE using optimum management practices. In farmer’s fields in China, the rice YG and NUE gap (expressed as the partial factor productivity of applied N, namely kg rice grain per kg fertilizer N applied, PFPN) averaged 1900 kg ha−1 and 18 kg kg−1, respectively. However, both were subject to large variability within and across different rice farming systems in response to key agronomic and environmental variables, with larger gaps in moderate- and low-yielding fields and in single rice systems. Management practices such as optimizing N and water management and increasing rice transplanting density simultaneously narrowed the YG by 38% and the NUE gap by 39% on average. Climatic- (YG-C) and inherent soil productivity-based YGs (YG-S), which represented fractions of YG derived from climate and soil variability, accounted for on average 16% and 38% of the total YG across low- and moderate-yielding fields in single rice systems, and by 14% and 27% in early and 11% and 20% in late rice farming systems, respectively. Growing-degree days (GDD) for early rice and daily minimum temperature (TMIN) for late rice were the best predictors of YG-C. For single rice in the Yangtze Delta, YG-C included multiple factors such as lower daily mean temperature and GDD, and higher daily maximum temperatures and precipitation during rice growing periods. Soil nutrient supplying capacity was partially responsible for YG-S in those under-performing fields. Significant and exploitable potential exists for increasing rice productivity with higher NUE, especially in moderate- and low-yielding fields. However, national and regional agricultural policies should place more emphasis on supporting good agronomy and soil management, thus moving towards a soil-climate smart management approach in rice farming systems.

Development of the first consensus genetic map of intermediate wheatgrass (Thinopyrum intermedium) using genotyping-by-sequencing.

Development of the first consensus genetic map of intermediate wheatgrass gives insight into the genome and tools for molecular breeding. Intermediate wheatgrass (Thinopyrum intermedium) has been identified as a candidate for domestication and improvement as a perennial grain, forage, and biofuel crop and is actively being improved by several breeding programs. To accelerate this process using genomics-assisted breeding, efficient genotyping methods and genetic marker reference maps are needed. We present here the first consensus genetic map for intermediate wheatgrass (IWG), which confirms the species' allohexaploid nature (2n=6x=42) and homology to Triticeae genomes. Genotyping-by-sequencing was used to identify markers that fit expected segregation ratios and construct genetic maps for 13 heterogeneous parents of seven full-sib families. These maps were then integrated using a linear programming method to produce a consensus map with 21 linkage groups containing 10,029 markers, 3601 of which were present in at least two populations. Each of the 21 linkage groups contained between 237 and 683 markers, cumulatively covering 5061cM (2891cM--Kosambi) with an average distance of 0.5cM between each pair of markers. Through mapping the sequence tags to the diploid (2n=2x=14) barley reference genome, we observed high colinearity and synteny between these genomes, with three homoeologous IWG chromosomes corresponding to each of the seven barley chromosomes, and mapped translocations that are known in the Triticeae. The consensus map is a valuable tool for wheat breeders to map important disease-resistance genes within intermediate wheatgrass. These genomic tools can help lead to rapid improvement of IWG and development of high-yielding cultivars of this perennial grain that would facilitate the sustainable intensification of agricultural systems.

Review of yield gap explaining factors and opportunities for alternative data collection approaches

