Sustainable Intensification Research Articles

Sustainable land management and implications on incomes, food self-sufficiency and women

The adoption of Sustainable Land Management (SLM) practices among smallholder farmers remains low, particularly among women farmers. Understanding the relationship between assets, gender, and SLM adoption and how their interaction impinges on household food self-sufficiency and livelihoods is essential for developing gender-responsive SLM programmes that effectively promote sustainable livelihoods and address household food insecurity. This study examines the effects of asset type on SLM practices adoption, women farmers, and their implications on household incomes and food self-sufficiency. Data was collected through a cross-sectional survey of 761 households selected from 11 chiefdoms across six districts in Eastern Zambia. Analysis involved Structural Equation System framework and Propensity Score Matching techniques to examine relationships between SLM adoption, food self-sufficiency, and household incomes, considering various socio-economic factors. Results showed marital status and household size as significant demographics, with education positively correlating with household income and SLM participation (p < 0.05). Gender disparities persisted, with male-headed households having higher incomes. Labour allocation analysis revealed women’s involvement in labour-intensive tasks, while smaller farms showed higher income probabilities, supporting sustainable agricultural intensification. Social capital significantly influenced SLM participation, and access to financial capital. Livestock assets, land size, and crop diversity predicted food security, while male decision-making influenced food security and income. Incomes were higher for women participating in SLM projects. This study underscores the importance of SLM practices in influencing household incomes and food security, especially for women. Addressing gender disparities and promoting women’s empowerment in agriculture are crucial for achieving equitable and sustainable rural development. Policymakers can foster sustainable livelihoods in rural communities by prioritizing SLM and empowering women.

Sustainable Intensification of Smallholder Farming Systems

Sustainable intensification of smallholder farming systems has emerged as a crucial strategy for addressing the dual challenges of food security and environmental sustainability in developing regions. This approach seeks to increase agricultural productivity on existing farmland while minimizing negative environmental impacts and ensuring the social and economic well-being of smallholder farmers. This article explores the principles, practices, and potential benefits of sustainable intensification within smallholder farming systems. By integrating improved agricultural techniques, such as agroecology, precision farming, and integrated pest management, with local knowledge and resources, sustainable intensification aims to enhance crop yields, soil health, and resource efficiency. The study also examines the barriers to adopting these practices, including limited access to technology, market constraints, and policy gaps, while highlighting the role of community engagement, education, and supportive policies in overcoming these challenges. Furthermore, the article discusses the implications of sustainable intensification for climate resilience and biodiversity conservation, emphasizing its potential to contribute to global efforts to achieve sustainable development goals. The findings suggest that with the right support and adaptation to local conditions, sustainable intensification can play a vital role in transforming smallholder farming systems into more productive, resilient, and sustainable sources of food and livelihoods.

Advanced prediction of rice yield gaps under climate uncertainty using machine learning techniques in Eastern India

The current study focuses on applying machine learning approaches to forecast future Kharif rice yield gaps in eastern India while accounting for climate change implications. To achieve the United Nations Sustainable Development Goals (SDGs), food security must be prioritized. Rice yield has been predicted using Cubist, GBM, MARS, RF, SVM, and XGB machine learning methods, considering six factors: elevation, soil moisture, precipitation, temperature, soil temperature, and actual evapotranspiration. Climatic change scenarios were generated using the latest climatic Coupled Model Intercomparison Project Phase 6 (CMIP6 MIROC6) Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP5-8.5 datasets between 1990 and 2030. Finally, machine learning algorithms were used to identify rice yield gaps to achieve sustainable agricultural intensification. The rice yield validation was completed with 1889 field-based farmer observation records. The results suggest that Murshidabad and Purba Bardhaman districts had very high rice yields (5.60–3.45 t/ha) when using the Cubist model compared to another model. The findings also reveal a poor rice-yielding zone (1.44–0.39 t/ha) in the western region (Purulia) and a northwestern region (half of the west of Birbhum). The Cubist and RF models' maximum and minimum R2 values were 0.73 and 0.72, respectively. The R2 values were also negligible for the XGB, GBM, SVM, and MARS, machine learning models. Projections for rice production in 2030 indicate that the northern and north-eastern regions (Murshidabad and Purba Bardhaman) as well as the southeastern areas (Jhargram and Paschim Medinipur) have the highest yields, categorized as extremely very high (5.56–3.49 t/ha) and high (3.49–2.49 t/ha). A significant rice yield gap (50-40 %) was found in the center and south-east areas (Bankura, Jhargram, and Paschim Medinipur), the northern region (Murshidabad and Birbhum), and the western region (Purulia). In 2030, the north-western region (Birbhum), as well as the middle and south-eastern regions (Bankura, Jhargram, and Paschim Medinipur districts), had the highest proportion of high (50%–40 %) and very high (60%–50 %) rice yield gap. Our findings can contribute to a new viewpoint on agricultural planning and management for sustainable growth in the face of changing climate circumstances.

