Sustainable Intensification Of Agriculture Research Articles

The role of household labour for sustainable intensification in smallholder systems: a case study in cocoa farming systems

Sustainable agricultural intensification aims at increasing yields on existing agricultural land without negative environmental impacts. Managing pests and diseases contributes to increasing yields. Without synthetic pesticides, this management is labour intensive. Smallholder farming systems heavily rely on manual and household labour, which will be affected by future demographic changes. Knowledge on how these changes will affect sustainable intensification is limited. Based on a case study of Ugandan cocoa farms, we tested the impact of increased household labour availability on pest and disease management (PDM) practices and pesticide use. We made use of a unique quasi-experimental design, in which household labour increased during the national COVID-19 lockdowns as children did not attend school and family members returned from cities. Our interview data from 2019 to 2021 showed that household labour availability increased on average by 0.8 (±2.5) household members and 16% of labour days per hectare. Using different regression models complemented with qualitative insights, we found that the uptake of alternative PDM practices significantly reduced pesticide quantities and expenditures. The implementation of alternative PDM practices was only weakly influenced by household labour availability and increased with farmer training and trust in alternative practices. These results imply that alternative PDM practices are an important pillar for production with little or without synthetic pesticides and their adoption requires support and incentives, especially on labour or resource-constrained farms.

Mapping upland crop–rice cropping systems for targeted sustainable intensification in South China

Upland crop-rice cropping systems (UCR) facilitate sustainable agricultural intensification. Accurate UCR cultivation mapping is needed to ensure food security, sustainable water management, and rural revitalization. However, datasets describing cropping systems are limited in spatial coverage and crop types. Mapping UCR is more challenging than crop identification and most existing approaches rely heavily on accurate phenology calendars and representative training samples, which limits its applications over large regions. We describe a novel algorithm (RRSS) for automatic mapping of upland crop–rice cropping systems using Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 Multispectral Instrument (MSI) data. One indicator, the VV backscatter range, was proposed to discriminate UCR and another two indicators were designed by coupling greenness and pigment indices to further discriminate tobacco or oilseed UCR. The RRSS algorithm was applied to South China characterized by complex smallholder rice cropping systems and diverse topographic conditions. This study developed 10-m UCR maps of a major rice bowl in South China, the Xiang-Gan-Min (XGM) region. The performance of the RRSS algorithm was validated based on 5197 ground-truth reference sites, with an overall accuracy of 91.92%. There were 7348 km2 areas of UCR, roughly one-half of them located in plains. The UCR was represented mainly by oilseed-UCR and tobacco-UCR, which contributed respectively 69% and 15% of UCR area. UCR patterns accounted for only one-tenth of rice production, which can be tripled by intensification from single rice cropping. Application to complex and fragmented subtropical regions suggested the spatiotemporal robustness of the RRSS algorithm, which could be further applied to generate 10-m UCR datasets for application at national or global scales.

Editorial: Maximizing nitrogen fixation in legumes as a tool for sustainable agriculture intensification, volume II

Editorial: Maximizing nitrogen fixation in legumes as a tool for sustainable agriculture intensification, volume II

Seed priming with gas plasma-activated water in Ethiopia’s “orphan” crop tef (Eragrostis tef)

Main conclusionSeed priming with gas plasma-activated water results in an increased ageing resilience in Eragrostis tef grains compared to a conventional hydropriming protocol.Tef (Eragrostis tef) is a cereal grass and a major staple crop of Ethiopia and Eritrea. Despite its significant importance in terms of production, consumption, and cash crop value, tef has been understudied and its productivity is low. In this study, tef grains have undergone different priming treatments to enhance seed vigour and seedling performance. A conventional hydropriming and a novel additive priming technology with gas plasma-activated water (GPAW) have been used and tef grains were then subjected to germination performance assays and accelerated ageing. Tef priming increases the germination speed and vigour of the grains. Priming with GPAW retained the seed storage potential after ageing, therefore, presenting an innovative environmental-friendly seed technology with the prospect to address variable weather conditions and ultimately food insecurity. Seed technology opens new possibilities to increase productivity of tef crop farming to achieve a secure and resilient tef food system and economic growth in Ethiopia by sustainable intensification of agriculture beyond breeding.

