This paper presents the main features of a unique decision-support tool developed for selecting tree species in coffee and cocoa agroforestry systems. This tool aims at assisting in the selection of appropriate shade trees taking into account local conditions as well as needs and preferences of smallholder farmers while maximizing ecosystem services from plot to landscape level. This user-friendly and practical tool provides site-specific recommendations on tree species selection via simple graphical displays and is targeted towards extension services and stakeholders directly involved in sustainable agroforestry and adaptation to climate change. The tool is based on a simple protocol to collect local agroforestry knowledge through farmers’ interviews and rankings of tree species with respect to locally perceived key ecosystem services. The data collected are first analysed using the BradleyTerry2 package in R, yielding the ranking scores that are used in the decision-support tool. Originally developed for coffee and cocoa systems of Uganda and Ghana, this tool can be extended to other producing regions of the world as well as to other cropping systems. The tool will be tested to see if repeated assessments show consistent ranking scores, and to see if the use of the tool by extension workers improves their shade tree advice to local farmers.

Agricultural development projects frequently promote new crop production technologies for adoption at scale on the basis of research and pilot studies in a limited number of contexts. The performance of these production technologies is often variable and dependent on context. Using an example from the Agroforestry for Food Security Project in Malawi, that promoted agroforestry technologies for soil fertility enhancement, we explore the nature and implications of variation in performance across farmers. Mean effects of these technologies, measured by differences in maize yield between agroforestry and sole maize plots, were modest but positive. However, there was large variation in those differences, some explained by altitude, plot management and fertilizer use but with much unexplained. This represents risk to farmers. Those communicating with farmers need to be honest and clear about this risk. It can be reduced by explanation in terms of contextual factors. This should be an aim of research that can often be embedded in scaling up the promotion of agronomic innovations.

Poor access to improved seeds in West and Central Africa has compromised crop yields and productivity as most farmers source the bulk of their seeds from informal channels. The use of farmer produced seeds has mostly resulted in high seedling mortality thereby presenting challenges to cocoa rehabilitation programmes across the sub region. With the aid of a mobile data collection system (MDCS), the first of its kind to enhance accuracy of survey results in an improved seed supply system through brokerage and linkages among diverse actors, this study assesses Ghanaian farmers’ access to improved hybrid cocoa seeds and provides evidence on the socio-cultural factors that affect field performance of such planting materials. Results show that farmers value a seed brokerage system (SBS), which is facilitated through group bulk purchase, timely acquisition and delivery of seeds. The study also revealed that farm size, land use type and gender have significant effect on survival rate of transplanted hybrid cocoa seedlings over two dry seasons. Regardless of the rehabilitation process, mean survival rate was high (79%) although an 11% (p < 0.000) difference occurred between gender with men recording a higher rate. The majority of farmers prefer cultivating cocoa on forest and fallow lands, implying continues degradation of forest areas. There is therefore an urgent need for a change of mind set, to advocate for land recycling to spare forest areas to thrive.

Innovation Platforms (IPs) are seen as a promising vehicle to foster a paradigm shift in agricultural research for development (AR4D). By facilitating interaction, negotiation and collective action between farmers, researchers and other stakeholders, IPs can contribute to more integrated, systemic innovation that is essential for achieving agricultural development impacts. However, successful implementation of IPs requires institutional change within AR4D establishments. The objective of this paper is to reflect on the implementation and institutionalisation of IPs in present AR4D programmes. We use experiences from sub-Saharan Africa to demonstrate how the adoption and adaptation of IPs creates both opportunities and challenges that influence platform performance and impact. Niche-regime theory is used to understand challenges, and anticipate on how to deal with them. A key concern is whether IPs in AR4D challenge or reinforce existing technology-oriented agricultural innovation paradigms. For example, stakeholder representation, facilitation and institutional embedding determine to a large extent whether the IP can strengthen systemic capacity to innovate that can lead to real paradigm change, or are merely ‘old wine in new bottles’ and a continuation of ‘business as usual’. Institutional embedding of IPs and – more broadly – the transition from technology-oriented to system-oriented AR4D approaches requires structural changes in organisational mandates, incentives, procedures and funding, as well as investments in exchange of experiences, learning and capacity development.

