Blog IICA

Evidences

179 results

Technologies by supply chain: citrus

01/08/2022 Go to Evidence

Plant replacement, fertilization, IPM, quality and post-harvest were prioritized.

Reposición de plantas, fertilización, manejo integrado de plagas, calidad y postcosecha fueron priorizados.

Low dairy costs

01/08/2022 Go to Evidence

In dairy products, input and labor costs decreased (with methodological caution). US$ 33,854 (inputs) and US$ 11,507 (labor).

En lácteos bajaron costos de insumos y mano de obra (con cautela metodológica). US$ 33.854 (insumos) y US$ 11.507 (mano de obra).

Citrus technology adoption

01/08/2022 Go to Evidence

0.293 is the increase in technological adoption (citrus), which is highly significant.

0,293 es el aumento en adopción tecnológica (cítricos), altamente significativo.

PRODAF operability

01/08/2022 Go to Evidence

Two provinces and four value chains were prioritized based on technological gaps and economic relevance. These included Chaco (cotton, livestock) and Entre Ríos (citrus, dairy).

2 provincias y 4 cadenas fueron priorizadas según brechas tecnológicas y relevancia económica. En Chaco (algodón, ganadería) y Entre Ríos (cítricos, lácteos).

Differentiated technological menus

01/08/2022 Go to Evidence

The program defined specific technological menus for cotton, livestock, dairy and citrus, aligned with gaps and good practices.

El programa definió menús tecnológicos específicos para algodón, ganadería, lácteos y cítricos, alineados a brechas y buenas prácticas.

Plan distribution

01/08/2022 Go to Evidence

795, 565, 333 and 317 plans were executed in cotton, livestock, dairy and citrus respectively, demonstrating PRODAF's multi-channel focus.

795, 565, 333 y 317 planes se ejecutaron en algodón, ganadería, lácteos y cítricos respectivamente, evidenciando la focalización multicanal de PRODAF.

Strategic Foresight in the Agri-Food Chain

22/03/2022 Go to Evidence

The study conducts a systematic review of the methods applied in prospective studies for strategic planning of agri-food chains in Latin America and the Caribbean between 2010 and 2021. It examines the most widely used methodologies (such as MACTOR, MICMAC, and Delphi), their contributions to decision-making, and the challenges that remain in institutionalizing regional foresight. It also highlights the importance of incorporating a long-term vision that links sustainability, innovation, and food security in the development of agri-food production systems.

Universidad Autónoma de Baja California (UABC). Ensenada, Baja California, México.

Agribusiness

15/03/2022 Go to Evidence

26.7% of Brazil's GDP accounted for agribusiness in 2020, while agricultural production alone reached 7% (Cruz et al., 2022).

En 2020, la agroindustria en su conjunto (incluidos suministros, industria, servicios y producción agrícola) representó el 26,7% del Producto Interno Bruto (PIB) de Brasil, mientras que la producción agrícola por sí sola (sector primario de la producción en el campo) representó alrededor del 7%. del PIB, (Cruz. et al, 2022)

Cruz. et al, 2022. Brazil’s Agribusiness Economic Miracle: Exploring Food Supply Chain Transformations for Promoting Win–Win Investments

Country: Brazil

6 Pathways Connecting Agriculture-Nutrition

01/02/2022 Go to Evidence

Nutritional outcomes and agriculture are linked in six important ways: as a source of food, as a source of income, through food prices, women's empowerment, women's time use, and women's health and nutritional status (Duncan et al., 2022).

Los resultados nutricionales y la agricultura están vinculados de 6 maneras importantes: como fuente de alimentos, como fuente de ingresos, a través de precios de alimentos, empoderamiento de mujeres, utilización del tiempo de las mujeres, y salud y estado nutricional de las mujeres (Duncan et al., 2022).

uncan, E., Ashton, L., Abdulai, A. R., Sawadogo-Lewis, T., King, S. E., Fraser, E. D. G., Vosti, S., Haines, J., Knight, F., & Roberton, T. (2022). Connecting the food and agriculture sector to nutrition interventions for improved health outcomes. Food Security, 14, 657-675. https://doi.org/10.1007/s12571-022-01262-3

Forest Commodities Linked to Deforestation

28/10/2021 Go to Evidence

4 main forest commodities (cocoa, palm oil, soybean and timber) have been identified as drivers of deforestation and are subject to various VSS (Larrea et al., 2021).

4 commodities forestales principales (cacao, aceite de palma, soja y madera) han sido identificados como impulsores de la deforestación y son objeto de varios VSS (Larrea et al., 2021).