Crop management based on field observations: Case studies in sugarcane and coffee

Cock, James H.; Oberthür, Thomas; Isaacs, C. H.; Läderach, Peter; Palma, A.; Carbonell, Javier; Victoria, Jorge; Watts, Geoff; Amaya, A.; Collet, Laure; Lema, Germán; Anderson, Einar

doi:10.1016/j.agsy.2011.07.001

Cited by 30 publications

(28 citation statements)

References 24 publications

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“…refs. 13,[22][23][24][25] ), the key to the preparatory phase will be to create a flexible enabling environment for selfdirected change among farmers, consumers and value chain participants in response to climatic changes, situated within the wider context of rapid demographic and economic change 3,5,9 .This analysis, like many others, operates in a context of high uncertainty 9 . Our estimates of transformational adaptation are based on simulations of a single crop suitability model and are probably conservative owing to projected changes in climate extremes, pests and diseases, soil, trade and socio-economic constraints not considered here, and the fact that threshold exceedance may happen after 2100.…”

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Timescales of transformational climate change adaptation in sub-Saharan African agriculture

et al. 2016

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Climate change is projected to constitute a significant threat to food security, if no adaptation actions are taken 1,2 . Transformation of agricultural systems, e.g. switching crop types or moving out of agriculture, is projected to be necessary in some cases [3][4][5] .However, little attention has been paid to the timing of these transformations. Here, we develop a temporal uncertainty framework using the CMIP5 ensemble to assess when and where cultivation of key crops in Sub-Saharan African becomes unviable.We report potential transformational changes for all major crops during the 21 st century, as climates shift and areas become unsuitable. For most crops, however, transformation is limited to small pockets (<15 % of area), and only for beans, maize and banana is transformation more widespread (~30 % area for maize and banana, 60 % for beans). We envision three overlapping adaptation phases to enable projected transformational changes: an incremental adaptation phase focused on improvements to crops and management, a preparatory phase that establishes appropriate policies and enabling environments, and a transformational adaptation phase in which farmers substitute crops, explore alternative livelihoods strategies, or relocate. To best align policies with production triggers for no-regret actions, monitoring capacities to track farming systems as well as climate are needed.Agricultural activities are the main means to reduce poverty and improve food security among 850 million undernourished people 2 . Numerous studies have shown that climate change can be a significant threat to food availability and stability by reducing agricultural productivity and increasing inter-annual variations in yields 1,2,6 . Adaptation will be required if food production is to be increased in both quantity and stability in order to meet food security needs during the 21st century. A recent global meta-analysis 1 reported that decreases of ca. 5 % in crop productivity are expected for every degree of warming above historical levels, and that adapted crops yield roughly 7 % greater than non-adapted crops.Yield gains from adaptation through crop management and varietal substitution, however, are highest with moderate or low (< +3 ºC) levels of warming 1,6 , suggesting that more profound systemic and/or transformational changes may be required when and where higher levels of warming occur 5 .Transformational adaptation is defined by the IPCC 7 as a response to the effects of climate change that "changes the fundamental attributes of a system" (see Text S1 for definitions).Transformational change implies shifts in locations for production of specific crops and livestock, or shifting to farming systems new to a region or resource system 3,5 . Here, we consider one type of transformation: switching of staple crop type grown over a large geographic area of 0.3 million ha (the grid cell size of our analysis) or more. We analyze when and where major cropping systems transformations are likely to occur for important crops in Sub-Saharan A...

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Timescales of transformational climate change adaptation in sub-Saharan African agriculture

et al. 2016

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“…Given the diversity of entomological data sources and collection methods, it is not surprising that ecoinformatics data sets may be highly heterogeneous. Some ecoinformatics data sets may not reach the quality standards expected by researchers (29,47,77,124). Ecoinformatics data sets that combine multiple sources of data that use different sampling methods can create especially difficult problems (109).…”

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confidence: 99%

“…savings, and it is these cost savings that make it possible to assemble larger data sets (29,47,66,131). Although experimentation can, in principle, produce data sets of any size, large data sets are costly; for example, a rare experimental study that achieved levels of replication and spatial coverage that approached that seen in ecoinformatics studies was achieved with a budget of £6 million (≈US$8.8 million) (129).…”

Section: Size Of Data Setsmentioning

confidence: 99%

Ecoinformatics (Big Data) for Agricultural Entomology: Pitfalls, Progress, and Promise

Rosenheim

Gratton

2017

Annu. Rev. Entomol.

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Ecoinformatics, as defined in this review, is the use of preexisting data sets to address questions in ecology. We provide the first review of ecoinformatics methods in agricultural entomology. Ecoinformatics methods have been used to address the full range of questions studied by agricultural entomologists, enabled by the special opportunities associated with data sets, nearly all of which have been observational, that are larger and more diverse and that embrace larger spatial and temporal scales than most experimental studies do. We argue that ecoinformatics research methods and traditional, experimental research methods have strengths and weaknesses that are largely complementary. We address the important interpretational challenges associated with observational data sets, highlight common pitfalls, and propose some best practices for researchers using these methods. Ecoinformatics methods hold great promise as a vehicle for capitalizing on the explosion of data emanating from farmers, researchers, and the public, as novel sampling and sensing techniques are developed and digital data sharing becomes more widespread.

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“…Cock et al [10] presentan una metodología para determinar prácticas de gestión de cultivos mediante AP basadas en labores tradicionales. Los autores definen en su metodología la obtención de datos del cultivo que caracterizan las condiciones del mismo, la gestión y el análisis en bases de datos centralizadas y la facilidad en la accesibilidad de dicha información a los encargados del cultivo, para que tomen mejores decisiones relacionadas con el mismo.…”

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Sistemas de Información enfocados en tecnologías de agricultura de precisión y aplicables a la caña de azúcar, una revisión

Sarasti

Ramírez

2016

Rev. ing. univ. Medellín

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ResumenLos cultivos de caña de azúcar son una de las principales actividades económicas en Colombia; por ende, son esenciales para el desarrollo agrícola del país. Además, las tecnologías de la información y las comunicaciones (TIC) se han empezado a utilizar e implementar en todo el ciclo de vida del cultivo. Consecuentemente, las TIC son importantes al momento de definir sistemas basados en Agricultura de Precisión (AP), capaces de incrementar el rendimiento del cultivo y optimizar el uso de recursos económicos como fertilizantes, agua y pesticidas, entre otras funciones. Este artículo presenta una revisión acerca de sistemas de información basados en AP y aplicables a cultivos de caña de azúcar, haciendo énfasis en las tecnologías utilizadas, la gestión de datos y sus arquitecturas. Además, se presenta la propuesta de los autores: un sistema de información integral de tres capas basado en AP, capaz de facilitar la optimización en distintas etapas del ciclo de vida de la caña de azúcar. El artículo concluye describiendo el trabajo futuro y el desarrollo de la implementación del sistema propuesto.

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Crop management based on field observations: Case studies in sugarcane and coffee

Cited by 30 publications

References 24 publications

Timescales of transformational climate change adaptation in sub-Saharan African agriculture

Timescales of transformational climate change adaptation in sub-Saharan African agriculture

Ecoinformatics (Big Data) for Agricultural Entomology: Pitfalls, Progress, and Promise

Sistemas de Información enfocados en tecnologías de agricultura de precisión y aplicables a la caña de azúcar, una revisión

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