Higher productivity in Danish arable crop production

The projected expansion of organic farming in Denmark is conditioned on increased arable crop production, which requires higher and more stable crop yields. This must be achieved while also phasing out the use of imported conventional manure and reducing environmental impacts, such as greenhouse gas (GHG) emissions. HighCrop has two main hypotheses: 1) Higher yields and reduced environmental impact can be achieved by introduction of energy crops and improved management of nitrogen (N) in catch crops, green manure and crop residues; and 2) Low yields in practical arable organic farming are caused by a knowledge gap that requires new strategic management tools to overcome. HighCrop applies a comprehensive approach linking research, development and demonstration. Research will improve our understanding of effects of N dynamics and weed pressure on crop productivity, N leaching, GHG emissions and soil biodiversity to derive essential models for N and weed management in organic arable cropping systems. The key to development and dissemination will be new knowledge transfer tools which will be targeted by identification of real and perceived barriers on the farm, as well as in supply and knowledge chains. These concepts and tools will be tested on organic farms and disseminated to Danish organic advisers and farmers. HighCrop will also make use of participatory approaches to synthesize and disseminate knowledge by organising workshops focusing on different supply chains

Scaling Success: Lessons from Adaptation Pilots in the Rainfed Regions of India

"Scaling Success" examines how agricultural communities are adapting to the challenges posed by climate change through the lens of India's rainfed agriculture regions. Rainfed agriculture currently occupies 58 percent of India's cultivated land and accounts for up to 40 percent of its total food production. However, these regions face potential production losses of more than $200 billion USD in rice, wheat, and maize by 2050 due to the effects of climate change. Unless action is taken soon at a large scale, farmers will see sharp decreases in revenue and yields.Rainfed regions across the globe have been an important focus for the first generation of adaptation projects, but to date, few have achieved a scale that can be truly transformational. Drawing on lessons learnt from 21 case studies of rainfed agriculture interventions, the report provides guidance on how to design, fund and support adaptation projects that can achieve scale

Modelling and simulation framework for reactive transport of organic contaminants in bed-sediments using a pure java object - oriented paradigm

Numerical modelling and simulation of organic contaminant reactive transport in the environment is being increasingly relied upon for a wide range of tasks associated with risk-based decision-making, such as prediction of contaminant profiles, optimisation of remediation methods, and monitoring of changes resulting from an implemented remediation scheme. The lack of integration of multiple mechanistic models to a single modelling framework, however, has prevented the field of reactive transport modelling in bed-sediments from developing a cohesive understanding of contaminant fate and behaviour in the aquatic sediment environment. This paper will investigate the problems involved in the model integration process, discuss modelling and software development approaches, and present preliminary results from use of CORETRANS, a predictive modelling framework that simulates 1-dimensional organic contaminant reaction and transport in bed-sediments

Maize-Nutrient-Manager: A mobile phone application for field-specific, balanced nutrient management advisory

To increase productivity and profitability, while limiting nutrient losses and related GHG-emissions, African smallholders need more tailored fertilizer advice. Yet, such advice critically hinges upon – largely lacking – field-level management data, as management is key to efficient fertilizer use. The Maize- Nutrient-Manager (MNM) mobile phone application enables collection of such data at scale, and directly converts this data into actionable advice for the farmer. Focusing on field-level management data, MNM can identify those management practices that are currently imperative for enhancing smallholder farmers’ efficient use of fertilizers in their locality, thereby increasing productivity while reducing greenhouse gas (GHG) emissions. This document describes the background, design principles and development process of then MNM mobile phone application, as well as its pilot use in advisory practice in the Mbozi and Momba districts of Songwe region, Tanzania