Search results for ' Maize'

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Call for proposals: Global Feed the Future Agricultural Biotechnology Program

Commodities that will receive prioritized consideration for BFS/ARP funding, including under this Addendum to the Agricultural Biotechnology APS, include:

Cereals (maize, rice, wheat, sorghum, millet)

Legumes (common bean, cowpea, peanut/groundnut, soya)

Roots, tubers, and bananas (potato, cassava, banana)

Horticulture crops (emphasis on horticultural species of broad global or regional relevance to smallholders)

Livestock (poultry, cattle, small ruminants, fish, dairy)

Concept notes must be submitted by the deadline of 17 January 2020.

Illustration Photo: Projects funded through the Feed the Future Innovation Lab for Collaborative Research on Sorghum and Millet, funded though USAID and established at Kansas State University, are aimed to help improve the adaptation and resilience of these crops in East and West Africa. (credits: K-State Research and Extension / Flickr Creative Commons Attribution 2.0 Generic (CC BY 2.0))

Check more https://adalidda.com/posts/r2TzAvwBG2Y6FoCAj/call-for-proposals-global-feed-the-future-agricultural

https://agfuse.com/article/how-cover-crops-affect-your-fertilizer-strategy

https://agfuse.com/article/how-cover-crops-affect-your-fertilizer-strategy

Low-Cost Three-Dimensional Modeling of Crop Plants

Authors: Jorge Martinez-Guanter, Ángela Ribeiro, Gerassimos G. Peteinatos, Manuel Pérez-Ruiz, Roland Gerhards, José María Bengochea-Guevara, Jannis Machleb and Dionisio Andújar

Journal Title: Sensors

ISSN: 1424-8220 (Online)

Publisher: MDPI AG

Plant modeling can provide a more detailed overview regarding the basis of plant development throughout the life cycle. Three-dimensional processing algorithms are rapidly expanding in plant phenotyping programmes and in decision-making for agronomic management. Several methods have already been tested, but for practical implementations the trade-off between equipment cost, computational resources needed and the fidelity and accuracy in the reconstruction of the end-details needs to be assessed and quantified. This study examined the suitability of two low-cost systems for plant reconstruction. A low-cost Structure from Motion (SfM) technique was used to create 3D models for plant crop reconstruction. In the second method, an acquisition and reconstruction algorithm using an RGB-Depth Kinect v2 sensor was tested following a similar image acquisition procedure. The information was processed to create a dense point cloud, which allowed the creation of a 3D-polygon mesh representing every scanned plant. The selected crop plants corresponded to three different crops (maize, sugar beet and sunflower) that have structural and biological differences. The parameters measured from the model were validated with ground truth data of plant height, leaf area index and plant dry biomass using regression methods. The results showed strong consistency with good correlations between the calculated values in the models and the ground truth information. Although, the values obtained were always accurately estimated, differences between the methods and among the crops were found. The SfM method showed a slightly better result with regard to the reconstruction the end-details and the accuracy of the height estimation. Although the use of the processing algorithm is relatively fast, the use of RGB-D information is faster during the creation of the 3D models. Thus, both methods demonstrated robust results and provided great potential for use in both for indoor and outdoor scenarios. Consequently, these low-cost systems for 3D modeling are suitable for several situations where there is a need for model generation and also provide a favourable time-cost relationship.

Figure: Examples from different perspectives of different crop models reconstructed using Kinect v2 (top) and photogrammetry (bottom) reconstruction methods. Credits: Jorge Martinez-Guanter, Ángela Ribeiro, Gerassimos G. Peteinatos, Manuel Pérez-Ruiz, Roland Gerhards, José María Bengochea-Guevara, Jannis Machleb and Dionisio Andújar

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European Space Agency #ESA Call for Kick-start Activities: #SpaceTechnologies enabled #Biodiversity Services #Agriculture #Fisheries #Aquaculture #Biofuel #TransportNetworks

Biological diversity is the variety of life found in any of, or across, Earth’s ecosystems. It is fundamental to life on Earth since it provides oxygen, food, clean water, fertile soil, medicines, shelter, protection from storms and floods, fibres for clothing, a stable climate and even recreation. It is estimated that the services provided by ecosystems are worth trillions of dollars, more than double the world’s GDP! Biodiversity loss in Europe alone costs the continent €450m a year or, 3% of its annual gross domestic product. However, the current state of biodiversity is ominous; overpopulation and overconsumption are driving a biodiversity crisis as people continue to expend resources in an unsustainable fashion. Space assets and satellite technologies, combined with advanced and innovative ways to use them, can make a crucial difference in the future of the biodiversity on Earth.

Dateline for submission: 25 October 2019

Illustration Photo: Deforestation for maize near Kirindy village, Madagascar (credits: USAID Biodiversity & Forestry / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

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Call for proposals: Grant to strengthen the supply of improved seeds and improved PPP in Central Africa

The overall goal of SISCA is to enhance reliable access of smallholder farmers to quality cassava planting material and maize seed of superior varieties at the right time and at an affordable price through piloting and expanding inclusive seed business models and seed partnerships in the target countries.

Through this call for proposals, IFAD will contribute by promoting access of smallholder farmers (female and male), in a sustainable way, to quality seeds through the expansion of a private sector-led seed sector. SISCA will contribute to IFAD’s updated strategy and enhance smallholder farmer productivity and income.

Dateline for submission: 18 September 2019

PPP: Public Private Partnership

Illustration Photo: Corn field in DR Congo (credits: MONUSCO / Jacques Miroza / Flickr Creative Commons Attribution-ShareAlike 2.0 Generic (CC BY-SA 2.0))

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Crop Monitoring Using Sentinel-1 Data: A Case Study from The Netherlands

Authors: Saeed Khabbazan, Paul Vermunt, Susan Steele-Dunne, Lexy Ratering Arntz, Caterina Marinetti, Dirk van der Valk, Lorenzo Iannini, Ramses Molijn, Kees Westerdijk and Corné van der Sande

Journal Title: Remote Sensing

ISSN: 2072-4292 (Print)

Publisher: MDPI AG

Agriculture is of huge economic significance in The Netherlands where the provision of real-time, reliable information on crop development is essential to support the transition towards precision agriculture. Optical imagery can provide invaluable insights into crop growth and development but is severely hampered by cloud cover. This case study in the Flevopolder illustrates the potential value of Sentinel-1 for monitoring five key crops in The Netherlands, namely sugar beet, potato, maize, wheat and English rye grass. Time series of radar backscatter from the European Space Agency’s Sentinel-1 Mission are analyzed and compared to ground measurements including phenological stage and height. Temporal variations in backscatter data reflect changes in water content and structure associated with phenological development. Emergence and closure dates are estimated from the backscatter time series and validated against a photo archive. Coherence data are compared to Normalized Difference Vegetation Index (NDVI) and ground data, illustrating that the sudden increase in coherence is a useful indicator of harvest. The results presented here demonstrate that Sentinel-1 data have significant potential value to monitor growth and development of key Dutch crops. Furthermore, the guaranteed availability of Sentinel-1 imagery in clouded conditions ensures the reliability of data to meet the monitoring needs of farmers, food producers and regulatory bodies.

Figure : Location of study area and map of crop types in Flevopolder. (credits: Saeed Khabbazan, Paul Vermunt, Susan Steele-Dunne, Lexy Ratering Arntz, Caterina Marinetti, Dirk van der Valk, Lorenzo Iannini, Ramses Molijn, Kees Westerdijk and Corné van der Sande)

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