Efficient water management is crucial for sustainable agriculture and water resource conservation, particularly in water-scarce regions. This study investigated the effect of different irrigation depths on onion (Allium cepa L.) yield and water use patterns in a semi-arid tropical region of Colombia, using a completely randomized design with five treatments. The treatments ranged from 0–100% of total available water (TAW), T1 (100% of TAW), T2 (80% of TAW), T3 (60% of TAW), T4 (40% of TAW), and T5 (20% of TAW). The experiment was conducted in a greenhouse during one growing season (2022–2023). The normalized water productivity (WP *), irrigation water productivity (IWP), consumptive water productivity, blue water footprint (WF_blue), marginal water use efficiency (MWUE), and elasticity of water productivity (EWP), as well as some parameters of quality onion, were determined. The soil in the experimental field was classified as sandy loam; the results show that the WP * of onion is 17.42 g m⁻², the water production function shows the maximum production will be achieved at a water application depth of approximately 943 mm, and beyond that, the biomass yield will decrease with additional water application, IWP values for onion ranged from 2.18 to 3.42 kg m⁻³, the highest Wf_blue was in T5 (34.10 m³ t⁻¹), and low Wf_blue was T1 (20.95 m³ t⁻¹). In terms of quality, treatment T1 had the most favorable effects on bulb weight, polar diameter, and equatorial diameter, while treatment T5 had the least favorable effects. The study highlights the importance of efficient irrigation on sandy loam soils to maximize yield and water use efficiency. It provides valuable data for evaluating the potential yield benefits of precision irrigation in the study area. Optimizing irrigation depth can significantly improve onion yield and water use efficiency in semi-arid regions.

Crop models that can accurately estimate yield and final biomass have been used for major herbaceous crops and to a lesser extent in forage systems. The AquaCrop version 7.0 contains new modules that have been introduced to simulate the growth and production of perennial herbaceous forage crops. Simulated forage yields as a function of water consumption provide valuable information that allows farmers to make decisions for adapting to both climate variability and change. The study aimed to calibrate and validate the AquaCrop model for perennial ryegrass (Lolium perenne L.) in the high tropics of Colombia (South America). The experiments were conducted during two consecutive seasons, in which perennial ryegrass meadows were subjected to two irrigation regimes: full irrigation and no irrigation. The model was evaluated using precision, accuracy, and simulation error indices. The overall performance of AquaCrop in simulating canopy cover, biomass and soil water content showed a good match between measured and simulated data. The calibration results indicated an acceptable measurement of simulated canopy cover (CC) (R² = 0.95, d-index = 0.41, RMSE = 9.4%, NRMSE = 12.2%, and FE = −21.72). The model satisfactorily simulated cumulative dry mass (R² = 0.95, d-index = 0.98, RMSE = 2. 63 t ha⁻¹, NRMSE = 11.8%, and FE = 0.94). Though the biomass values obtained in the end-of-season cuts were underestimated by the model, soil water content was simulated with reasonable accuracy (R² = 0.82, d-index = 0.84, RMSE = 6.10 mm, NRMSE = 4.80%, and FE = 0.32). During validation, CC simulations were good, except under water deficit conditions, where model performance was poor (R² = 0.42, d-index = 0.01, RMSE = 40.60%, NRMSE = 40.90%, and FE = −25.71); biomass and soil water content simulations were reasonably good. The above results confirmed AquaCrop’s (v 7.0) suitability for simulating responses to water for perennial ryegrass. A single crop file was developed for managing a full season and can be confidently applied to direct future research to improve the understanding of the necessary processes and interactions for the development of perennial herbaceous forage crops.

Introduction. Typologies can be used as a mechanism to address the heterogeneity of agricultural systems. Panela, or non-centrifuged cane sugar, is a traditional sweetener of great economic and cultural importance in Colombia, it generates 236,000 direct jobs per year and is produced in 47 % of the country’s municipalities. Objective. To identify typologies of agro-industrial production units (UPA) of panela based on technical and socioeconomic characteristics in the department of Huila, Colombia. Materials and methods. The multivariate statistical technique of mixed data factor analysis (AFDM) was used with data from 94 UPAs, taken from a representative cross-sectional survey of the year 2019 carried out within the framework of this study. The survey provided information on production cycle, socioeconomic, and environmental management management of by-products. Results. Three differentiated types of UPA were identified: type 1(6 UPA- 6.38 %): composed of units oriented to productive diversification and technological transition; type 2 (63 UPA-67.02 %): composed of units with traditional management of the cultivation, processing and use of by-products; and type 3 (25 UPA-26,6 %): composed of units specialized in the production of panela, with greater technification in cultivation and processing of sugarcane. Conclusions. Different heterogeneous groups of panela agro-industrial production units were identified in the department of Huila, Colombia, where a traditional small-scale operation model is developed. The empirical exploration of this research made it possible to delineate the potential for technology adoption in the identified groups. Technology transfer programs should consider the technical and socioeconomic characteristics of the UPAs.

