Decision support for optimised irrigation scheduling

The system, developed under the FLOW-AID (an FP6 project), is a farm level water management system of special value in situations where the water availability and quality is limited. This market-ready precision irrigation management system features new models, hardware and software. The hardware platform delivers a maintenance-free low cost dielectric tensiometer and several low-end irrigation or fertigation controllers for serving different situations. The software includes a complete, web based, Decision Support System (DSS) that consists of an expert planner for farm zoning (MOPECO) and a universal irrigation scheduler, based on crop-water stress models (UNIPI) and water and nutrient uptake calculations. The system, designed also to service greenhouse fertigation and hydroponics, is scalable from one to many zones. It consists of 1) a data gathering tool which uploads agronomic data, from monitored crops around the world, to a central web Data Base (DB), and 2) a web based Decision Support System (DSS). The DSS processes intelligently the data of the crop using Crop Response Models, Nutrient Uptake Models and Water Uptake Models. The central system returns over Internet to the low-end controller a command file containing water scheduling and nutrient supply guideline

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Sustainable Irrigation in Agriculture: An Analysis of Global Research

Irrigated agriculture plays a fundamental role as a supplier of food and raw materials. However, it is also the world’s largest water user. In recent years, there has been an increase in the number of studies analyzing agricultural irrigation from the perspective of sustainability with a focus on its environmental, economic, and social impacts. This study seeks to analyze the dynamics of global research in sustainable irrigation in agriculture between 1999 and 2018, including the main agents promoting it and the topics that have received the most attention. To do this, a review and a bibliometric analysis were carried out on a sample of 713 articles. The results show that sustainability is a line of study that is becoming increasingly more prominent within research in irrigation. The study also reveals the existence of substantial differences and preferred topics in the research undertaken by different countries. The priority issues addressed in the research were climatic change, environmental impact, and natural resources conservation; unconventional water resources; irrigation technology and innovation; and water use efficiency. Finally, the findings indicate a series of areas related to sustainable irrigation in agriculture in which research should be promoted

A demonstration greenhouse for Malaysian Horticulture : trip report October 2010

This report results from the project “Tropical Horticulture in Malaysia”. Modernization of the greenhouse horticulture sector in Malaysiar is required in order to realize better quality of the product, higher yields and less production costs

Tanzania Country Climate Risk Profile Series, Mufindi District

The agricultural sector in Tanzania is facing high climatic risks. Frequent and severe temperature and precipitation, recurrent droughts and increased incidences of pests and diseases are some of the climate effects that have been observed. Catalyzed with rising input prices and price volatility, there has been a decline in food productivity and farmer incomes. The natural resources that support agricultural production—including rivers and forests—are also degrading due to extreme climate events. Projections indicate that these trends are likely to worsen in the coming decades, with temperatures increasing by nearly 2.7°C by and 4.5°C by 2060 and 2090 respectively (Irish Aid , 2018). At the same time, both day and night temperatures will become more extreme, and precipitation will begin to vary more dramatically by geographic area. Smallholder farmers are particularly vulnerable to the effects of climate change because of their low access to the resources needed to adapt to changing conditions. Among smallholders, women are more vulnerable due to their outsized role in agriculture and the social limitations placed on their decision-making and inclusion. A lack of coordination and information symmetry between stakeholders have prevented the full implementation of policies aimed at mitigating climate change. The government, with the support of development partners, has put in place a number of policies, strategies and guidelines to address climate change. The National Agriculture Policy (2013), National Climate Change Strategy (2012), National Adaptation Programme of Action (2007), and the Climate Smart Agriculture guideline (2007) provide a framework for creating agricultural resiliency in the face of climate change. This Climate-Smart Agriculture (CSA) Profile documents the need for, and adoption of CSA practices at the local level in Mufindi District. This profile is an output of the CSA/SuPER project on Upscaling CSA with Small-Scale Food Producers Organized through Village Savings and Lending Associations (VSLA). The project is implemented by Cooperative Assistance and Relief Everywhere (CARE) International, the International Center for Tropical Agriculture (CIAT) (now part of the Alliance of Bioversity International and CIAT), Sokoine University of Agriculture (SUA), and Wageningen University and Research (WUR). Both qualitative and quantitative methods were used to gather the information herein, in accordance with the methodology employed by Mwongera et al. (2015). Secondary information was collected through an extensive literature review. Primary information was collected from interviews with agricultural experts, farmer focus group discussions, stakeholder workshops, and farmer interviews in the Mufindi District. This profile is organized into six major sections based on the analytical steps of the study. The first section describes the contextual importance of agriculture to Mufindi livelihoods and households. The second describes historic and future climatic trends. The third section highlights farmers’ priority value chains. The fourth section addresses the challenges and cross-cutting issues in the sector. The fifth section details climate hazards experienced by farmers, as well as the current and proposed adaptation strategies. Finally, the sixth section outlines the policies related to CSA and the institutions that facilitate implementation of climate change initiatives