People, Palms, and Productivity: Testing Better Management Practices in Indonesian Smallholder Oil Palm Plantations

More than 40% of the total oil palm area in Indonesia is owned and managed by smallholders. For large plantations, guidelines are available on so-called ‘best management practices’, which should give superior yields at acceptable costs when followed carefully. We tested a subset of such practices in a sample of smallholder plantations, aiming to increase yields and profitability. We implemented improved practices (weeding, pruning, harvesting, and fertiliser application) in 14 smallholder plantations of 13–15 years after planting in Jambi province (Sumatra) and in West-Kalimantan province (Kalimantan) for a duration of 3 to 3.5 years. During this period, we recorded yields, measured palm leaf parameters and analysed leaf nutrient contents. Yield recording then continued for an additional two years. In the treatment plots, the yields did not increase significantly, but the size of the bunches and the size of the palm leaves increased significantly and substantially. The tissue nutrient concentrations also increased significantly, although after three years, the potassium concentrations in the rachis were still below the critical value. Because of the absence of yield increase and the additional costs for fertiliser inputs, the net profit of implementing better management practices was negative, and ‘business as usual’ was justified financially. Some practices, such as harvesting at 10-day intervals and the weeding of circles and paths, were received positively by those farmers who could implement them autonomously, and were applied beyond the experiment. It is challenging to find and implement intensification options that are both sustainable and profitable, that have a substantial impact on yield, and that fit in the smallholders’ realities. On-farm experimentation and data collection are essential for achieving sustainable intensification in smallholder oil palm plantations.

Contextual realities in sustainable intensification: why do smallholder maize commercializing farmers in Eastern Uganda use sustainable intensification practices

Contextual realities in sustainable intensification: why do smallholder maize commercializing farmers in Eastern Uganda use sustainable intensification practices

Defoliation of Autumn Planted Maize Hybrids for Sustainable Intensification of Maize – Soybean Intercropping System

Defoliation of Autumn Planted Maize Hybrids for Sustainable Intensification of Maize – Soybean Intercropping System

Climate change will exacerbate land conflict between agriculture and timber production

Timber and agricultural production must both increase throughout this century to meet rising demand. Understanding how climate-induced shifts in agricultural suitability will trigger competition with timber for productive land is crucial. Here, we combine predictions of agricultural suitability under different climate change scenarios (representative concentration pathways RCP 2.6 and RCP 8.5) with timber-production maps to show that 240–320 Mha (20–26%) of current forestry land will become more suitable for agriculture by 2100. Forestry land contributes 21–27% of new agricultural productivity frontiers (67–105 Mha) despite only occupying 10% of the surface of the land. Agricultural frontiers in forestry land occur disproportionately in key timber-producing nations (Russia, the USA, Canada and China) and are closer to population centres and existing cropland than frontiers outside forestry land. To minimize crop expansion into forestry land and prevent shifting timber harvests into old-growth tropical and boreal forests to meet timber demand, emissions must be reduced, agricultural efficiency improved and sustainable intensification invested in.

