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Embracing smart irrigation management techniques empowers growers to irrigate with greater efficiency, thereby promoting sustainable agricultural production. In this context, growers often rely on crop evapotranspiration (ETc) as a key factor in making informed irrigation decisions, underscoring the significance of accurately determining and spatially mapping crop water status. Technological progress, exemplified by the emergence of unmanned aerial vehicles (UAVs), has brought about a revolutionary shift in agricultural monitoring. UAV platforms can capture high-resolution images with centimeter-level spatial accuracy and offer higher temporal coverage compared to satellite imagery. Considering these advancements, this study introduces a robust method for classifying water stress in cotton using a compact UAV platform and convolutional neural networks (CNN). The experiment was conducted at the USDA-ARS Cropping Systems Research Laboratory (CSRL) in Lubbock, Texas, where the cotton field was divided into 12 drip zones. The study included three replications to evaluate four irrigation treatments: “rainfed”, “full irrigation”, “percent deficit of full irrigation”, and “time delay of full irrigation”. The results demonstrated that the CNN model successfully classified the cotton water stress using the UAV-based RGB image, achieving an overall best prediction accuracy of approximately 91%. By segmenting the original cotton images into separate canopy and soil areas using morphological image processing methods, the authors also isolated and analyzed the individual contributions of these components to cotton water stress. Additionally, a random forest classifier revealed the relative importance of different image features in the classification process through feature importance analysis. These findings highlighted the state-of-the-art performance of the proposed system in cotton water stress classification and provided valuable insights into the key image features contributing to accurate classification. The authors concluded that integrating UAV-based RGB imagery and CNN models had great potential for assessing water stress in cotton.

A new approach to measure spatial variability of soil parameters and field technique to test-value specific fertilizer

Information on the distribution of soil properties is important to know the status of nutrients in the soils based on which fertilizer nutrients are recommended. Given the variability of nutrients in the soils, making a site-specific fertilizer recommendation seems to be a compelling work. To determine the spatial variability of soil nutrients and to make judicious and precise fertilizer recommendations, new measures are designed with this study. These measures are tested against the soil samples (n = 43) for total nitrogen (N), organic matter (OM), phosphorus (P2O5), and potassium (K2O) in the study area. The descriptive statistical analysis indicated an average of low nitrogen and organic matter, while phosphorus was found to be very high and the level of potassium was high. The spread of nutrients across the data sets, however, included low, medium, high, and very high levels of ratings. The Deviation Square Index was developed and applied for the variability measurement and found that the largest variation was with phosphorus distribution, followed by potassium, nitrogen, and organic matter. The coefficient of variation (CV%) analysis also exhibited similar trends in nutrient distributions. Nitrogen was the main determinant explaining the variations in rice yield, while phosphorus and potash were negatively related to the yield. An index of fertilizer nutrient recommendation called Test-Value Specific Dose (TVSD) was developed and used to calculate the nutrient recommendation for each sampled location. This new method gave easy and more accurate doses of fertilizer over the blanket recommendation to fit the variations across the soil samples.

Family agriculture for inclusive rural development

Laksmi Reddiar Krishnamurthy, Sumithra Krishnamurthy, Indumathi Rajagopal, Arturo Peralta Solare

Article ID: 2082
Vol 2, Issue 2, 2021

DOI: https://doi.org/10.54517/ama.v2i2.2082
VIEWS - 381 (Abstract)

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Abstract

The indigenous Mayan populations of the Yucatan Peninsula of Mexico have practiced the ancient traditions of family farming, especially home gardens, to ensure their food security. With the objective of improving traditional practice with modern science, data were collected on the structural complexity and functional diversity of 20 home gardens selected at random in each of the following five communities: X-Maben, X-Pichil, X-Yatil, San José II, and Melchor Ocampo. In addition, group discussions were organized to elucidate the management strategy practiced by the indigenous people. The results show that home gardens are managed mainly by women. The main purpose of growing and maintaining home gardens is to guarantee the production of nutritious food year round. Finally, the home gardens also serve secondary purposes, such as the provision of products and services for traditional medicine. This study suggests that home gardens should be promoted and invested in to improve inclusive development strategies for contexts with similar socio-cultural and biophysical circumstances.

