Global Food Security Support Analysis Data at Nominal 1 km (GFSAD1km) Derived from Remote Sensing in Support of Food Security in the Twenty-First Century: Current Achievements and Future Possibilities

2018 ◽  
pp. 865-894 ◽  
Keyword(s):  
Remote Sensing ◽  
Food Security ◽  
Analysis Data ◽  
First Century ◽  
Global Food Security ◽  
Twenty First Century ◽  
Global Food

Sustaining Global Food Security

2019 ◽  
Keyword(s):  
Remote Sensing ◽  
Food Security ◽  
Agricultural Policies ◽  
Crop Breeding ◽  
Sustainable Food ◽  
Global Food Security ◽  
International Policies ◽  
Policy Analysts ◽  
New Policies ◽  
Global Food

Population growth alone dictates that global food supplies must increase by over 50% in coming decades. Advances in technology offer an array of opportunities to meet this demand, but history shows that these can be fully realised only within an enabling policy environment. Sustaining Global Food Security makes a compelling case that recent technological breakthroughs can move the planet towards a secure and sustainable food supply only if new policies are designed that allow their full expression. Bob Zeigler has brought together a distinguished set of scientists and policy analysts to produce well-referenced chapters exploring international policies on genetic resources, molecular genetics, genetic engineering, crop breeding and protection, remote sensing, the changing landscape of agricultural policies in the world’s largest countries, and trade. Those entering the agricultural sciences and those who aspire to influence public policy during their careers will benefit from the insights of this unique set of experiences and perspectives.

scholarly journals Modeling Land Suitability for Rice Crop Using Remote Sensing and Soil Quality Indicators: The Case Study of the Nile Delta

2020 ◽  
Vol 12 (22) ◽  
pp. 9653
Author(s):  
Ahmed A. El Baroudy ◽  
Abdelraouf. M. Ali ◽  
Elsayed Said Mohamed ◽  
Farahat S. Moghanm ◽  
Mohamed S. Shokr ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Food Security ◽  
Soil Quality ◽  
Quality Indicators ◽  
Nile Delta ◽  
Point Of View ◽  
Soil Quality Indicators ◽  
Global Food Security ◽  
Increasing Demand ◽  
Global Food

Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments.

scholarly journals Accuracy Assessment of Global Food Security-Support Analysis Data (GFSAD) Cropland Extent Maps Produced at Three Different Spatial Resolutions

2018 ◽  
Vol 10 (11) ◽  
pp. 1800 ◽  
Author(s):  
Kamini Yadav ◽  
Russell G. Congalton
Keyword(s):  
Food Security ◽  
Accuracy Assessment ◽  
Simple Random Sampling ◽  
Analysis Data ◽  
Reference Dataset ◽  
Large Area ◽  
Global Food Security ◽  
Study Sites ◽  
Comparison Of The Results ◽  
Global Food

Monitoring global agriculture systems relies on accurate and timely cropland information acquired worldwide. Recently, the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program has produced Global Food Security-support Analysis Data (GFSAD) cropland extent maps at three different spatial resolutions, i.e., GFSAD1km, GFSAD250m, and GFSAD30m. An accuracy assessment and comparison of these three GFSAD cropland extent maps was performed to establish their quality and reliability for monitoring croplands both at global and regional scales. Large area (i.e., global) assessment of GFSAD cropland extent maps was performed by dividing the entire world into regions using a stratification approach and collecting a reference dataset using a simple random sampling design. All three global cropland extent maps were assessed using a total reference dataset of 28,733 samples. The assessment results showed an overall accuracy of 72.3%, 80–98%, and 91.7% for GFSAD1km, 250 m (only for four continents), and 30 m maps, respectively. Additionally, a regional comparison of the three GFSAD cropland extent maps was analyzed for nine randomly selected study sites of different agriculture field sizes (i.e., small, medium, and large). The similarity among the three GFSAD cropland extent maps in these nine study sites was represented using a similarity matrix approach and two landscape metrics (i.e., Proportion of Landscape (PLAND) and Per Patch Unit (PPU)), which categorized the crop proportion and the crop pattern. A comparison of the results showed the similarities and differences in the cropland areas and their spatial extent when mapped at the three spatial resolutions and considering the different agriculture field sizes. Finally, specific recommendations were suggested for when to apply each of the three different GFSAD cropland extent maps for agriculture monitoring based on these agriculture field sizes.

On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics

2018 ◽  
Vol 52 (1) ◽  
pp. 421-444 ◽  
Author(s):  
Jason G. Wallace ◽  
Eli Rodgers-Melnick ◽  
Edward S. Buckler
Keyword(s):  
Food Security ◽  
First Century ◽  
Global Food Security ◽  
The Road ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Line Breeding ◽  
On The Road ◽  
Quantitative Genomics ◽  
Global Food

Understanding the quantitative genetics of crops has been and will continue to be central to maintaining and improving global food security. We outline four stages that plant breeding either has already achieved or will probably soon achieve. Top-of-the-line breeding programs are currently in Breeding 3.0, where inexpensive, genome-wide data coupled with powerful algorithms allow us to start breeding on predicted instead of measured phenotypes. We focus on three major questions that must be answered to move from current Breeding 3.0 practices to Breeding 4.0: ( a) How do we adapt crops to better fit agricultural environments? ( b) What is the nature of the diversity upon which breeding can act? ( c) How do we deal with deleterious variants? Answering these questions and then translating them to actual gains for farmers will be a significant part of achieving global food security in the twenty-first century.

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