Sustainable investigation and process intensification on the separation of ternary organic wastewater with heterogeneous characteristics

The tetrahydrofuran (THF)/water/n-propyl acetate (PROAC) mixture, which is categorized into class 2.0-2b-C, exhibits pressure-sensitive property along with heterogeneous regions in its phase diagram. Conventional pressure-swing distillations with different separation sequences (PSD-PTW, PSD-PWT) and a novel three-column heterogeneous azeotropic pressure-swing distillation (T-HAPSD) are designed to complete the separation. The PSD section of T-HAPSD combines three columns into two columns. The HAD section of T-HAPSD is more energy-efficient owing to the automatic separation in the decanter. T-HAPSD is more economical than conventional pressure-swing distillation. Heat integration and Self-heat recuperation technology (SHRT) are then introduced to reduce energy consumption and costs. Finally, the five processes are evaluated from four aspects (economy, energy, environment and exergy). The best of five processes is T-HAPSD-SHRT with 37.83% reduction in TAC, 51.17% reduction in TEC, 48.83% reduction in gas emissions and 52.63% reduction in exergy destruction when compared with PSD-PTW.

Impact of Sustainable Intensification of Coconuts Toward Women Farmer’s Empowerment in Sarmi Papua

Impact of Sustainable Intensification of Coconuts Toward Women Farmer’s Empowerment in Sarmi Papua

Management of maize-legume conservation agriculture systems rather than varietal choice fosters human nutrition in Malawi

Malawi smallholder farmers are facing climate-induced challenges that have increased food and nutrition insecurity in the country, thus sustainable intensification practices has been widely recommended. The objective of this study was to assess the effects of cropping systems with improved varieties on total system productivity and nutrition under different environments. The study involved on-farm experiments in ten communities in Central and Southern Malawi, incrementally established from 2005/2006 to 2018/2019 cropping seasons. Each community had six demonstration plots with three main treatments: conventional ploughing (CP): sole maize grown on seasonally constructed ridges and furrows; no-tillage (NT): sole maize grown on retained ridges with minimum soil disturbance and residue retained; and Conservation agriculture (CA): maize intercropped either cowpea, pigeon pea or groundnut on retained ridges as in NT. Our results show that total system nutrition was higher in CA treatments than NT and CP. The yields of maize were at least 800 kg ha−1 higher in CA and NT than CP despite the variety that was grown. Legume yields were also higher under CA and NT than CP. High protein yield was observed in CA systems (at least 100 kg ha−1 higher than CP) where maize and legume intercrops were rotated with grain legumes. Our results show nutrients and energy gains in CA and NT systems that can be invested in practices that increases the resilience of smallholder farmers to climate change. Conservation agriculture and NT systems have more influence on productivity of smallholder farms, despite the genotypes used (hybrids or OPVs).

Soil Organic Carbon Storage, Nitrous Oxide Emission and Net Climate Benefit of Conservation Agriculture: Insights from Two Long-Term Experiments in Zimbabwe

The slow increase in grain production in sub-Saharan Africa (SSA) is largely the result of cropland expansion rather than an increase in crop yields, which have been stagnantly low (< 1.5 t ha-1). Sustainable intensification of crop production is therefore needed to feed a growing population whilst minimizing negative impacts on the environment, biodiversity, and climate. Full accounting of the net global warming potential (GWP) of management practices can provide a holistic approach for identifying cropping systems that promote sustainable agriculture intensification to ensure food security whilst mitigating climate change.

The Value of Manure and Phosphorus Application to Unlock Immobilized Microbial Phosphorus for Sustainable Intensification of Maize in Zimbabwe

Microbial phosphorus (P) immobilization is a hidden challenge in most parts of sub-Saharan Africa. It affects crop establishment, growth, and response to mineral nitrogen (N) fertilizer application that ultimately reduces crop yields. This research highlighted that split application of N in combination with a medium rate (7 t ha-1) cattle manure and P fertilizer (>36 kg P ha-1) (an intensification pathway) reduced microbial immobilization and increased P uptake subsequently increasing root biomass productivity.