Hand-planted plots of across-row-oriented corn seeds (Zeamays L.) produce highly structured leaf canopies and have shown significant yield advantage over randomly planted plots in prior studies. For further investigation of the phenomenon by simulation, the objective of this study was to develop a probabilistic model for the correlation between seed orientation and initial plant orientation. In greenhouse trials, the azimuthal orientation of kernels of four different hybrids was recorded at planting. At collar setting of the seed leaf, the orientation of the seed leaf was determined and the angular data subjected to the analytical methods of circular statistics. The results indicate that the correlation between seed azimuth and seed leaf azimuth can be described by a von Mises distribution. The probabilistic seed to seed leaf azimuth model described herein may be implemented in simulation models to investigate the effect of canopy architecture, canopy closure and light interception efficiency of corn under conditions of seed oriented planting.

Seedling vigor is important to help ensure good crop establishment. In direct-seeded rice, this is particularly relevant when soil conditions are marginal. In Asia, about one third of the area of rainfed rice is situated on unfavorable soils, many of which are low in plant available P. In such environments, as farmers tend to have few resources, options to overcome poor crop establishment should be low cost and preferably seed-based. The P content of seed depends on genotype and can be augmented by soaking seeds in a P-containing solution prior to seeding (P-priming). In addition, the presence of the Pup1 quantitative trait locus can reportedly confer tolerance to low soil P availability. We tested combinations of seed priming (unprimed control, water priming, P-priming), and inherent seed P concentrations in contrasting rice genotypes (DJ123, Sadri Tor Misri), and two near isogenic sister lines of IR74 with (+Pup1) and without (−Pup1) the Pup1 QTL. Treatment effects on germination were studied in Petri dishes, while seedling growth and P accumulation were assessed using pots with P deficient soil. Germination was less than 75% in seeds with low seed P content. Seed priming with both water and P enhanced germination and seedling growth. In plants growing from high P seeds, water priming outperformed P-priming. In Sadri Tor Misri with low seed P, we observed a tendency for better performance in some parameters when P-primed. While the presence of the Pup1 QTL in IR74 increased shoot biomass and total root length, these effects could be further enhanced by water priming. Combining genetic and seed management approaches may contribute to improved rice establishment in P deficient soils but its effectiveness depends on genotype and seed attributes.

Conducting farmers participatory field trials at 40 sites for 3 consecutive years in four rice-wheat system dominated districts of Haryana state of India, this paper tested the hypothesis that zero tillage (ZT) based crop production emits less greenhouse gases and yet provide adequate economic benefits to farmers compared to the conventional tillage (CT). In each farmer's field, ZT and CT based wheat production were compared side by side for three consecutive years from 2009–10 to 2011–12. In assessing the mitigation potential of ZT, we examined the differences in input use and crop management, especially those contributing to GHGs emissions, between ZT wheat and CT wheat. We employed Cool Farm Tool (CFT) to estimate emission of GHGs from various wheat production activities. In order to assess economic benefits, we examined the difference in input costs, net returns and cost-benefit analysis of wheat production under CT and ZT. Results show that farmers can save approximately USD 79 ha−1 in terms of total production costs and increase net revenue of about USD 97.5 ha−1 under ZT compared to CT. Similarly, benefit-cost ratio under ZT is 1.43 against 1.31 under CT. Our estimate shows that shifting from CT to ZT based wheat production reduces GHG emission by 1.5 Mg CO2-eq ha−1 season−1. Overall, ZT has both climate change mitigation and economic benefits, implying the win-win outcome of better agricultural practices.

