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As part of a larger food security project under Ethiopia’s Agricultural Growth Program (CASCAPE), 928 farms in the Ethiopian Highlands were surveyed between 2012 and 2017. The aim was to determine whether the Net Farm Income (NFI) is a relevant indicator that drives food security at the household and the farm level, and to determine its drivers across six study regions of Ethiopia (i.e., Addis Ababa, Hawassa, Haramaya, Bahir Dar, Jimma, and Mekelle). The effect of different socio-economic and environmental drivers on NFI was determined using descriptive statistics, correlation analysis, k-means clustering and comparison of high and low NFI quartiles per region. Results: The average annual NFI in Ethiopia was just below 1000 US$ per farm household, with Addis Ababa region leading. Jimma and Bahir Dar were just above average, and the others were at the lower end. In the correlation analysis, NFI was best explained by farm size, net cash flow and the use of nitrogen fertilizer. Male-headed households earned considerably more than female-headed households. The k-means clustering yielded two major farm types on the basis of significant differences in rainfall, farm size, education level, crop diversity, cash flow and N fertilizer use. An analysis of richest 25% versus poorest 25% per region showed Addis Ababa, Bahir Dar, Jimma and Mekelle regions all had significant differences between the two quartiles in farm size, crop diversity and N fertilizer use, whereas Hawassa and Haramaya regions seem more homogeneous. Conclusions: The survey results present new entry points for informed decision making through targeted, area-specific food security policies in the Ethiopian Highlands by virtue of insight in the regional spread of NFI and its driving forces. Important deductions from the results are policy actions that are obtainable from the results. For example, the farm-size variable provides an indicator on the type of policy action that is required to determine the farm siz

Growing populations and changing diets associated with greater wealth increase the pressure on the world's available land, constituting serious threats to food security. Policies to reverse this situation have aimed mainly at increasing agricultural yields and productivity, but these efforts are often cost- and time-intensive. Agri-food systems must be transformed to provide enough quantity of healthy food for everyone in a sustainable way, including those involved in the production chain, while dealing with the dynamics of local and global economies and the environment. Transforming the agri-food systems requires a combination of research, policies, and investments to manage complex trade-offs.Food loss and food waste (FLW) is one essential element of the agri-food system transformation, which touches not only the productivity efficiency of using natural resources but also the reduction of Greenhouse gas emissions. FLW, as a result, has become an increasingly important topic in the development community. Food losses represent 14% of global production (FAO, 2019). This is equivalent to US$400 billion annually. In fact, the United Nations included the issue of food loss and waste in the Sustainable Development Goal target 12.3, which aims to "halve per capita global food waste at the retail and consumer levels and reduce food losses along production and supply chains, including post-harvest losses" by 2030. Greenhouse gas emissions linked with food losses are equivalent to about 1.5 gigatonnes of CO2. In addition, food loss entails excessive use of scarce resources. For example, each year, 75 billion cubic meters of water are used to produce fruits and vegetables that are not eaten. Finally, the loss of marketable food can reduce producers' income and increase consumers' expenses, likely having larger impacts on disadvantaged population segments. The losses of fruit and vegetables are equivalent to 912 trillion kilocalories and micronutrients. This is happening, as 3

Peatland wildfire frequency and severity are increasing globally owing to climate change. The direct risk of elevated greenhouse gas emissions from peat burning receives much attention, yet the risks to vegetation composition or peat decomposition from alkaline ash inputs are poorly understood. We explored whether ash produced during smoldering increases peatland topsoil (∼0–25 cm) pH through field observations and laboratory experiments. We assessed spatial patterns of smoldering and ash presence, and measured soil and ash pH after a peatland wildfire in the Netherlands. Additionally, a peat smoldering experiment was conducted to compare freshly produced ash pH with aged ash pH collected 2 months following the wildfire. Additionally, we assessed the amount of ash needed to increase soil pH. Results showed that ash inputs at the field site were insufficient to increase pH of the acidic peatland after the wildfire. Incubation experiments showed that a ≥3 cm ash layer (ash load 163 t ha–1) would be required to increase soil pH by at least 1 unit. Given that aged ash was slightly acidic and fresh ash was alkaline, leaching and neutralisation of ash after wildfire is likely, suggesting that elevated soil pH from ash input may be transient rather than long term.