Fertilizer use efficiency and economic viability in maize production in the Savannah and transitional zones of Ghana

Increasing fertilizer use is highly justified for sustainable agricultural intensification if yield response, fertilizer use efficiency (FUE), and economic viability of fertilizer application are high. Despite the increasing fertilizer application rates in Ghana, yields only marginally increased. Also, the recent fertilizer price hikes post COVID-19 revived concern for economic analysis of fertilizers. This study analyzed the FUE and economic viability of fertilizer use in maize production in Guinea/Sudan Savannah and Transitional/Deciduous zones of Ghana. Survey data from 2,673 farmers in the 2019, 2020, and 2021 production seasons were used. The average agronomic efficiency (AE), partial factor productivity (PFP), and value-cost ratio (VCR) of fertilizer use were 2.2 kg of grains per kilogram of fertilizer, 18.3 kg grains per kilogram of fertilizer, and 1.8 Ghana cedis of marginal yield per Ghana cedi spent on fertilizer, respectively. Fertilizer use was economically viable for only 28.1% of farmers with a VCR of 2 or higher, while 52.5% reached the break-even point with a VCR of at least 1. Various fertilizer formulations, including NPK plus sulfur, and adoption of integrated soil fertility management (ISFM) practices, particularly improved seeds, organic fertilizers, and minimum tillage, improved maize yield response to fertilizer and thus the FUE. These low efficiency and economic viability of fertilizer use are prevailing conditions in other sub-Saharan Africa (SSA) countries and these do not guarantee sustainable food security and improved livelihood of the farmers in the region. Ghana’s Ministry of Food and Agriculture (MoFA), together with relevant stakeholders, should provide guidance on ISFM and intensify farmer education through farmer associations to increase the adoption of ISFM. The local government should work with other relevant stakeholders to improve the market conditions within the agriculture sector, for instance, by linking farmers to city markets for favorable output prices.

Escaping chronic poverty: long-term impacts of an agricultural development program

AbstractThere is a need for groundbreaking initiatives to come to the rescue of the world’s rain-fed regions, especially in the face of the current climate and food crises and the associated reversal of previous advances in poverty reduction. However, there is little evidence of successful programs, which can inform the development of proactive policies to meet these urgent challenges. Can sustainable agricultural intensification enable marginalized, smallholder farmers to break out of chronic poverty? In this study, we scrutinize the Wadi concept, an integrated farming system that includes water resource development, soil conservation, cultivation of fruit trees, and intercropping on degraded land. We use a mixed-methods approach that involves surveying 1860 households, which were randomly sampled from a population of 188,231 participants across four Indian states, encompassing a variety of geographical regions. This is the first investigation into the effects of integrated farming systems on livelihoods on such a large scale and spanning 23 years. We compare the household participants of the program with the non-participants and run a linear regression analysis, ceteris paribus, comparing farmers who established integrated farming systems at different points in time over the period 1990–2017. Significant progress in several socioeconomic factors can be observed, such as higher incomes (the annual income of a typical participant has increased from INR 30,000 to 100,000 or even more), diversified income sources, positive life changes, higher life satisfaction and better perspectives for children, as well as environmental benefits. The Wadi program’s effectiveness in providing sustainable development pathways implies benefits to be gained from scaling it up. By thoroughly assessing its potential to help farmers escape chronic poverty and build resilience, this study provides evidence of the Wadi concept’s success that can enrich the science-policy dialog on development programs.