Abstract Yield gap analysis is gaining increased scientific attention, as estimating and explaining yield gaps shows the potential for sustainable intensification of agricultural systems. Explaining yield gaps requires detailed information about the biophysical environment, crop management as well as farm(er) characteristics and socio-economic conditions in which farmers operate. However, these types of data are not always available, mostly because they are costly to collect. The main objective of this research is to assess data availability and data collection approaches for yield gap analysis, and to summarize the yield gap explaining factors identified by previous studies. For this purpose, a review of yield gap studies (50 agronomic-based peer-reviewed articles) was performed to identify the most commonly considered and explaining factors of the yield gap. Besides a global comparison, differences between regions, crops and methods were analysed as well. The results show that management and edaphic factors are more often considered to explain the yield gap compared to farm(er) characteristics and socio-economic factors. However, when considered, both farm(er) characteristics and socio-economic factors often explain the yield gap. Fertilization and soil fertility factors are the most often considered management and edaphic factors. In the fertilization group, factors related to quantity (e.g. N fertilizer quantity) are more often considered compared to factors related to timing (e.g. N fertilizer timing). However, when considered, timing explained the yield gap more often. Explaining factors vary among regions and crops. For example, while soil fertility is considered relatively much both in Africa and Asia, it is often explaining in Africa, but not in Asia. Agronomic methods like crop growth simulation models are often used for yield gap analysis, but are limited in the type and number of factors that can be included. Qualitative methods based on expert knowledge can include the largest range of factors. Although the data included in yield gap analysis also depends on the objective, knowledge of explaining factors, and methods applied, data availability is a major limiting factor. Bottom-up data collection approaches (e.g. crowdsourcing) involving agricultural communities can provide alternatives to overcome this limitation and improve yield gap analysis.

Sustainable intensification of agricultural systems in the Central African Highlands: The need for institutional innovation

This study identifies entry points for innovation for sustainable intensification of agricultural systems. An agricultural innovation systems approach is used to provide a holistic image of (relations between) constraints faced by different stakeholder groups, the dimensions and causes of these constraints, and intervention levels, timeframes and types of innovations needed. Our data shows that constraints for sustainable intensification of agricultural systems are mainly of economic and institutional nature. Constraints are caused by the absence, or poor functioning of institutions such as policies and markets, limited capabilities and financial resources, and ineffective interaction and collaboration between stakeholders. Addressing these constraints would mainly require short- and middle-term productivity and institutional innovations, combined with middle- to long-term NRM innovations across farm and national levels. Institutional innovation (e.g. better access to credit, services, inputs and markets) is required to address 69% of the constraints for sustainable intensification in the Central Africa Highlands. This needs to go hand in hand with productivity innovation (e.g. improved knowhow of agricultural production techniques, and effective use of inputs) and NRM innovation (e.g. targeted nutrient applications, climate smart agriculture). Constraint network analysis shows that institutional innovation to address government constraints at national level related to poor interaction and collaboration will have a positive impact on constraints faced by other stakeholder groups. We conclude that much of the R4D investments and innovation in the Central Africa Highlands remain targeting household productivity at farm level. Reasons for that include (1) a narrow focus on sustainable intensification, (2) institutional mandates and pre-analytical choices based project objectives and disciplinary bias, (3) short project cycles that impede work on middle- and long-term NRM and institutional innovation, (4) the likelihood that institutional experimentation can become political, and (5) complexity in terms of expanded systems boundaries and measuring impact.

Field Pennycress Production and Weed Control in a Double Crop System with Soybean in Minnesota

Sustainable intensification of agricultural systems has been suggested as a way to increase food, fiber, energy, and feed to meet future demands. Field pennycress (Thlaspi arvense L.) is proposed as a means for temporal intensification of agriculture, increasing profitability through oilseed production while providing needed cover to address soil and water quality issues. Field research was conducted across four environments in Minnesota to (i) evaluate pennycress planting date and seeding rate on pennycress and soybean [Glycine max (L.) Merr.] seed production and (ii) determine the role of pennycress systems as a weed management tool. Pennycress seeding rate had a direct effect on pennycress yield at Rosemount but not at Waseca or Lamberton locations. The use of a companion cover crop along with pennycress further reduced pennycress seed yield at Rosemount, but not Waseca or Lamberton suggesting that water availability is a key driver in pennycress productivity. The effect of pennycress and cover crops on soybean yield was also dependent on location. At Rosemount, soybean yield was reduced when pennycress was planted ahead of soybeans both years of the study while there was no effect of pennycress on soybean yield at Waseca. Although soybean yield was reduced at Rosemount, the combined pennycress and soybean seed yield was greater. This research shows the potential for a double cropping system of pennycress–soybean to increase overall seed yield and reduce early‐season weed pressure.