Keywords

food security; home gardens; species diversity; sustainable development

References

1. Eyzaguirre PB, Linares OF. Home Gardens and Agrobiodiversity. Smithsonian Institution Press; 2004.

2. Galhena DH, Freed R, Maredia KM. Home gardens: A promising approach to enhance household food security and wellbeing. Agriculture & Food Security 2013; 2: 8. doi: 10.1186/2048-7010-2-8

3. Torquebiau E. Are tropical agroforestry home gardens sustainable? Agriculture, Ecosystems & Environment 1992; 41(2): 189–207. doi: 10.1016/0167-8809(92)90109-O

4. Méndez VE, Lok R, Somarriba E. Interdisciplinary analysis of homegardens in Nicaragua: Micro-zonation, plant use and socioeconomic importance. Agroforestry Systems 2001; 51: 85–96. doi: 10.1023/A:1010622430223

5. Kumar BM, Nair PKR. The enigma of tropical homegardens. In: New Vistas in Agroforestry. Springer Netherlands; 2004. pp. 135–152. doi: 10.1007/978-94-017-2424-1_10

6. Weersum KF. Tree gardening and taungya on Java: Examples of agroforestry techniques in the humid tropics. Agroforestry Systems 1982; 1(1): 53–70. doi: 10.1007/bf00044329

7. Brownrigg LA. Home Gardening in International Development: What the Literature Shows, Including an Anannotated Bibliography, and Inventories of International Organizations Involved in Home Gardening and Their Projects. League for International Food Education; 1985.

8. Fernandes ECM, Nair PKR. An evaluation of the structure and function of tropical homegardens. Agricultural Systems 1986; 21(4): 279–310. doi: 10.1016/0308-521X(86)90104-6

9. Soemarwoto O. Homegardens: A traditional agroforestry system with a promising future. In: Steppler HA, Nair PKR (editors). Agroforestry: A Decade of Development. ICRAF; 1987. pp. 157–170.

10. Caballero J. Maya homegardens: Past, present and future. Etnoecológica 1992; 1(1): 35–54.

11. UNDP. Inclusive development (Spanish). Available online: https://www.undp.org/es/el-salvador/desarrollo-inclusivo (accessed on 28 October, 2016).

12. Arias L. The current Mayan-Yucatec family or solar garden (Spanish). In: Mariaca Méndez R (editor). The Family Garden of the Mexican Southeast (Spanish). ECOSUR; 2012. pp. 111–130.

13. Flores Guido JS. Floristic diversity, uses and origin of genetic material of species from home gardens of the Yucatan Peninsula (Spanish). In: Mariaca Méndez R (editor). The Family Garden of the Mexican Southeast (Spanish). ECOSUR; 2012. pp. 149–175.

14. Mariaca Méndez R. The Family Garden of the Mexican Southeast (Spanish). ECOSUR; 2012.

15. Montagnini F. Homegardens of Mesoamerica: Biodiversity, food security, and nutrient management. In: Tropical Homegardens: A Time-Tested Example of Sustainable Agroforestry. Springer Netherlands; 2006. pp. 61–84. doi: 10.1007/978-1-4020-4948-4_5

16. Cahuich-Campos D. The Mayan garden and the daily diet of the peasant families of X-Mejía, Hopelchén, Campeche. In: Mariaca Méndez R (editor). The Family Garden of the Mexican Southeast (Spanish). ECOSUR; 2012. pp. 197–229.

17. Mohan S, Alavalapati JRR, Nair PKR. Financial analysis of homegardens: A case study from Kerala state, India (Spanish). In: Tropical Homegardens: A Time-Tested Example of Sustainable Agroforestry. Springer Netherlands; 2006. pp. 283–296. doi: 10.1007/978-1-4020-4948-4_16

18. Cámara-Córdova J. Contribution of the family garden to the rural economy, adaptation to climate change and productive conversion in Tabasco, Mexico (Spanish). In: Mariaca Méndez R (editor). The Family Garden of the Mexican Southeast (Spanish). ECOSUR; 2012. pp. 372–390.

19. Torquebiau E, Penot E. Ecology versus economics in tropical multistrata agroforests. In: Tropical Homegardens: A Time-Tested Example of Sustainable Agroforestry. Springer Netherlands; 2006. pp. 269–282. doi: 10.1007/978-1-4020-4948-4_15

20. Food and Agriculture Organization (FAO). World food summit. Available online: https://www.fao.org/3/w3548e/w3548e00.htm (accessed on 8 August 2015).

21. Vía Campesina. World food summit. Available online: https://viacampesina.org/en/index.php/organisation-mainmenu-44 (accessed on 18 September 2016).

