Datasets of the environmental factors and management practices of the smallholder tomato production systems in the Colombian Andes

© 2019 The Author(s) Datasets presented here were employed in the main work “Understanding the heterogeneity of smallholder production systems in the Andean tropics – The case of Colombian tomato growers” Gil, et al., 2019. In this region, tomato crop is developed under two technological levels: low, carried out under open field (OF) conditions and, a high, by using greenhouses (GH). For OF, data belong to five municipalities of the Guanentá province (Santander department), while for GH, data belong to five municipalities of the Alto Ricaurte province (Boyacá department). The data presented here includes information on soil parental materials and climate variables (averages ± standard deviations) relevant from the agricultural point of view, which were calculated from historical climate series. Soils natural fertility data, obtained by sampling the production areas, are also presented. After filtering the data, 67 samples were obtained for OF and 70 for the GH. For GH, a dataset with the results of 38 soil samples taken inside greenhouses were paired with the results of samples taken outside these greenhouses in uncropped areas. In the case of these soil analyses, the data correspond to tables with the results reported by the laboratory for both, chemical and physical variables, for each location in which soil samples were taken. In this work, the main dataset is one that contains the inputs of fertilizers and water, and the corresponding yields of tomato production cycles managed by local growers. This information was collected through two data collection tools: surveys (SVY) to growers about these aspects in their last production cycle, and through detailed follow-ups of selected production cycles (FWU). For the OF, we collected data from 71 cycles through the surveys and 22 through the follow-ups, while for the GH, information from 138 to 38 tomato cycles was collected through surveys and follow-ups, respectively. A table with the results aggregated by tomato cycle is attached.status: publishe

Modelling tomato crop growth and development in relation to nitrogen fertilization under high altitude cold tropical conditions

Nowadays, crop models are a widespread tool for both research and production activities. However, most of the models were developed and calibrated for potential conditions at places where there is a narrow gap between potential and actual yields. The objective of this work was to incorporate the effect of nitrogen (N) supply in a tomato crop growth model calibrated for high altitude tropical conditions. We carried out field experiments to determine the effect of N fertilization on plant parameters such as leaf area (LA) and allocation of dry matter (DM) in fruits. A total of 10 treatments ranging from 196 to 1114 N kg ha-1 were evaluated, six of them were used in the model calibration and the remaining four were reserved for validation. Plant development was determined by means of accumulated thermal time (ATT) using a base temperature of 10°C. LA results were fitted with a nonparametric model to predict the changes in LA as response to N supply. This N-model was introduced as a module within the tomato model. The N-module calculates LA for a given amount of soil N available and ATT. Simultaneously, a nitrogen stress factor (NSF) was calculated as the ratio between daily available soil N per plant and N demand to reach the potential growth. If NSF is less than one, a leaf area reduction factor (LARF) was calculated as the ratio among LA estimated by the nonparametric model and that calculated by the potential model. In this way, a deficient N-supply affects plant growth by correcting the leaf DM produced at the end of each day by LARF. The performance of the model was satisfactory as shown by statistics such as the root mean square error, model efficiency and coefficient of determination.cited By 0 document_type: Conference Paper source: Scopusstatus: publishe

Simulation and validation of the airflow inside a naturally ventilated greenhouse designed for tropical conditions

In the Colombian high-altitude tropics, protected horticulture is carried out under passively ventilated greenhouses. Still, nowadays, the current knowledge about the performance of these structures in the commercial areas under tropical conditions is scarce. The present work presents a combined methodology for the study of the natural ventilation through 3D computational fluid dynamics numerical simulation and 2D sonic anemometry. The experimental work was developed in a multi span greenhouse conformed by five spans with a ground covered area of 3025 m2 located in the Bogota savannah. This methodological approach obtained the airflow patterns in the experimental greenhouse under the prevailing wind and temperature conditions of the study region. Measurements and simulations were made for the daytime period (6 to 18 h) in which the following three ventilation configurations were considered: side ventilation, roof ventilation and a combination of both. The results showed high efficiency of the combined wall and roof ventilation for low-speed wind conditions (<1.5 m s-1). The airflow pattern simulations showed a high correlation with the wind direction and speed measured through sonic anemometry.cited By 0 document_type: Conference Paper source: Scopusstatus: publishe

Product carbon footprints and their uncertainties in comparative decision context

In response to growing awareness of climate change, requests to establish product carbon footprints have been increasing. Product carbon footprints are life cycle assessments restricted to just one impact category, global warming. Product carbon footprint studies generate life cycle inventory results, listing the environmental emissions of greenhouse gases from a product 's lifecycle, and characterize these by their global warming potentials, producing product carbon footprints that are commonly communicated as point values. In the present research we show that the uncertainties surrounding these point values necessitate more sophisticated ways of communicating product carbon footprints, using different sizes of catfish (Pangasius spp.) farms in Vietnam as a case study. As most product carbon footprint studies only have a comparative meaning, we used dependent sampling to produce relative results in order to increase the power for identifying environmentally superior products. We therefore argue that product carbon footprints, supported by quantitative uncertainty estimates, should be used to test hypotheses, rather than to provide point value estimates or plain confidence intervals of products' environmental performance

Approaches for modelling the energy flow in food chains

© 2015 Gowreesunker and Tassou; licensee Springer. "This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. "Background: The heavy reliance of the global food chain on the use of fossil fuels and anticipated rise in global population threatens future global food security. Due to the complexity of the food and energy systems, the impact of adequate food, climate or energy policies should be carefully examined in a modelling framework which considers the interaction of the food and energy systems. However, due to the different modelling approaches available, it can be very difficult to identify which method best suits the required purpose. Method: This paper presents the three main modelling approaches as ‘top-down’, ‘bottom-up’ and hybrids. It reviews different models under each category in terms of the practicality, benefits and limitations with reference to different past studies. Results: Bottom-up approaches generally tend to provide high levels of details, but their specificity to particular products/processes detracts their application to holistic models. On the other hand, top-down approaches consider the holistic aspects of the food chain, but the limited level of disaggregation prevents the identification of energy and environmental hot-spots. As a result, hybrid models seek to reduce the limitations of the individual approaches. Conclusions: This paper shows that the choice of one modelling approach over another depends on a variety of criteria including data requirements, uncertainty, available tools, time and labour intensity. Furthermore, future models and studies have to increasingly consider the inter-dependence of implementing social, demographic, economic and climate considerations in a holistic context to predict both short- and long-term impacts of the food chain.This study is a result of funding from the Research Councils UK to set up the RCUK National Centre for Sustainable Energy Use in Food Chains (CSEF), grant no. EP/K011820/1