Do combined sustainable agricultural intensification practices improve smallholder farmers welfare? Evidence from eastern and western Kenya

AbstractSmallholder farmers often bundle different sustainable agricultural intensification (SAI) practices to boost crop yield and address soil fertility challenges. However, there is a dearth of empirical studies that investigate farmers’ adoption of SAI bundles and their subsequent impacts. Using data from a three‐wave panel survey of smallholder maize‐legume producers in Kenya, we examine the adoption and payoffs from 10 SAI practices clustered into five dominant groups. We use a random effects multinomial logit model to determine the choice of SAI cluster at the plot level while controlling for unobserved individual heterogeneity. The results show that the number of extension contacts, farm labor availability, household wealth, and education of household heads positively and significantly affect the adoption of SAI clusters while renting plots and poor soil quality have negative effects. The multinomial endogenous treatment effects model results reveal significant variability in crop yield, total variable cost, revenue, and net income across the five SAI clusters. The benefits vary by crop system, region, and cropping year, indicating that a one‐size‐fits‐all extension design is unsuitable for farmers. The study suggests the promotion of participatory extension policies that would allow locally adaptable and highly profitable bundles of SAI practices to be identified, refined, and disseminated.

Impacts of irrigation development on water quality in the San Salvador watershed (Part 1): Assessment of current nutrient delivery and transport using SWAT

The development of irrigation involves a change in land use and management and has implications for water quality and quantity. It is critical to design conservation practices and best management practices consistent with sustainable agricultural intensification. The objective of this work was to understand and characterize key processes affecting hydrology, nutrient export and transport, and quantify impacts in the San Salvador watershed. For such purpose, the Soil & Water Assessment Tool (SWAT) was implemented, calibrated for water quantity, and water quality was adjusted using soft calibration techniques. The model reproduces water quantity and nutrient balance, and aids in characterizing the nutrient delivery and transport in the watershed. The magnitude of runoff affects the balance of nutrients. In high flows, diffuse sources are more prevalent, while in low flows, point sources and direct livestock manure to the river are more significant. The main outcomes of this work contribute to the design of strategies to achieve sustainable agricultural intensification. It also describes a new modeling tool freely available that could be used in further studies.

Impacts of irrigation development on water quality in the San Salvador watershed (Part 2): Implementation of scenarios in SWAT

Intensive agricultural activities pose a significant threat to water quality as critical non-point sources of pollution. Effective mitigation strategies demand understanding the causes and processes of water pollution. This study aimed to quantify the impacts of irrigation development on water quality and assess best management practices for sustainable agriculture intensification. Employing the calibrated SWAT model for the San Salvador watershed (baseline scenario), two scenarios were implemented and evaluated: the first one depicted irrigation development from a future reservoir, and the second integrated riparian buffer zones to minimize nutrient and sediment losses. Notably the baseline scenario did not achieve nutrient water quality objectives. Results revealed that irrigation development increases nutrient yields, driving the future reservoir toward eutrophication. Implementing riparian buffer zones reduced nutrient loss, but additional measures are necessary for sustainable environmental goals at the basin scale. This research contributes with valuable insights for formulating effective management strategies to minimize nutrient pollution in water and safeguard water quality and biodiversity in the basin.

Effects of Project Planning Practices for Project Performance: A Case of Sustainable Agricultural Intensification and Food Security Project in Rwanda

Effects of Project Planning Practices for Project Performance: A Case of Sustainable Agricultural Intensification and Food Security Project in Rwanda

Coupling input and output intensity to explore the sustainable agriculture intensification path in mainland China