Correction: Kumar et al. Sustainable Intensification of Cropping Systems under Conservation Agriculture Practices: Impact on Yield, Productivity and Profitability of Wheat. Sustainability 2023, 15, 7468

Affiliation Update: [...]

Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth

Hyperspectral measurements can help with rapid decision-making and collecting data across multiple locations. However, there are multiple data processing methods (Savisky-Golay [SG], first derivative [FD], and normalization) and analyses (partial least squares regression [PLS], weighted k-nearest neighbor [KKNN], support vector machine [SVM], and random forest [RF]) that can be used to determine the best relationship between physical measurements and hyperspectral data. In the current study, FD was the best method for data processing and SVM was the best model for predicting average cotton (Gossypium spp. Malvaceae) height and nodes. However, the combination of FD and RF were best at predicting cotton leaf area index, canopy cover, and chlorophyll content across the growing season. Additionally, results from models developed by both SVM and RF were closely related to pseudo-CHIME satellite wavebands, where in-situ hyperspectral data were matched to the spectral resolutions of a future hyperspectral satellite. The information and results presented will aid producers and other members of the cotton industry to make rapid and meaningful decisions that could result in greater yield and sustainable intensification.

Structure, tree diversity, and aboveground carbon stocks of smallholder farms with push-pull technology in western Kenya

Push-pull technology is a companion cropping system whose success in soil fertility improvement and management of agricultural pests has been established in cereal-based systems. Push-pull has also been proposed as a template for the sustainable intensification of agriculture in Africa. However, the application of the technology has remained on a field scale and is restricted to cereal-based systems. Trees in agricultural landscapes are considered a strategy for climate change mitigation by storing carbon in soils and woody biomass. However, their potential has not been quantified in push-pull systems. This study characterized 45 smallholder farms in western Kenya to establish the land use categories within which push-pull is integrated, the diversity and structure of perennials on the farms, and the aboveground carbon stored within those farms. The area of each land use category varied depending on the size of the land use category on each farm. The amount of carbon stored in aboveground biomass was estimated using an existing allometric equation. This study found that trees are integrated on farms with push-pull in homesteads (45), cropland (38), woodlots (26), boundaries (4), and grazing land (2) farms. A total of 9159 trees from 97 different species were recorded over 34 ha. Farms in Vihiga and Kisumu had more trees (38 % and 37 % of all trees recorded) than those in Siaya (25 %). There were more trees in woodlots (total=4518) and homesteads (total=3327), and the least in grazing land (total=18). Overall, the highest species richness, Shannon, and Simpson diversity were observed in the homestead (86 species, H’=2.52 and D = 0.86). Farms in Kisumu, Vihiga, and Siaya stocked an average of 12.1, 9.4, and 7.3 Mg C ha−1 in aboveground biomass respectively. Variations were observed in land use categories, where woodlots had the greatest amount of carbon (55.5 Mg C ha−1) while grazing land had the least (2.4 Mg C ha−1). Eucalyptus spp., Grevillea robusta, and Markhamia lutea were the most dominant trees in abundance at 50 %, 16 %, and 11 % respectively. Conservation of trees on farms should be encouraged, as they protect biodiversity and store carbon thus contributing to climate change mitigation. This study's findings contribute to knowledge valuable to farmers and policymakers in making decisions on tree species and land use categories that have a high potential to sequester carbon in agroforestry systems.