AimsThis study looks whether the response of soil management (liming and nitrogen fertilization) on the incidence of Fusarium wilt (Foc Race 1) in Gros Michel banana (Musa AAA) varies with different soil properties.MethodsThe effect of inoculation with Foc Race 1 was studied in a factorial greenhouse trial with soil samples from eight representative soil types from the Costa Rican banana region, two pH levels; and three levels of N-fertilization. After an 8-week period, plant biomass and a disease index were measured.ResultsThere were significant effects of soil pH and N, and their interactions on disease expression. Low pH levels and high N-fertilization increased the disease expression. The response to changes in soil pH and N-fertilization differed considerably between the different soils.ConclusionsAlthough soil pH and N influence Fusarium wilt in banana, each soil differs in its response to these soil properties. This complicates the development of standard soil management strategies in terms of e.g., N-fertilization and liming to mitigate or fight the disease.

Food system analysis is used to understand relations between the production, distribution, and consumption of agricultural products. Many export commodities commodities are facing “consumer concerns” and certification requirement issues.In this paper, the certification requirements and schemes of two export commodities—banana and cocoa—are discussed using food system analysis. The “inclusiveness” of the food system, in terms of living wage, is also discussed.

Crop diseases imply a high cost to control them and losses in the yield. Besides, effectiveness of conventional control methods such as pesticides can decrease in their effectiveness. There is a greater awareness of the fact that the optimal crop disease management system requires a combination of different approaches. Soil management may be a component that would modulate the expression of crop diseases. Despite of reports on the influence of soil conditions in the control of diseases, results are inconsistent. Based on the literature, a conceptual framework is proposed, where three types of soil influence in disease incidence are identified: a direct influence, where the pathogen is affected; an indirect influence, where the plant’s response to the disease is modulated, and a third, where both the first and the second occur simultaneously (Chapter 1). The model was examined for the case of Fusarium wilt (Fusarium oxysporum f. sp. cubense or Foc) in banana (Musa sp.). Tropical Race 4 (Foc TR4), one strain of this soil borne fungus could sweep away 80% of the whole bananas. It represents a high risk for the large-scale banana production and also for small-system. Foc Race 1 devastated the Gros Michel cultivar in Latin America and the Caribbean (LAC) during the 20th century. Social and economic impacts were truly significant. The was the shift of the Gros Michel to cultivars from de largely resistant to Foc Race 1 sub-group Cavendish (Musa AAA). With the reports of the new strain Foc TR4 and its wide range of susceptible cultivars, the research in the disease was reactivated. Foc can survive in the soil for decades. To better understand the Foc-soil-banana relationship, the research was divided in five phases in where different research tool with advantages and disadvantages were combined: literature, greenhouse experiments, field experiments and farm survey. The research questions were: i) Which soil properties are known to have an important role in disease expressi

Food systems analysis is increasingly being applied to understand relations between production, distribution, and consumption of food products, the drivers that influence the system, and the outcomes that show how well the food system performs on health and nutrition, on environmental sustainability, and on income and inclusiveness. Little attention has gone to the position of global export commodities, where production and consumption are far apart. Banana in Costa Rica and cocoa in Cote d’Ivoire were the subject of this study to find out what major drivers determine the functioning of these systems. Next to identifying drivers such as population growth and increased plant disease pressure, it was found that the typical far-away setting and different living conditions between producer and consumer countries required a special eye on governance as a tripartite arena (government, private sector, civil society) with their power relations, and on certification schemes as a driver that follows from corporate social responsibility. The certification schemes addressed cover all food system outcomes, although health and nutrition in a less conspicuous way. The descriptions of the functioning of the schemes were also linked to living wages and incomes for banana plantation workers in Costa Rica and cocoa smallholder farmers in Côte d’Ivoire. Although very meaningful, certification schemes so far do not prove to be a silver bullet, but they do have the potential, in combination with other measures, to help positive food system transformations.