Sustainable intensification (SI) of agriculture is widely regarded as an important way to alleviate the contradiction between the food gap and ecosystem health. Correlate input intensity and output intensity have been regarded as an important dimension in most estimation frameworks of SI. But in practice, this correlation is generally expressed in terms of efficiency metrics and calculated as the ratio of output intensity to input intensity, which cannot quantitatively explain the impact of input intensity on output intensity and provide a threshold value for estimating the suitability of SI. This study's goals are to propose an input—output coupled method to explain the impact of input intensity on output intensity and thereby estimate the suitability of provincial SI. Provincial annual input intensity and output intensity were estimated from an emergy-based perspective by taking China as a case study. The K-means algorithm was used to identify the structural pattern of arable land input intensity. A sliding window-based partial correlation index method was proposed and applied to reveal the interaction process between input intensity and output intensity. The results show that there are two main change paths in the pattern of input intensity: one path in the western irrigation regions and the other path in the eastern northeast China Plain and middle-lower Yangtze Plain. The former path can be expressed as a small increase in fertilizer and agro-machinery input intensity with a decrease in labour force input intensity. The latter path shows a larger increase in fertilizer and pesticide input intensity. For each type of input intensity except mulching film, its correlation to output intensity has experienced a similar coupling—decoupling—recoupling process in both plain provinces and mountainous or plateau provinces. According to Landau's theory of phase transition, the complex coupling of input and output undergoes a phase transition process from order to disorder and then to order, depicted by the sliding window-based partial correlation coefficient as the order parameter from a holistic perspective. The inflection points of coupling relation changes show that the phenomenon of fertilizer and pesticide overuse has steadily occupied most provinces in eastern China and is spreading westwards. Although the “zero growth action for fertilizers and pesticides” has made considerable achievements in reducing the input intensity of fertilizer and pesticides since 2015, the situation of superfluous fertilizer and pesticide input has not changed substantially. The input intensity of fertilizer and pesticides still needs to be further reduced. This study can contribute to the estimation method system of SI. The input—output coupled method is applicable for other spatial scales and regions (or countries) to estimate the suitability of SI.

Introducing exceptional growth mining-Analyzing the impact of soil characteristics on on-farm crop growth and yield variability.

Sustainable intensification of agriculture requires understanding of the effect of soil characteristics and nutrient supply on crop growth. As farms are increasing in size by acquiring small fields from various farmers, the soil characteristics and nutrient supply might be very different from field to field, while at the same time specific soil properties might limit the nutrient uptake. As a result, there might be a large number of heterogeneous reasons why crop growth varies significantly. New data analysis techniques can help to explain variability in crop growth among fields. This paper introduces Exceptional Growth Mining (EGM) as a first contribution. EGM instantiates the data mining framework Exceptional Model Mining (EMM) such that subgroups of fields can be found that grow exceptionally in terms of three growth parameters (high/low maximum growth, steep/flat linear growth and early/late midpoint of maximum growth). As second contribution, we apply EGM to a case study by analyzing the dataset of a potato farm in the south of the Netherlands. EGM consists of (i) estimating growth curves by applying nonlinear mixed models, (ii) investigating the correlation between the estimated growth parameters, and (iii) applying EMM on these growth curve parameters using a growth curve-specific quality measure. By applying EGM on the data of the potato farm, we obtain the following results: 1) the estimated growth curves represent the variability in potato tuber growth very well (R2 of 0.92), 2) the steepness of the growth curve has a strong correlation with the maximum growth and the midpoint of maximum growth, and the correlation between the midpoint of maximum growth and maximum growth is weak, 3) the subgroup analyses indicate that: high values of K correspond to high maxima; low values of K correspond to low maxima, steep growth curves', and a late midpoint of halfway growth; Mg influences the midpoint of the growth curve; values of B are higher on dry soils with high tuber growth, while low values of B are found on wet soils with high tuber growth; high values of Zn, Mn, and Fe are found in subgroups with low tuber weight, probably related to the soil's low pH. In summary, this paper introduces EGM to obtain understanding in crop response to soil properties and nutrient supply. In addition, EGM provides a way to analyze only small parts of a large dataset, such that the impact of soil factors on growth can be analyzed on a more detailed level than existing methods.

Insect frass composition and potential use as an organic fertilizer in circular economies.