Gender preferences for multiple attributes of soil and water conservation in Northern Rwanda

Despite the dominance of female labor in agricultural production, female-controlled farm plots have lower efficiency compared to plot managed by male-headed households, which indicates a huge gender disparity in agricultural productivity. Overlooking gender preferences when designing interventions that promote the conservation of soil and water resources might face challenges in adoption and could result in ineffective policies to close the gender gap. This study seeks to analyze gender-specific preferences regarding attributes of soil and water conservation (SWC) in northern Rwanda. A best-worst survey was conducted among 653 respondents, comprising 253 males and 400 females, representing 422 households surveyed between September and December 2019. The analysis of BWS data involved assessing attribute-level relative importance, Pearson correlation, and maximum difference scaling using multinomial logit (MNL). Findings from attribute-level importance analysis revealed significant gender-based disparities in preferences across three important SWC attribute scenarios: the high scenario (between 65 % and 100 %), the moderate scenario (between 50 % and 65 %), and the basic scenario (with <50 % relative importance). The study identified heterogeneity in preferences regarding the relative importance of SWC attribute levels. Pearson correlation analysis revealed substantial synergies among attribute levels linked to land consolidation, improved land tenure, and joint SWC decision-making between genders. Additionally, the study identified trade-offs among multiple levels of SWC attributes, including households' SWC decision-making and physical and structural measures. The results from MNL regression show that both males and females exhibit positive preferences for multiple levels of SWC attributes, but show negative preferences when it comes to household decisions involving multiple SWC strategies. The study highlights the importance of equal opportunities for males and females’ participation in agricultural transformation through the adoption of SWC technologies as a fundamental step towards sustainable agricultural intensification. It advocates for gender transformational approaches to incentivize the scaling up of SWC practices and promote packages with lower uptake rates. Additionally, the study suggests enhancing knowledge and extension education in SWC to better understand diverse needs and preferences of female farmers.

The LTAR Cropland Common Experiment at Eastern Corn Belt.

The Eastern Corn Belt (ECB) Long-Term Agroecosystem Research (LTAR) network site is one of the most agriculturally productive areas in the United States; however, nutrient and sediment losses from this region directly contribute to water quality impairment in both the Gulf of Mexico and Lake Erie. One of the largest challenges facing agricultural production in the ECB is water management, especially under a changing climate. Shifting precipitation patterns in combination with evolving infrastructure (i.e., tile drainage, irrigation) and management (i.e., crops planted; 4R nutrient management: source, timing, rate, and placement) in response to changing climate are likely to alter water quantity and quality and agricultural productivity. Through plot- and field-scale research, the ECB Common Experiment (CE) is focused on crop, soil, and water management to support sustainable agricultural intensification, with the goal of maximizing profitability, minimizing agriculture's environmental footprint, and enhancing ecosystem services. At both spatial scales, the CE aims to examine differences in water quantity and quality between the primary prevailing crop production system in the ECB (i.e., corn [Zea mays L.]-soybean [Glycine max L.] rotation, tillage prior to corn planting, free drainage, and fertility management consistent with tri-state recommendations) and an alternative system (e.g., adding small grains into the crop rotation, cover crops, limited phosphorus fertilizer, and drainage water management). Aligning producer and stakeholders needs with research objectives and long-term data collection, the ECB CE will tackle both ongoing and newly emerging research priorities and explore the effectiveness of conservation strategies to decrease nutrient and sediment losses from agricultural land.

Rethinking environmental sustainability in rainfed cropping systems

Activity data from a 30-year on-farm experiment with six soil-management treatments were used to develop inventory data for environmental partial life-cycle assessment (LCA). The purpose was to compare the treatments based on environmental outcomes and evaluate conservation agriculture (CA) in Australia's dryland cropping zone. Multiple trade-offs were revealed that highlight the need for a nuanced approach to sustainable intensification and show that rules-based CA is not sufficient to guarantee low greenhouse gas (GHG) emissions, nor low overall environmental impact. Nutrient mining in dryland cropping even under CA can lead to losses in soil carbon that can double GHG intensity. In these systems, additional nutrient inputs can reduce the loss of soil carbon as well as net GHG emissions, demonstrating the critical need to include the effects of soil carbon change in LCA to prevent perverse outcomes.The treatment involving strategic tillage and nutrient balancing, along with stubble retention, had the lowest GHG intensity, but there was a trade-off with the higher embedded impacts across several other environmental categories. Higher fertiliser input could lead to toxicity impacts, due to heavy-metal content, that contribute significantly to the Human health endpoint. However, limitations in modelling such local, site-specific impacts were considerable and more research is needed to address this.In general, trade-offs were found to exist between impacts from on-farm activities versus upstream manufacture of inputs; between GHG emissions and land use (yield) versus other environmental categories; and between different on-farm GHG emission sources. Despite these trade-offs, the treatments all had similar overall scores in the Human health and Ecosystems damage categories. There was no single treatment with low, or high, impact scores across all environmental indicators, indicating that trade-offs need to be carefully considered when making farm-management decisions in the context of net-zero or carbon-neutral farming.