The paper describes value chain actors and institutional arrangements along value chains, and identifies major determinants of farmers’ decision making to work with middlemen/traders ‘jabbans’ (or cheese makers), and based on those identify short implications for research, development and policy processes. We hypothesize that small-scale sheep producers are more dependent on middlemen for market and loans than larger holders, leading to welfare losses. Our empirical findings based on a Heckman model applied for 120 farming households conducted in Khanasser region (Syria) show that despite unequal benefits, local arrangements are more blessing than curse for the poor. Small-scale sheep producers and middlemen developed intricate institutional arrangements that are mutually beneficial. Producers act collectively to pool sufficient quantity of milk to be attractive to traders (jabban) while gaining access to market and cash loans mainly for feed. This provides the middlemen needed supplies with reduced transaction costs. This suggests that development organizations should support local capacity of producing organizations to work together, small-scale producers to organize, develop small scale dairy processing workshops for pooling and possibly processing milk, support training for direct market access and facilitate access to loans. Finally, supporting organizations such as rural financial services and micro-finance need to ensure up-to-date market information is available to ensure fair prices are paid. They should also be able to negotiate favourable conditions for loans and reach out to these resource-poor rural populations where formal credit systems are absent.

Seasonal drought stresses as a result of changes in global climate and local weather conditions are among the major factors adversely affecting growth and productivity of Robusta coffee (Coffea canephora pierre ex froehner) in many areas producing the crop. It is believed that there exists a wide range of genetic variability among Robusta coffee clones for traits associated with drought tolerance. Therefore, in an attempt to determine differences among Robusta coffee clones for some growth, physiological and biochemical parameters and identify drought-tolerant materials, 12 months old seedlings of six clones (IC-2, IC-3, IC-4, IC-6, IC-8 and R-4) were subjected to two treatments: well-watered control and drought-stressed (soil drying) by withholding irrigation for three weeks in a rain shelter at University Putra Malaysia, Malaysia. The rate of stress development, expressed as extent of wilting and damage to leaves, was considerably higher for clones IC-8, IC-4, R-4 and IC-2 than for IC-3 and IC-6 during the stress period. Leaf water potential (LWP), stomatal conductance (gs) and rate of net photosynthesis (PN) progressively decreased but leaf proline (LP) concentration substantially increased with time of exposure of the plants to soil drying. There was a considerable difference between coffee clones for the rate of change in these parameters. All the clones except IC-6 and IC-8 showed a negative carbon balance with the most negative value for R-4 at the end of the stress period. Six days after rewatering, LWP, gs and PN increased rapidly while LP concentration decreased and reached a level equivalent to those of well-watered plants, especially for clones IC-3 and IC-6. Among the drought-stressed plants, IC-6 and IC-3 had still significantly higher shoot growth, total dry matter yield and root to shoot ratio than did IC-2, IC-4, IC-8 and R-4. In general, clones IC-6 and IC-3 exhibited quite a better performance in almost all the parameters considered in this study and seemed to be less sensitive to drought stress. Hence, drought tolerance attributes in these clones could be linked to a more effective osmotic adjustment due to more rapid accumulation of LP and probably some morphological parameters, such as increased root-to-shoot ratio. However, further analyses at molecular level, detail biochemical studies and observations under diverse field conditions are required to come up with more conclusive recommendations.

A defining characteristic of many rainfed tropical agricultural systems is their vulnerability to weather variability. There is now increased attention paid to climate-agriculture links as the world is focused on climate change. This has shown the need for increased understanding of current and future climate and the links to agricultural investment decisions, particularly farmers’ decisions, and that integrated strategies for coping with climate change need to start with managing current climate risk. Research, largely from an Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA) project to demonstrate the value of such increased understanding, is presented in this issue of the journal. Key lessons from this research are as follows:

1. 1. Statistical methods of analysis of historical climate data that are relevant to agriculture need not be complex. The most critical point is to describe the climate in terms of events of direct relevance to farming (such as the date of the start of a rainy season) rather than simple standard measures (such as annual total rainfall).

2. 2. Analysis requires access to relevant data, tools and expertise. Daily climate data, both current and historical, are primarily the responsibility of national meteorological services (NMS). Accessing such data, particularly daily data, is not always easy. Including staff from the NMS as research partners, not just data providers, can reduce this problem.