Insect manure or "frass" has emerged as an alternative nutrient source for alleviating the dependence on fossil fuel-based fertilizers, reducing food waste, and promoting food security. Yet, research on insect frass chemical composition is in its infancy. Here, we assessed the chemical properties of yellow mealworm (Tenebrio molitor L.) frass compared with poultry litter (PL). Insect frass was obtained from the National Biological Control Laboratory (NBCL; IF-L) and an insect-rearing company (IF-C). PL was collected from facilities in Arkansas (PL-AR) and North Carolina (PL-NC). Samples were analyzed for pH, electrical conductivity, macro- and micronutrients, heavy metals, pathogens, and indicator microorganisms. On average, insect frass had 43% and 47% higher C and N than PL, respectively (P < 0.05). Considering a 5mg/ha application rate, IF-C can supply 159kg N/ha, twice the N supply of PL-AR (78kg/ha). IF-L had a 53% higher P supply than PL-NC. Mean K, Ca, S, and micronutrient contents were higher in PL than in frass (P < 0.05), whereas As, Cd, Cr, and Pb were nearly absent in frass. Chemical composition and pathogens in fertilizer sources were largely affected by insect-rearing substrate and supplements used in poultry and insect production. Insect frass utilized in this study had optimum C and N rates relative to PL, suggesting a promising soil amendment for improving soil health and C sequestration, thus contributing to sustainable agricultural intensification and reuse of food waste in circular economies.

Evaluating sustainable intensification levels of dryland agriculture: A focus on Xinjiang, China

Adequate tools for evaluating the Sustainable Intensification of Agriculture (SIA) level are crucial, especially in drylands with limited resources. Based on emergy indices and environmental footprints, We propose an evaluation framework for the case of major crop intensification in Xinjiang, China, and examine the local SIA from 2001 to 2020. The results show that increases in emergy input (EI) of the crop system were achieved with simultaneous increases in water consumption and carbon emissions. The most EI to the system is from economically non-free non-renewable resources (75.1 %), and only 5.4 % from environmentally free renewable resources. The emergy output (EO) of cotton was less than 80 % of wheat and maize, but the carbon footprint (CF) and water footprint (WF) of cotton were much higher than wheat and maize (>1.18 times and > 5.01 times, respectively). We group historical results covering emergy indices, CF, WF, and other production indicators into five dimensions and comprehensively evaluate the level of SIA in Xinjiang according to the changes in the five dimensions. It was found that raising the SIA depended on improving management, productivity, and environmental impact dimension from 2000 to 2005. After 2005, the SIA’s down-turning was due to the trade-offs between management, environmental dimensions, and their indicators and the continuous reduction of sustainability of other dimensions. In addition, the progress and realization of SDG 2, SDG 6, SDG 7, SDG 8, SDG 11, and SDG 12 can effectively improve the SIA. Our study serves as a helpful example for evaluating the level of sustainability of intensive agricultural policies not just in Xinjiang but also in other drylands of the world.

UNDERSTANDING THE IMPACTS OF CROP DIVERSIFICATION IN THE CONTEXT OF CLIMATE CHANGE: A MACHINE LEARNING APPROACH

Abstract. The concept of sustainable intensification in agriculture necessitates the implementation of management practices that prioritize sustainability without compromising productivity. However, the effects of such practices are known to depend on environmental conditions, and are therefore expected to change as a result of a changing climate. We study the impact of crop diversification on productivity in the context of climate change. We leverage heterogeneous Earth Observation data and contribute a data-driven approach based on causal machine learning for understanding how crop diversification impacts may change in the future. We apply this method to the country of Cyprus throughout a 4-year period. We find that, on average, crop diversification significantly benefited the net primary productivity of crops, increasing it by 2.8%. The effect generally synergized well with higher maximum temperatures and lower soil moistures. In a warmer and more drought-prone climate, we conclude that crop diversification exhibits promising adaptation potential and is thus a sensible policy choice with regards to agricultural productivity for present and future.