Irrigation modernization in the Ebro – Aragón region of Spain: Past and future trends

Irrigation modernization has been analyzed in the part of the Aragón region within the Ebro River Basin, in northeastern Spain. A geodatabase was built with 1144 irrigation cartographical units (ICUs) adding up to 476 k ha with access to water and equipped with on-farm irrigation hardware. ICUs were classified in eight categories related to irrigation modernization. The classification revealed that in the past two decades an integral irrigation modernization was achieved in 103 k ha. In a second modernization, 13 k ha were transformed to reduce their dependence on grid energy. A third type of modernization, oriented to the digitalization of irrigation management processes, is only incipient at this time. Public investments in modernization during this period were estimated at 36.8 M€/year. This intense, publicly co-funded, policy-driven process will be far from sufficient to complete the modernization of all irrigated land in the study area in another twenty-year period. In a concurrent process, obsolete, socially unfavored and structurally deficient irrigated areas are being abandoned for irrigation and even for farming. Specific indicators were proposed to approach the abandonment process, revealing that irrigation intensity in temperate climate, riparian ICUs was only 20 %. Irrigation in the study area needs to progress towards sustainable intensification, concentrating agricultural production in areas equipped with the technology and the water management capacities required to face the current agronomical and environmental challenges. The on-going processes of irrigation modernization, new irrigation developments and irrigation abandonment should be coordinated to serve this purpose.

Conversion of monocropping to intercropping promotes rhizosphere microbiome functionality and soil nitrogen cycling

Intercropping can increase soil nutrient availability and provide greater crop yields for intensive agroecosystems. Despite its multiple benefits, how intercropping influences rhizosphere microbiome assemblages, functionality, and complex soil nitrogen cycling is not fully understood. Here, a three-year field experiment was carried out on different cropping system with five fertilization treatments at the main soybean production regions. We found that soybean yields in intercropped systems were on average 17 % greater than in monocropping system, regardless of fertilization treatments. We also found that intercropping systems significant increased network modularity (by 46 %) and functional diversity (by 11 %) than monocropping systems. Metagenomics analyses further indicated intercropping promotes microbiome functional adaptation, particularly enriching core functions related to nitrogen metabolism. Cropping patterns had a stronger influence on the functional genes associated with soil nitrogen cycling (R2 = 0.499). Monocropping systems increased the abundance of functional genes related to organic nitrogen ammonification, nitrogen fixation, and denitrification, while functional guilds of nitrate assimilation (by 28 %), nitrification (by 31 %), and dissimilatory nitrate reduction (by 10.1 %) genes were enriched in intercropping systems. Furthermore, we found that abiotic factors (i.e. AP, pH, and Moisture) are important drivers in shaping soil microbial community assemblage and nitrogen cycling. The functional genes include hzsB, and nrfA, and nxrA that affected by these biotic and abiotic variables were strongly related to crop yield (R2 = 0.076 ~ R2 = 0.249), suggesting a key role for maintaining crop production. We demonstrated that land use conversion from maize monocropping to maize-soybean intercropping diversify rhizosphere microbiome and functionality signatures, and intercropping increased key gene abundance related to soil nitrogen cycling to maintain the advantage of crop yield. The results of this study significantly facilitate our understanding of the complex soil nitrogen cycling processes and lay the foundation for manipulating desired specific functional taxa for improved crop productivity under sustainable intensification.