En Colombia, la producción de panela es una de las agroindustrias más tradicionales que, a pesar de su antigüedad, continúa cumpliendo importantes funciones desde el ámbito social, económico y de seguridad alimentaria. De hecho, la agroindustria panelera es un ejemplo de las llamadas agroindustrias rurales, la cual cuenta con más de 70.000 cultivadores de caña de pequeña a mediana escala, quienes realizan el procesamiento de la caña en cerca de 18.000 trapiches, distribuidos principalmente en los diferentes departamentos de la región Andina del país. Desde el punto de vista social, la panela representa una importante actividad que genera empleo e ingresos a cerca de 350.000 personas, quienes se vinculan como trabajadores en las faenas agrícolas y de molienda. De hecho, la agroindustria panelera se sigue considerando la segunda actividad generadora de empleo en las áreas rurales del país, después de la producción de café.En este documento se presenta el modelo productivo de caña de azúcar destinada a la producción de panela en el departamento de Cundinamarca, el cual incluye la descripción de las áreas de cultivo, la descripción de la especie, los requerimientos climáticos y de suelo, la descripción de la tecnología y recomendaciones para el manejo del cultivo de la caña, la cosecha, la postcosecha y la transformación en panela, brindando a su vez algunos indicadores técnicos, económicos y ambientales de la producción panelera en el departamento.

Germplasm banks are the most significant repository for plant genetic resources for food and agriculture (PGRFA) worldwide. Despite their strategic importance, national germplasm banks of tropical megadiverse developing countries such as Colombia have extremely limited funds. Therefore, making strategic decisions about research investment is essential. Here, we designed a data-driven approach to build an index that sorts Colombian PGRFA into three groups: high, medium, or low priority, based on four pillars of information from open-access databases and aligned with the sustainable goals of no poverty and zero hunger: Geographic origin, vulnerability status, economic benefits, and food security importance. We analyzed 345 PGRFA using the index, separating them into two groups, 275 already conserved in the Colombian germplasm bank (BGVCOL group) and 70 not currently conserved in the BGVCOL (NCB group). We used fuzzy logic to classify each PGRFA by each pillar and integrate it to obtain a priority index. Missing data for native crops were frequent in the BGVCOL group. Therefore we adopted an imputation strategy to fill the gaps and calculated the uncertainty. After applying the index, PGRFA with higher priority were 24 (8.72%) from the BGVCOL (i.e., 15 potatoes, three tomatoes, two tree tomatoes, pineapple, cocoa, papaya, and yacon) and one from NCB (i.e., coffee). We concluded that this methodology successfully prioritized PGRFA in Colombia and shows the big holes of knowledge for future research and alternatives to improve this index. The versatility of this methodology could be helpful in other genebanks with budget limitations for research investment.

Climate variability is a major threat to maize (Zea mays) crops in Colombia, posing a risk to food security and compliance with Sustainable Development Goals. Therefore, this study aimed to assess the physical vulnerability of maize crops to climate variability in the semi-arid region of the Department of Cesar, Colombia, using the AquaCrop-OS model. Specifically, the study evaluated the vulnerability of maize crops to three typical meteorological years (dry, intermediate, and wet) adjusted to the growth cycle in two semesters of the year (periods I and II). An analysis of 43 years of data (1980–2022) revealed that most years in the area can be classified as intermediate, whereas the number of wet years was higher than the number of dry years. However, under the intermediate typical meteorological year scenario, maize cultivation in the department of Cesar experienced severe drought conditions during periods I and II. The study’s vulnerability curve showed an increasing rate within the yield loss index when the average water stress index was between 0.5 and 0.8 for period I. The rate of increase slowed when the index exceeded 0.9. For period II, the maize crop presented a lower degree of vulnerability, with 64% of the area experiencing a yield loss rate between 5% and 30%. The study also determined the required irrigation depth of water for optimal yields, which ranged from 70 to 160 mm during the growing season for all maize crop scenarios in the Department of Cesar. The results of this study can contribute to the consolidation of a database of physical vulnerability and threats of precipitation anomalies on regional and national scales. Overall, this study’s evaluation of the physical vulnerability of maize crops can help producers develop better strategies to mitigate the impacts of climate variability and ensure regional food security.