Grassland intensification effects cascade to alter multifunctionality of wetlands within metaecosystems

Sustainable agricultural intensification could improve ecosystem service multifunctionality, yet empirical evidence remains tenuous, especially regarding consequences for spatially coupled ecosystems connected by flows across ecosystem boundaries (i.e., metaecosystems). Here we aim to understand the effects of land-use intensification on multiple ecosystem services of spatially connected grasslands and wetlands, where management practices were applied to grasslands but not directly imposed to wetlands. We synthesize long-term datasets encompassing 53 physical, chemical, and biological indicators, comprising >11,000 field measurements. Our results reveal that intensification promotes high-quality forage and livestock production in both grasslands and wetlands, but at the expense of water quality regulation, methane mitigation, non-native species invasion resistance, and biodiversity. Land-use intensification weakens relationships among ecosystem services. The effects on grasslands cascade to alter multifunctionality of embedded natural wetlands within the metaecosystems to a similar extent. These results highlight the importance of considering spatial flows of resources and organisms when studying land-use intensification effects on metaecosystems as well as when designing grassland and wetland management practices to improve landscape multifunctionality.

Can biochar conserve soil moisture and improve soil properties for sustainable intensification of acid soils in the Eastern Indian Himalayas?

AbstractThe marginal Himalayan ecosystems have great potential for biochar application for conserving soil moisture, ameliorating soil acidity, improving soil fertility, and thus, contributing to sustainable intensification. Thus, the efficacy of biochar was tested along with nutrient management practices (NMP) on the performance of maize (Zea mays L.)‐French bean (Phaseolus vulgaris L.) as the emerging cropping system in an acid soil under rainfed hill ecosystem. The rainy season maize was grown with three levels of biochar (0, 2.5, and 5 Mg ha−1, applied only once in the first year), and four NMP (100% recommended dose of fertilizer [RDF] [80:60:40 N:P2O5:K2O kg ha−1], 75% RDF, 75% RDF + 4 Mg ha−1 farm yard manure [FYM], and 50% RDF) under minimum tillage. After harvesting of maize, French bean was grown under no‐till with four NMP (100% RDF [50:60:40 N:P2O5:K2O kg ha1], 75% RDF, 75% RDF + 4 Mg ha−1 FYM, and 50% RDF). The soil properties after 3 years viz., soil moisture, soil organic carbon (SOC), pH, and available N, P, and K status were significantly improved under 5 Mg ha−1 biochar than no biochar. Among the NMP, 75% RDF + FYM and 100% RDF had higher soil moisture, water infiltration, pH, SOC concentrations, and available N, P, and K status than others. The interaction effect of 5 Mg ha−1 biochar and 75% RDF + 4 Mg ha−1 FYM registered the highest SOC content (15.7 g kg−1). Available N was the highest in soil under 75% RDF + 4 Mg ha−1 FYM whereas, available P in soil under 100% RDF. Application of 5 Mg ha−1 biochar produced significantly the highest mean grain yield of maize and succeeding French bean. The combined application of 100% RDF and biochar 5 Mg ha−1 produced the highest maize equivalent yield. Thus, 5 Mg ha−1 biochar and application of recommended fertilizers are suggested for sustaining soil fertility and sustainable intensification of rainfed hill agriculture under acidic soil.

Grazing intensity and nitrogen fertilization timing to increase soil organic carbon stock and nitrogen in integrated crop-livestock systems