Despite the increased usage of global soil property maps, a proper review of the maps rarely takes place. This study aims to explore the options for such a review with an application for the S-World global soil property database. Global soil organic carbon (SOC) and clay content maps from S-World were studied at two spatial resolutions in three steps. First, a comparative analysis with an ensemble of seven datasets derived from five other global soil databases was done. Second,a validation of S-World was done with independent soil observations from the WoSIS soil profile database. Third, a methodological evaluation of S-world took place by looking at the variation of soil properties per soil type and short distance variability. In the comparative analysis, S-World and the ensemble of other maps show similar spatial patterns. However, the ensemble locally shows largediscrepancies (e.g., in boreal regions where typically SOC contents are high and the sampling density is low). Overall, the results show that S-World is not deviating strongly from the model ensemble(91% of the area falls within a 1.5% SOC range in the topsoil). The validation with the WoSIS database showed that S-World was able to capture a large part of the variation (with, e.g., a root mean square difference of 1.7% for SOC in the topsoil and a mean difference of 1.2%). Finally, the methodological evaluation revealed that estimates of the ranges of soil properties for the different soil types can be improved by using the larger WoSIS database. It is concluded that the review through the comparison,validation, and evaluation provides a good overview of the strengths and the weaknesses of S-World.The three approaches to review the database each provide specific insights regarding the quality of the database. Specific evaluation criteria for an application will determine whether S-World is a suitable soil database for use in global environmental studies.

Fusarium oxysporum f. sp. cubense (Foc) causes Fusarium wilt in banana (Musa AAA). Foc Race 1 devastated the subgroup Gros Michel during the first half of the twentieth century. The Gros Michel was largely replaced by the resistant subgroup Cavendish in the 1950s. However, in the 1980s, Foc Tropical Race 4 started to spread affecting Cavendish bananas. No proper control measures have been found to deal with the disease. This paper re-takes an important research line from the 1950s to evaluate the potential of soil management for Fusarium wilt management. The role of soil properties on Fusarium wilt in bananas was studied in two greenhouse experiments. It was evaluated whether the influence of two main soil properties (pH and N) on Fusarium wilt is similar for Race 1 and Tropical Race 4. Two soil pH levels (lower than 5.2 and higher than 6.0) respectively ensured through acidification and liming; and three levels of N (ammonium nitrate, 33.5% N) weekly doses (low:0 N g, medium: 0.08 N g and high: 0.25 N g per plant) were achieved. The first experiment in Costa Rica confirmed the earlier results about the influence of soil pH and nitrogen on Fusarium wilt (Race 1) on Gros Michel bananas. The second experiment in The Netherlands evaluated the influence of pH and N on interactions between Foc (both Race 1 and Tropical Race 4) and Cavendish bananas. Results in both experiments showed that soil pH affected crop development and the disease. Besides, the interaction of the lower pH x the higher N accelerated the infection and reduced plant development. As such, the results showed that soil management has the potential to reduce the impacts of Fusarium wilt while dealing with Race 1 and Tropical Race 4 although it requires confirmation and further evaluation under field conditions.

