The role of millets in attaining United Nation's sustainable developmental goals

Ceasar, Stanislaus Antony; Maharajan, Theivanayagam

doi:10.1002/ppp3.10254

Cited by 35 publications

(19 citation statements)

References 32 publications

(43 reference statements)

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“…This richness of millets in terms of micronutrients helps not only in ensuring good health at individual level but also promoting well‐being at community level. It is a short duration crop with minimal use of resources (Antony Ceasar & Maharajan, 2022) and has inherent ability to adapt to harsh climate as it is a hardiest and resilient crop. Millets production and consumption also help address the most important goal SDG 13 Climate Action as they have low‐water footprint (J. K. Ladha et al., 2020; UN General, 2015) and low emission zero carbon footprint.…”

Section: Introductionmentioning

confidence: 99%

Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning

Thulasiraman,

Haldar,

Kumar

et al. 2024

Earth and Space Science

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The potential of single date fully Polarimetric RADARSAT‐2 data in retrieving crop biophysical parameters using Machine Learning techniques was investigated. Various polarimetric parameters along with coherent and incoherent decomposition techniques were assessed for its sensitivity toward crop parameters like Wet and Dry Biomass, Crop Height, Leaf Area Index and Vegetation Water Content. A set of 39 polarimetric observables extracted from the Quad‐Pol data were used for regression analysis. In this study two Machine Learning techniques Random Forest Regression (RFR) and Multiple Linear Regression (MLR) models were assessed for the prediction of Wet Biomass (gm−2) and Height (cm). The most significant (6 out of 39) variables were applied for prediction. The results revealed that RFR algorithm performed better than MLR. The coefficient of determination (R2) and root‐mean‐square‐error of estimating wet biomass and height were 0.646, 655.65 (gm−2) and 0.71, 14.5 (cm) respectively in RFR and 0.566, 683.86 (gm−2) and 0.65, 16.14 (cm) respectively in MLR. Thus this study explored the effective application of quad‐pol data for assessing sensitivity and accurate retrieval of parameters using optimum PolSAR observables.

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Section: Introductionmentioning

confidence: 99%

Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning

Thulasiraman,

Haldar,

Kumar

et al. 2024

Earth and Space Science

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Section: Introductionmentioning

confidence: 99%

“…Finger millet (Eleusine coracana L. Gaertn) is an essential cereal in arid and semiarid regions of the world due to its resistance to pests, diseases, and drought [1][2][3]. It is also considered an important cereal for future human survival due to increasing and decreasing water supplies globally [1]. Finger millet is commonly cultivated in African and Asian countries for poor people's consumption; therefore, it is considered a poor man's crop [2,3].…”

Section: Introductionmentioning

confidence: 99%

Identification of QTL Associated with Agro-Morphological and Phosphorus Content Traits in Finger Millet under Differential Phosphorus Supply via Linkage Mapping

et al. 2023

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Finger millet (Eleusine coracana (L.) Gaertn.) is one of the most important cereal crops for people in Asia and Africa. It supplies energy and nutrients for all people, particularly poor people in these continents. Phosphorus (P) is an essential macronutrient for plant growth and grain quality, so an adequate amount of P is required for healthy plant life. There is considerable evidence that P deficiency affects the growths and yields of all cereals, including finger millet. The present study aimed at identifying the quantitative trait loci (QTL) for various agro-morphological and P-content traits under low P (LP) and high P (HP) conditions through linkage mapping. Two cultivars, IE-2606 (low-P-susceptible) and PR-202 (low-P-tolerant) were used to develop 100 recombinant inbred lines (RILs). In total, 55 QTL, associated with various agro-morphological (primary root length (PRL), shoot fresh weight (SFW), root fresh weight (RFW), shoot dry weight (SDW), root dry weight (RDW), and root hair density (RHD)) and P-content traits (inorganic phosphate content in shoots (PiS), inorganic phosphate content in roots (PiR), and total P content in shoots (TPS)) were detected under LP conditions. Similarly, 37 QTL for various agro-morphological (PRL, RFW, SDW, and root hair length (RHL)) and P-content traits (PiS, PiR, TPS, and total P content in roots (TPR)) were detected under HP conditions. Biotic and abiotic stress-responsive candidate genes linked to a few QTL were also identified. The identified QTL associated with agro-morphological and P-content traits in finger millet under P deficiency could be used in breeding programs to develop finger millet with better P use efficiency (PUE). Furthermore, improving finger millet growth and yield under LP soil will help to reduce Pi application and eutrophication, which may help to improve the lives of poor farmers and maintain sustainable environments in Asia and African countries.

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“…India is the world's largest producer and leader in production of millets with 15% share of the world total production accompanied by Niger, China, Nigeria, Mali, Sudan, Ethiopia, and Senegal (Karki et al, 2020). As per the reports of Food and Agriculture Organisation (Food and Agriculture Organisation (FAO, 2022), UNGA (UN General Assembly) has adopted the Government of India's plan for declaring and dedicating "2023" as the International year of Millets for encouraging the millet cultivation which could help to achieve the United Nations Sustainable Development Goal two (SDG2) for attaining zero hunger, food security, improved nutrition, and promoting sustainable agriculture (Ceasar & Maharajan, 2022). A number of millet varieties are prevalent since ages such as sorghum (Jowar), foxtail millet (Kakum), kodo millet (Kodon), pearl millet (Bajra), finger millet (Ragi), proso millet (Chena), small millet (Kutki), barnyard millet (Sanwa), and brown top millet (Gopalan et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Nutritional exploration of foxtail millet (Setaria italica) in addressing food security and its utilization trends in food system

Kalsi,

Bhasin

2023

eFood

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Millets are recognized as nutritional grains that have been important for preventing the malnutrition and significantly enhancing the human health. Foxtail millet (Setaria italica) is a C4, self pollinating millet species belonging to family Poaceae; acknowledged as Italian millet, Chinese millet or German millet. Being the oldest crops to be cultivated and produced, it is also utilized as a bird feed in African regions of the world. As far as the nutritional content is concerned, it has substantial amounts of carbohydrates (60–65 g), protein (12.3 g), fiber (6 g), minerals (Phosphorous, calcium, iron, zinc, magnesium, sodium), and phytochemicals (Phenols, Ferulic, chlorogenic acids, and p‐coumaric, flavonoids, carotenoids, tocopherol, and tocotrienol). Additionally foxtail millet is reported to have anti inflammatory, antioxidant, anticancerous, antihypolipidemic antihyperglycemic properties that may serve well with respect to pharmacological relevance. Apart from the medicinal prospect, its food utilization for making bakery, weaning, fermented as well as extruded goods are studied in the literature. Thus it can be mentioned that foxtail millet has a promising position in strengthening dietary quality and food security of world, thereby functioning as an emissary crop to replenish other economically valuable crops against environmental constraints even while supplying food for people and livestock via biotechnological techniques.

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The role of millets in attaining United Nation's sustainable developmental goals

Cited by 35 publications

References 32 publications

Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning

Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning

Identification of QTL Associated with Agro-Morphological and Phosphorus Content Traits in Finger Millet under Differential Phosphorus Supply via Linkage Mapping

Nutritional exploration of foxtail millet (Setaria italica) in addressing food security and its utilization trends in food system

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