3. 3. Farmers’ perceptions of climate variation, risk and change are complex. They are keenly aware of variability, but there is evidence that they over-estimate risks of negative impacts and thereby fail to make use of good conditions when they occur. There is also evidence that multiple causes of changes are confounded, so farmers who observe decreasing crop production may not be distinguishing between rainfall change and declining soil fertility or other conditions. Hence any project working with farmers’ coping and adaptation to climate must also have access to analyses of observed climate data from nearby recording stations.

4. 4. Mechanisms for reducing and coping with risks are exemplified in pastoral systems that exist in the most variable environments. New approaches to risk transfer, such as index-based insurance, show potential for positive impact.

5. 5. Skilful seasonal forecasts, which give a better indication of the coming season than a simple average, would help farmers take decisions for the coming cropping season. Increasing meteorological knowledge shows that such forecasting is possible for parts of Africa. There are institutional barriers to farmers accessing and using the forecast information. Furthermore, the skill of the forecasts is currently limited so that there are maybe still only a few rational choices for a farmer to make on the basis of a forecast.

With the justified current interest in climate and agriculture, all stakeholders including researchers, data providers, policy developers and extension workers will need to work together to ensure that interventions are based on a correct interpretation of a valid analysis of relevant data.

Rainfall variability, both within and between seasons, is reflected in highly variable crop growth and yields in rainfed agriculture in sub-Saharan Africa and results in varying degrees of weather-induced risk associated with a wide range of crop, soil and water management innovations. In addition there is both growing evidence and concern that changes in rainfall patterns associated with global warming may substantively affect the nature of such risk. Eighty-nine years of daily rainfall data from a site in southern Zambia are analysed. The analyses illustrate approaches to assessing the extent of possible trends in rainfall patterns and the calculation of weather-induced risk associated with the inter- and intra-seasonal variability of the rainfall amounts. Trend analyses use monthly rainfall totals and the number of rain days in each month. No simple trends were found. The daily data were then processed to examine important rain dependent aspects of crop production such as the date of the start of the rains and the risk of a long dry spell, both following planting and around flowering. The same approach is used to assess the risk of examples of crop disease in instances when a ‘weather trigger’ for the disease can be specified. A crop water satisfaction index is also used to compare risks from choices of crops with different maturity lengths and cropping strategies. Finally a different approach to the calculations of these risks fits a Markov chain model to the occurrence of rain, with results then derived from this model. The analyses shows the relevance of this latter approach when relatively short daily rainfall records are available and is illustrated through a comparison of the effects of El Niño, La Niña and Ordinary years on rainfall distribution patterns.

This paper investigates farmers’ perceptions of climate change and variability in southwest Uganda and compares them with daily rainfall and temperature measurements from the 1960s to the present, including trends in daily rainfall and temperature, seasonality, changing probability of risk and intensity of rainfall events. Statistical analyses and modelling of rainfall and temperature were performed and contrasted with qualitative data collected through a semi-structured questionnaire. The fieldwork showed that farmers perceived regional climate to have changed in the past 20 years. In particular, farmers felt that temperature had increased and seasonality and variability had changed, with the first rainy season between March and May becoming more variable. Farmers reported detailed accounts of climate characteristics during specific years, with recent droughts in the late 1990s and late 2000s confirming local perceptions that there has been a shift in climate towards more variable conditions that are less favourable to production. There is a clear signal that temperature has been increasing in the climate data and, to a lesser extent, evidence that the reliability of rains in the first season has decreased slightly. However, rainfall measurements do not show a downward trend in rainfall amount, a significant shift in the intensity of rainfall events or in the start and end of the rainy seasons. We explore why there are some differences between farmers’ perceptions and the climate data due to different associations of risk between ideal rainfall by farmers, including the amount and distribution needed for production, meteorological definitions of normal rainfall or the long-term statistical mean and its variation, and the impact of higher temperatures. The paper reflects on the methodological approach and considers the implications for communicating information about risk to users in order to support agricultural innovation.