Fusarium oxysporum f. sp. cubense (Foc) is a soil-borne fungus causing Fusarium wilt (FW) in banana. It is practically impossible to eradicate Foc in soils. Our understanding of soil–Foc–banana interactions is hampered by inconsistent research results caused by agro-ecological variability and the complexity of the soil system. This study aimed to evaluate the options to manage soil chemical properties to reduce disease expression and maintain banana production. The expression of FW (Foc Race 1) and the agronomic performance of the Gros Michel (Musa AAA) banana were evaluated in two medium-term factorial field experiments at representative locations in the Costa Rican banana region. In the experiments, five soil chemical properties (pH, N, Ca, Mg, and Mn) were managed to achieve a low and a high level. Plant mortality caused by FW, soil fertility, plant nutrition, and agronomic performance were monitored during four crop cycles. After the first crop cycle, the treatments started to present differences in plant mortality. There was a significant rise of plant mortality after the second crop cycle resulting in a cumulative plant mortality exceeding 60% in both experiments. A lower soil pH consistently resulted in significantly higher plant mortality. The interactions between soil properties (pH-N, pH-CaMg, pH-Mn, N-Mn, and CaMg-Mn) also influenced plant mortality. Soil N was the most significant treatment affecting leaf nutrient concentrations, bunch weight, and clusters per bunch. The experiments confirmed the potential role of soil management in FW expression in banana. Our results suggest that the management of soil chemical properties in the conditions here studied may help to reduce the expression rate of FW, but not to control the disease in the long run. View Full-Text

Agriculture is the largest contributor of non-CO2 anthropogenic greenhouse gas emissions (GHG). Agricultural based mitigation strategies (e.g. no-tillage) are identified to reduce emissions from agricultural soils through improved agricultural management. Global ecosystem models that are usually used for finding the potential of agricultural based mitigation strategies are limited, because processes related to agricultural management are currently underrepresented in global ecosystem models. The aim of this thesis is to contribute to the representation of agricultural management in global ecosystem models, so that the potential of agricultural based mitigation practices can be better quantified. Therefore, this thesis first addressed how processes related to agricultural management can be described in global ecosystem models, with a focus on processes related to tillage and N2O emissions. This analysis resulted in a standardized framework that can be followed to incorporate other agricultural management practices in global ecosystems as well. After indicating how processes related to tillage can be described, they were implemented into the global ecosystem model LPJmL. Subsequently, the extended LPJmL model was evaluated on its performance on various fluxes (including N2O and CO2) at the global scale and for a number of experimental sites. Finally, the uncertainty caused by the upscaling of soil input data when assessing tillage effects on N2O emissions were addressed. LPJmL was not capable of accurately simulating tillage effects on N2O emissions. Hence, the potential of mitigating N2O emissions through tillage management cannot be well assessed. However, the implementation of the more detailed tillage-related mechanism into the global ecosystem model LPJmL improved the ability to understand agricultural management options for agricultural mitigation of CO2 emissions, climate change adaptation and reducing environmental impacts. The work in this thesis concludes th

Policy makers and farmers use tools, such as a nutrient balance, to gain insight into the environmental impact of agricultural practices. A discrepancy, however, exists between the needs of policy makers and farmers, about the use and the spatial scale of such tools. Farm balances calculate nutrient balances across all agricultural fields within a farm without distinguishing separate fields, whereas field balances calculate a nutrient balance on a delineated field. For farmers, a nutrient balance at field level is more useful than at crop or farm level, because decision making and fine-tuning management occurs at the field level. A field balance, however, requires more detailed data than a farm balance and therefore is less easy to implement. As soil types influence nutrient balances, we hypothesize that if within-farm variation in soil types is low, there is no need to replace a farm balance by a field balance. To test this hypothesis, we computed nutrient balances at farm and field level on five Dutch dairy farms (three on sand, two on clay), varying in degree of within-farm variation in soil series. A full year of soil nitrogen (N) and phosphorus (P) input and output data on farm and field level were provided by farmers, while soil variation was determined using the Dutch 1:50.000 soil map. The Annual farm Nutrient Cycle Assessment (ANCA) was used to calculate soil N and P surpluses, and soil nutrient fluxes such as nitrate leaching and nitrous oxide emission at farm and field level. Even on farms with few soil series, a considerable variation in N and P inputs, outputs and balances across fields was found, due to management differences and soil properties not represented by the soil map. Furthermore, field-level balances better represented nitrogen leaching than farm-level balances on farms with diverse soils (reflected by different leaching factors) and negative nitrogen field balances (deficits). Also, using field balances, for one case study farm the highest

