Farmer responses to an input subsidy and co‑learning program: intensification, extensification, specialization, and diversification?

Open Access ArticleSustainable intensification aims to increase production and improve livelihoods of smallholder farmers in sub-Saharan Africa. Many farmers, however, are caught in a vicious cycle of low productivity and lack of incentives to invest in agricultural inputs. Moving towards sustainable intensification therefore requires support such as input subsidies and learning about new options through, for instance, co-learning approaches. Yet such support is not straightforward as agricultural developments often diverge from the envisaged pathways: extensification may occur instead of intensification and specialization instead of diversification. Understanding of farmers’ responses to incentives such as input subsidies and new knowledge is lacking. Our overarching aim was to improve this understanding, in order to better support future pathways for agricultural development in smallholder farming. Over five seasons, we compared the responses of farmers in western Kenya taking part in a novel co-learning program we developed, which included provision of an input voucher, with the responses of farmers who only received a voucher. We also assessed the differences before and during the program. We used diverse indicators that were related to the different agricultural development pathways. Farmer responses were mainly a result of the input voucher. Farmers increased maize yields (intensification) and maize area (specialization) for maize self-sufficiency. Increased farm and maize areas in combination with relatively low N application rates also pointed to extensification coupled with the risk of soil N mining. Diversification by increasing the soybean and groundnut area share was facilitated by the integrated co-learning approach, which thereby supported relatively complex farm management changes. Our results highlight the difficulty of enabling yield and production increases, while also meeting environmental and economic goals. The diversity of farmer responses and constraints beyond the farm level underlined the importance of wider socio-economic developments in addition to support of sustainable intensification at farm level

Mapping spatial distribution and geographic shifts of east African highland banana (Musa spp.) in Uganda

Open Access Journal; Published online: 17 Feb 2022East African highland banana (Musa acuminata genome group AAA-EA; hereafter referred to as banana) is critical for Uganda’s food supply, hence our aim to map current distribution and to understand changes in banana production areas over the past five decades. We collected banana presence/absence data through an online survey based on high-resolution satellite images and coupled this data with independent covariates as inputs for ensemble machine learning prediction of current banana distribution. We assessed geographic shifts of production areas using spatially explicit differences between the 1958 and 2016 banana distribution maps. The biophysical factors associated with banana spatial distribution and geographic shift were determined using a logistic regression model and classification and regression tree, respectively. Ensemble models were superior (AUC = 0.895; 0.907) compared to their constituent algorithms trained with 12 and 17 covariates, respectively: random forests (AUC = 0.883; 0.901), gradient boosting machines (AUC = 0.878; 0.903), and neural networks (AUC = 0.870; 0.890). The logistic regression model (AUC = 0.879) performance was similar to that for the ensemble model and its constituent algorithms. In 2016, banana cultivation was concentrated in the western (44%) and central (36%) regions, while only a small proportion was in the eastern (18%) and northern (2%) regions. About 60% of increased cultivation since 1958 was in the western region; 50% of decreased cultivation in the eastern region; and 44% of continued cultivation in the central region. Soil organic carbon, soil pH, annual precipitation, slope gradient, bulk density and blue reflectance were associated with increased banana cultivation while precipitation seasonality and mean annual temperature were associated with decreased banana cultivation over the past 50 years. The maps of spatial distribution and geographic shift of banana can support targeting of context-specific intensification options and policy advocacy to avert agriculture driven environmental degradation

Living income benchmarking of rural households in low-income countries

Open Access Article; Published online: 28 Sept 2020The extreme poverty line is the most commonly used benchmark for poverty, set at US$1.90 by the World Bank. Another benchmark, based on the Anker living wage methodology, is the remuneration received for a standard work week necessary for a worker to meet his/her family’s basic needs in a particular place. The living wage concept has been used extensively to address incomes of plantation workers producing agricultural commodities for international markets. More recently intense discussion has emerged concerning the ‘living income’ of smallholder farmers who produce commodities for international supply chains on their own land. In this article we propose a simple method that can be used in all types of development projects to benchmark a rural ‘living income’. We launch the Living Income Methodology, as adapted from the Living Wage Methodology, to estimate the living income for rural households. In any given location this requires about one week of fieldwork. We express it per adult equivalent per day (AE/day) and data collection is focused on rural households and their immediate surroundings. Our three case studies showed that in 2017 in Lushoto District, rural Tanzania, the living income was US$ PPP 4.04/AE/day, in Isingiro District, rural Uganda, 3.82 and in Sidama Zone, rural Ethiopia, 3.60. In all cases, the extreme poverty line of US$ PPP 1.90 per capita per day is insufficient to meet the basic human rights for a decent living in low-income countries. The Living Income Methodology provides a transparent local benchmark that can be used to assess development opportunities of rural households, by employers in rural areas, including farmers hiring in labour, while respecting basic human rights on a decent living. It can be used to reflect on progress of rural households in low-income countries on their aspired path out of poverty. It further provides a meaningful benchmark to measure progress on Sustainable Development Goal 1, eliminating poverty, and 2, zero hunger and sustainable food systems, allowing for consideration of the local context

Implementation of early next-generation sequencing for inborn errors of immunity: a prospective observational cohort study of diagnostic yield and clinical implications in Dutch genome diagnostic centers

Objective Inborn errors of immunity (IEI) are a heterogeneous group of disorders, affecting different components of the immune system. Over 450 IEI related genes have been identified, with new genes continually being recognized. This makes the early application of next-generation sequencing (NGS) as a diagnostic method in the evaluation of IEI a promising development. We aimed to provide an overview of the diagnostic yield and time to diagnosis in a cohort of patients suspected of IEI and evaluated by an NGS based IEI panel early in the diagnostic trajectory in a multicenter setting in the Netherlands. Study DesignWe performed a prospective observational cohort study. We collected data of 165 patients with a clinical suspicion of IEI without prior NGS based panel evaluation that were referred for early NGS using a uniform IEI gene panel. The diagnostic yield was assessed in terms of definitive genetic diagnoses, inconclusive diagnoses and patients without abnormalities in the IEI gene panel. We also assessed time to diagnosis and clinical implications. ResultsFor children, the median time from first consultation to diagnosis was 119 days versus 124 days for adult patients (U=2323; p=0.644). The median turn-around time (TAT) of genetic testing was 56 days in pediatric patients and 60 days in adult patients (U=1892; p=0.191). A definitive molecular diagnosis was made in 25/65 (24.6%) of pediatric patients and 9/100 (9%) of adults. Most diagnosed disorders were identified in the categories of immune dysregulation (n=10/25; 40%), antibody deficiencies (n=5/25; 20%), and phagocyte diseases (n=5/25; 20%). Inconclusive outcomes were found in 76/165 (46.1%) patients. Within the patient group with a genetic diagnosis, a change in disease management occurred in 76% of patients. ConclusionIn this cohort, the highest yields of NGS based evaluation for IEI early in the diagnostic trajectory were found in pediatric patients, and in the disease categories immune dysregulation and phagocyte diseases. In cases where a definitive diagnosis was made, this led to important disease management implications in a large majority of patients. More research is needed to establish a uniform diagnostic pathway for cases with inconclusive diagnoses, including variants of unknown significance.Transplantation and immunomodulatio