22. United Nations. Millennium development goals and beyond 2015. Available online: http://www.un.org/millenniumgoals/poverty.shtml (accessed on 25 August 2015).

23. Food and Agriculture Organization (FAO). State of Food and Agriculture. Food System for Better Nutrition. FAO; 2013.

24. National Council for Evaluation of Social Development Policy (CONEVAL). Poverty Report in Mexico, 2012. CONEVAL; 2013.

25. Angel-Pérez AL. Homegardens and the dynamics of Totonac domestic groups in Veracruz, Mexico. Anthropological Notebooks 2013; 19: 5–22.

26. United Nations Environment Programme (UNEP). Consideration of initial elements: Recognizing indigenous and local knowledge and building synergies with science. Available online: http://www.ipbes.net/plenary/ipbes-1.html (accessed on 4 December 2015).

27. Rebollar-Domínguez S, Santos-Jiménez VJ, Tapia-Torres NA, et al. Family gardens, an experience in Chancah Veracruz, Quintana Roo (Spanish). Polibotánica 2008; 25: 135–154.

28. DBCity. Felipe Carrillo Puerto. Available online: http://es.db-city.com/M%C3%A9xico-Quintana-Roo-Felipe-Carrillo-Puerto (accessed on 18 September 2016).

29. Bautista F, Palma-López D, Huchin-Malta W. Update of the soil classification of the state of Yucatán (Spanish). In: Bautista F, Palacio G (editors). Characterization and Management of Soils in the Yucatan Peninsula: Agricultural, Forestry and Environmental Implications (Spanish). National Institute of Ecology; 2005. pp. 105–122.

30. National Institute of Statistics and Geography (INEGI). Available online: http://sipse.com/novedades/quintana-roopoblacion-indigena-encuesta-intercensal-2015-inegi-lenguamaya-184159.html (accessed on 18 September 2016).

31. National Institute of Statistics and Geography (INEGI). Available online: http://www.cuentame.inegi.org.mx/monograf ias/informacion/qroo/poblacion/diversidad.aspx?tema=me&e=23 (accessed on 18 September 2016).

32. Tageo. Melchor Ocampo, Quintana Roo. Available online: http://www.tageo.com/index-e-mx-v-23-d-m2398966.htm (accessed on 28 October 2016).

33. Tageo. X-Pichil, Quintana Roo. Available online: http://www.tageo.com/index-e-mx-v-23-d-m2399119.htm (accessed on 28 October 2016).

34. Dices. Melchor Ocampo, Quintana Roo, Felipe Carrillo Puerto, Chetumal. Available online: http://www.dices.net/mapas/mexico/mapa.php?nombre=Melchor-Ocampo&id=110414 (accessed on 29 October 2016).

35. Kitzinger J. Qualitative research. Introducing focus groups. BMJ 1995; 311: 299–302. doi: 10.1136/bmj.311.7000.299

36. Raymond CM, Fazey I, Reed MS, et al. Integrating local and scientific knowledge for environmental management. Journal of Environmental Management 2010; 91(8): 1766–1777. doi: 10.1016/j.jenvman.2010.03.023

37. Convention of Biological Diversity (CBD). The Tkarihwaié: RI code of Ethical Conduct to Ensure Respect for the Cultural and Intellectual Heritage of Indigenous and Local Communities Relevant to the Conservation and Sustainable Use of Biological Diversity. CBD; 2011.

38. De Clerck FAJ, Negreros-Castillo P. Plant species of traditional Mayan homegardens of Mexico as analogs for multistrata agroforests. Agroforestry Systems 2000; 48: 303–317. doi: 10.1023/A:1006322612362

39. Toledo VM. Indigenous peoples, strategic actors for the Mesoamerican Biological Corridor (Spanish). Biodiversitas 2003; 47: 8–15.

40. Millennium Ecosystem Assessment (MEA). Ecosystems and Human Well-Being: Synthesis. Island Press; 2005.

41. Lope-Alzina DG, Howard PL. The structure, composition, and functions of homegardens: Focus on the Yucatán Peninsula. Revista Etnoecologica 2012; 9(1): 17–41.

42. Leclerc C, Thuillet AC. Wild and cultivated biodiversity and natural resource management. Montpellier, France. Agrop. Int 2014; 19: 35–47.

43. Gupta J, Vegelin C. Sustainable development goals and inclusive development. International Environmental Agreements: Politics, Law and Economics 2016; 16: 433–448.

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Zhejiang University, China

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