Urbanization is an important trend in global land cover change and seriously impacts the soil resources. However, there is no clear definition for urban areas. As a result estimates of urbanization and its effects on soil resources vary widely. Urbanization can be modelled in different ways with a specific focus on environmental conditions, temporal dynamics and spatial patterns. The processes underlying urbanization require a hybrid approach that combines the different methods. Similarly, the unique conditions of the urban environment require specific surveying techniques for the soil resources. The global debate on urbanization and its environmental impacts calls for a rapid standardization of definitions and methodologies to come with proper information on rates and impacts.

With limitations in the availability and accessibility of surface water, attention is increasingly directed towards groundwater resources as the most reliable source of fresh water for different sectors. Accordingly, groundwater is over abstracted in many countries of the world. The overexploitation of groundwater renewable and non-renewable aquifers for both urban use and irrigation results in a drop of the water table and, frequently, in a reduction in groundwater quality. This study focuses on the use of groundwater for irrigation purposes in desert areas of the MENA region. The thesis contributes to conserving and sustaining the use of limited groundwater resources in desert agriculture, by analyzing the current unsustainable use of groundwater, focusing on groundwater policy on the one hand, and on the specificities of desert agriculture on the other, with a focus on Azraq basin in Jordan.

The United Nations pledged to achieve the Sustainable Development Goals by 2030. Regional land use analyses (RLUA) have an essential contribution to achieving these goals. To better meet the needs for achieving sustainable development, RLUA became more quantitative and more interdisciplinary over recent decades. This change resulted in an increased use of quantitative simulation models, which changed the type and nature of input data as well. Soil data are one of the input data RLUA require. Available soil data often do not meet the soil data requirements anymore, due to the change in RLUA. Therefore, a gap exists between the available and required soil data. This thesis aims to find possible solutions to bridge this gap. In Chapter 2, different soil datasets are compared to identify the gap and to analyse the effect of using different soil datasets as input for a regional land use analysis (RLUA). Main challenges with soil data in RLUA are: i) understanding the assumptions in soil datasets, ii) creating soil datasets that meet the requirements for regional land use analysis, iii) not only rely on available soil data but also collect new soil data and iv) validate soil datasets. Chapter 2 demonstrated differences between soil datasets, which had significant effect on the results of RLUA. Three potential solutions on bridging the gap between the available and required soil data are given in Chapter 3, 4 and 5. A literature study showed that RLUA hardly combine available and newly collected soil data. Chapter 3 analyses what complementary data RLUA require by combining available soil data and newly collected soil data. Two case studies were carried out to illustrate how a combination can enrich the soil data for RLUA. Predicting soil properties, in particular soil organic matter, using newly collected soil data often result in soil maps of poor quality. The digital soil mapping techniques that are currently being used for predicting soil properties make dominantly use

The research community increasingly analyses global environmental problems like climate change and desertification with models. These global environmental modelling studies require global, high resolution, spatially exhaustive, and quantitative data describing the soil profile. This study aimed to develop a pedological approach that takes stock of available legacy and auxiliary data to create a global, 30 arc second soil property database for modelling. The methodology uses the Harmonized World Soil Database and the ISRIC-WISE 3.1 soil profile database. Auxiliary information at 30 arc second resolution for various landscape properties is used to describe the variation in landscape properties (temperature and precipitation, topography, elevation, land use, and land cover). Complex mapping units of the HWSD were first disaggregated using a digital elevation model and toposequences to generate delineated areas described by a single soil type. Secondly, ranges of soil properties per soil type were determined using the soil profile data. Then a meta-analysis on a broad literature survey was used to develop a simple model that, based on landscape properties at a particular location, determines the position within these ranges and thus provides an estimation of the local soil properties. Finally, the model was implemented at the global level to determine the distribution of soil properties. The methodology, denominated S-World (Soils of the world) resulted in readily available, high resolution, global soil property maps that are now available for environmental modelling.