ABSTRACT Integrated crop-livestock systems (ICLS) foster synergistic relationships to increase nitrogen (N) cycling and soil organic carbon (SOC) accrual in agricultural setups. This study evaluated how the grazing intensity and N fertilization (rates and timing) affect both SOC and N fractions, and soil organic matter chemical composition in an ICLS managed under no-tillage in an Oxisol, six years after initiation. The ICLS was compared to a nearby pasture (PA) and a native forest (NF). The treatments consisted of two grazing intensities: Low Sward Height (LH) and High Sward Height (HH) were maintained with high and low stocking rates, respectively. The HH varied between 0.20 and 0.60 m, and LH between 0.10 and 0.30 m according to the plant forage species throughout the experiment. Fertilization using 200 kg ha -1 N-urea, not splitting up, was conducted at two timings, either at the winter pasture establishment (autumn), about 35 days after sowing or during the summer cash crop cycle (spring). Total N amount per year, including both phases, pasture and cash crop was the same for all treatments. The SOC and N contents were assessed in soil and particulate organic matter (POM), while carbon (C) and N stocks were specifically determined in the soil. Soil organic matter composition was characterized by FTIR. The combination of HH and N fertilization during the pasture phase increased the content of C from 36.1 to 39.9 ± 0.7 g C kg -1 and of N from 2.7 to 3.2 ± 0.1 g N kg -1 . The SOC stocks varied from 37.3 to 41.1 ± 0.7 Mg C ha -1 , and the N stocks from 2.1 to 3.3 ± 0.1 Mg N ha -1 at 0.0-0.10 m soil layer. The SOC content of the POM and the soil organic matter chemical composition determined by FTIR were mainly affected by the grazing intensity. The HH led to an increased in C content within the POM fraction, reaching values of 51.6 ± 1 and 49.2 g C kg -1 , respectively to N crop fertilization and N pasture fertilization. Land-use changed how organic functional groups were stored in soil organic matter fractions. The NF had a greater abundance of aliphatic and phenol in the MAOM, while pasture and ICLS systems had greater aliphatic in the POM fraction. In ICLS, SOC accrual was positively associated with more recalcitrant organic functional groups of phenol, aromatic, and carbonyl C-O. The HH increases SOC accrual, while N-fertilization on pasture ensures adequate nutrition of plants and animals during the winter ICLS phase, at the same time as providing greater residual N for subsequent cash crops through enhanced catalyzed by ruminants. Therefore, grazing and fertilization management strategies should be considered to promote sustainable agriculture intensification with ICLS.

Sensitivity of the global agricultural sector to changes in climate policy - EU countries compared to the rest of the world

Abstract There has been a decline in greenhouse gas (GHG) emissions per capita in all world regions since the 1990s. In developing countries, this decline has been attributed to population growth and an increase in absolute emissions, while in developed countries, the trend is mainly due to a decrease in absolute emissions combined with minor population changes. This paper aims to delve into the intricacies of global GHG emissions, with a spotlight on the agricultural sector. This paper assesses the patterns and reasons behind the decline in GHG emissions per capita since the 1990s across different regions. In particular, it addresses the concept of the “sustainable intensification of agriculture” and the debate between intensive vs. less-intensive production in the context of GHG emissions. Despite having high emissions per hectare, we argue that European countries show lower emissions in relation to production value, highlighting the region’s production intensity and efficiency. Compelling visual data representations and references from significant international bodies, such as the IPCC and EEA, bolster the paper’s findings and conclusions.

From frequency to intensity – A new index for annual large-scale cropping intensity mapping

Continuous population growth, global warming, extreme weather and local wars pose considerable challenges to agricultural production. Excessive agricultural intensification may lead to serious environmental problems such as water resources depletion and non-point source pollution. Sustainable agricultural intensification is a potential solution, and cropping intensity and its spatio-temporal patterns are of great significance to the planet hearth, human well-being and sustainable development of agriculture. However, traditional methods for cropping intensity mapping lack the deep analysis of crop phenology and failure to consider the spatial detail, spatial coverage and time continuity simultaneously. Existing cropping intensity indicators, such as cropping frequency or multiple crop index, have their limitations in China because of its diverse topographies and fragmented landscapes. In actual fact, few indicators for fine cropping intensity have been developed that address this problem. Time series vegetation index data contain meaningful vegetation phenology information. Information mining on these data can provide new insights for cropping intensity mapping. In this study, the concept of systematic mapping was put forward to measure cropping intensity with a fresh perspective. A new phenology-based cropping intensity index (PCII) was proposed to reach the goal of “from frequency to intensity” in cropping intensity mapping. Through thoroughly exploring the temporal spectral characteristics of croplands and considering the crop pattern as a whole, PCII set up the mapping between cropping intensity and land-cover types. The method can accurately map cropping intensity even though the study spanned a vast area, and can handle the effects of geographical differentiation caused by vegetation phenology differences. It can also precisely measure cropping intensity at the abundance level and reflect the heterogeneity within a pixel. It’s a novel method for annual fine cropping intensity mapping at large-scale and long-term.