Manure Phosphorus Management from a Global Perspective

While livestock manure is a significant global reserve of P, it is not always used efficiently in agricultural production. Due to the segregation of livestock and cropping systems in many countries, poor redistribution of manure P has led to regions with both surpluses and deficits. As phosphate rock must be considered a finite source, the recycling of P from manures regionally, nationally, and even globally needs to be improved for food security in the future.

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Future outlook on microbial bioprotectants in agriculture

10.19103/as.2021.0093.21 ◽

2021 ◽

pp. 669-690

Author(s):

Willem J. Ravensberg ◽

Keyword(s):

Food Security ◽

Plant Growth ◽

New Technologies ◽

Cropping Systems ◽

Crop Protection ◽

Microbial Interactions ◽

Plant Diseases ◽

Future Outlook ◽

Regulatory Issues ◽

The Future

Microbial bioprotectants have the potential to play a major role in the future of crop protection. Agriculture needs to become more sustainable and still provide food security within planetary borders. New technologies and scientific discoveries can unravel the interactions between the plant, the microbiome and the soil and provide new opportunities for crop protection and more resilient cropping systems. Regulatory issues delay and hamper exploitation and research of genetic resources. This chapter describes the factors that promote the use of microbial bioprotectants as well as those that hamper their further adoption. A sustainable and resilient agriculture depends on the microbial interactions between plants in promoting plant growth and combatting biotic and abiotic threats. The transition to a resilient agriculture requires big changes in policy, regulation and farming practices. This chapter assesses the future outlook for the methods for controlling plant diseases described in this book as well as the factors determining their uptake and success.

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Prediction of Food Production Using Machin Learning Algorithms of Multilayer Perceptron and ANFIS

10.20944/preprints202104.0628.v1 ◽

2021 ◽

Author(s):

Saeed Nosratabadi ◽

Sina Ardabili ◽

Zoltan Lakner ◽

Csaba Mako ◽

Amir Mosavi

Keyword(s):

Food Security ◽

Multilayer Perceptron ◽

Agricultural Production ◽

Food Production ◽

Livestock Production ◽

Series Data ◽

Accurate Estimation ◽

Inference System ◽

The Future ◽

Future Of Food

Advancing models for accurate estimation of food production is essential for policymaking and managing national plans of action for food security. This research proposes two machine learning models for the prediction of food production. The adaptive network-based fuzzy inference system (ANFIS) and multilayer perceptron (MLP) methods are used to advance the prediction models. In the present study, two variables of livestock production and agricultural production were considered as the source of food production. Three variables were used to evaluate livestock production, namely livestock yield, live animals, and animal slaughtered, and two variables were used to assess agricultural production, namely agricultural production yields and losses. Iran was selected as the case study of the current study. Therefore, time-series data related to livestock and agricultural productions in Iran from 1961 to 2017 have been collected from the FAOSTAT database. First, 70% of this data was used to train ANFIS and MLP, and the remaining 30% of the data was used to test the models. The results disclosed that the ANFIS model with Generalized bell-shaped (Gbell) built-in membership functions has the lowest error level in predicting food production. The findings of this study provide a suitable tool for policymakers who can use this model and predict the future of food production to provide a proper plan for the future of food security and food supply for the next generations.

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Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS

10.21203/rs.3.rs-477719/v1 ◽

2021 ◽

Author(s):

Saeed Nosratabadi ◽

Sina Ardabili ◽

Zoltan Lakner ◽

Csaba Mako ◽

Amir Mosavi

Keyword(s):

Machine Learning ◽

Food Security ◽

Multilayer Perceptron ◽

Agricultural Production ◽

Food Production ◽

Livestock Production ◽

Series Data ◽

Accurate Estimation ◽

The Future ◽

Future Of Food

Abstract Advancing models for accurate estimation of food production is essential for policymaking and managing national plans of action for food security. This research proposes two machine learning models for the prediction of food production. The adaptive network-based fuzzy inference system (ANFIS) and multilayer perceptron (MLP) methods are used to advance the prediction models. In the present study, two variables of livestock production and agricultural production were considered as the source of food production. Three variables were used to evaluate livestock production, namely livestock yield, live animals, and animal slaughtered, and two variables were used to assess agricultural production, namely agricultural production yields and losses. Iran was selected as the case study of the current study. Therefore, time-series data related to livestock and agricultural productions in Iran from 1961 to 2017 have been collected from the FAOSTAT database. First, 70% of this data was used to train ANFIS and MLP, and the remaining 30% of the data was used to test the models. The results disclosed that the ANFIS model with Generalized bell-shaped (Gbell) built-in membership functions has the lowest error level in predicting food production. The findings of this study provide a suitable tool for policymakers who can use this model and predict the future of food production to provide a proper plan for the future of food security and food supply for the next generations.

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Agricultural production in Greater Sekhukhune: the future for food security in a poverty node of South Africa?

Agrekon ◽

10.1080/03031853.2009.9523826 ◽

2009 ◽

Vol 48 (3) ◽

pp. 245-275 ◽

Cited By ~ 5

Author(s):

S Drimie ◽

T Germishuyse ◽

L Rademeyer ◽

C Schwabe

Keyword(s):

South Africa ◽

Food Security ◽

Agricultural Production ◽

The Future

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Paradigma Pendidikan Islam dan Keprofesionalan Guru dalam Menjawab Tantangan Global

INSANIA Jurnal Pemikiran Alternatif Kependidikan ◽

10.24090/insania.v14i1.315 ◽

1970 ◽

Vol 14 (1) ◽

pp. 3-18

Author(s):

Mahsun Mahfud

Keyword(s):

Middle Age ◽

Global Perspective ◽

Islamic Education ◽

Teacher Professionalism ◽

The Future ◽

Mutual Agreement

Islamic education must be directed from paradigm that past oriented (middle age) to the future. Not just preserve advancement, but also pioneering progress. Feudal paradigm must been replaced by Islam education paradigm that innovative and democratic. Therefore, we need harmonious planning and mutual agreement, that Islamic education must oriented to student, have multicultural character, and global perspective. Education has to become liberation process, not social and cultural domestication. One important aspect is to manifesting teacher professionalism that identified from competence aspect, responsibility, honesty, discipline, and high dedication to guard student to their successfulness.

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The Poverty Resolution as Peacelessness and the Future of Food Security : Competing for Marine Genetic Resources and Countermeasures

Peace and Religions ◽

10.25168/kaprs.2017.3.61 ◽

2017 ◽

Vol 3 ◽

pp. 61-83

Author(s):

Woochoel Joo ◽

◽

Kyungmin Ko

Keyword(s):

Food Security ◽

Genetic Resources ◽

The Future ◽

Future Of Food

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THE IMPACT OF STATE REGULATION OF AGRICULTURAL PRODUCTION ON FOOD SECURITY IN RUSSIA

Economy, labor, management in agriculture ◽

10.33938/188-49 ◽

2018 ◽

pp. 49-54

Author(s):

Vladimir Ivanovich Hajduk ◽

S.A. Kalitko ◽

Y.A. Nikiforova ◽

M.G. Paremuzova

Keyword(s):

Food Security ◽

Agricultural Production ◽

State Regulation ◽

The Impact

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Mechanisms of Green Development of Urban Agricultural Production in a Large Industrial City

Economics and Management ◽

10.35854/1998-1627-2020-8-823-829 ◽

2020 ◽

Vol 26 (8) ◽

pp. 823-829

Author(s):

E. V. Malysh

Keyword(s):

Food Security ◽

Urban Agriculture ◽

Food Supply ◽

Agricultural Production ◽

High Tech ◽

Agricultural Technologies ◽

Short Supply ◽

Industrial City ◽

Self Sufficiency ◽

Green Development

A city’s potential for food self-sufficiency is expected to increase through the distribution of innovative, high-tech, green agricultural practices of producing food in an urban environment, which can improve the city’s food security due to increased food accessibility in terms of quantity and quality. Aim. Based on the systematization of theoretical approaches and analysis of institutional aspects, the study aims to propose ways to strengthen the city’s food security by improving food supply in urban areas, increasing the socio-economic and environmental sustainability of urban food systems, and changing the diet of urban residents.Tasks. The authors propose methods for the development of urban agricultural production in a large industrial city based on the principles of green economy and outline the range of strategic urban activities aimed at implementing green agricultural production technologies associated with the formation and development of the culture of modern urban agricultural production.Methods. This study uses general scientific methods of cognition to examine the specificity of objectives of strengthening a city’s food security by improving the quality of food supply to the population. Methods of comparison, systems analysis, systematization of information, and the monographic method are also applied.Results. A strategic project for the development of urban agricultural systems through the implementation and green development of advanced urban agricultural technologies is described. Green development mechanisms will create conditions for the city’s self-sufficiency in terms of organic and safe products, functioning of short supply chains, and green urban agriculture.Conclusions. Managing the growth of urban agriculture will promote the use of highly effective, easily controlled, resource-efficient, eco-friendly, weather- and season-independent, multi-format urban agricultural technologies. The study describes actions aimed at creating conditions for stabilizing a city’s high-quality food self-sufficiency with allowance for the growing differentiation of citizen needs.

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