Pursuing the potential of heirloom cultivars to improve adaptation, nutritional and culinary features in a changing climate

Dwivedi, Sangam L.; Goldman, Irwin L.; Ortíz, Rodomiro

doi:10.20944/preprints201906.0022.v1

Cited by 14 publications

(1 citation statement)

References 48 publications

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“…Among these superior traits, delicious taste, fragrant and abiotic stress tolerance characteristic are the most desirable. They are gaining in popularity because of their unique flavors and cultural significance to local cuisine, and their role in sustainable food production for smallscale farmers (Dwivedi, et al, 2019). However, heirloom rice are now in a critical condition.…”

Section: Introductionmentioning

confidence: 99%

Population Characteristic and Genetic Relationship on 25 Bengkulu Heirloom Rice Based on Morpgological Traits

et al. 2019

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Bengkulu Province has many local rice germplasms that have adapted to specific areas. The germplasm has certain character advantages so that it is maintained by farmers. The characteristics of each germplasm need to be identified in order to improve the properties of the existing germplasm. This study aimed to determine the performance, to estimate the value of genetic parameters, and to determine the genetic relationship of local rice genotypes collected from four districts in Bengkulu Province. The results showed that the ‘Kuning Sulaowangi’ genotype was the earliest in maturity had the highest number of tillers amongst genotypes. Genotypes which have significantly the highest average component yields were ‘Kunig Air Dingin’ and ‘Impera’. Traits that have a high heritability estimated value were weight of 100 grains (91.046%) and grain weight per panicle (80.252%). The weight of 100 grains also has the highest genetic variability value. Thus increasing local rice production is possible. Based on the results of the analysis with the similarity coefficient of 55%, the local rice genotypes could be grouped into two groups. Group I consisted of 9 genotypes namely ‘Kuning Pendek’, ‘Humbur’, ‘Cantik’, ‘Pandak Kelabu’, ‘Cisadane Putih’, ‘Kuning Sulaowangi’, ‘China Abang’, ‘China Putih’ and ‘Impera’. Other genotypes were in Group II. Trait improvement can be done through hybridization between individuals of different groups. To develope early in maturity and high-yielding varieties can be done through hybridization of the ‘Kunig Sulaowangi’ and ‘Kunig Air Dingin’

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Section: Introductionmentioning

confidence: 99%

Population Characteristic and Genetic Relationship on 25 Bengkulu Heirloom Rice Based on Morpgological Traits

et al. 2019

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Prediction of Potato (Solanum tuberosum L.) Yield Based on Machine Learning Methods

Kurek,

Niedbała,

Wojciechowski

et al. 2023

Agriculture

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This research delves into the application of machine learning methods for predicting the yield of potato varieties used for French fries in Poland. By integrating a comprehensive dataset comprising agronomical, climatic, soil, and satellite-based vegetation data from 36 commercial potato fields over five growing seasons (2018–2022), we developed three distinct models: non-satellite, satellite, and hybrid. The non-satellite model, relying on 85 features, excludes vegetation indices, whereas the satellite model includes these indices within its 128 features. The hybrid model, combining all available features, encompasses a total of 165 features, presenting the most-comprehensive approach. Our findings revealed that the hybrid model, particularly when enhanced with SVM outlier detection, exhibited superior performance with the lowest Mean Absolute Percentage Error (MAPE) of 5.85%, underscoring the effectiveness of integrating diverse data sources into agricultural yield prediction. In contrast, the non-satellite and satellite models displayed higher MAPE values, indicating less accuracy compared to the hybrid model. Advanced data-processing techniques such as PCA and outlier detection methods (LOF and One-Class SVM) played a pivotal role in model performance, optimising feature selection and dataset refinement. The study concluded that machine learning methods, particularly when leveraging a multifaceted approach involving a wide array of data sources and advanced processing techniques, can significantly enhance the accuracy of agricultural yield predictions. These insights pave the way for more-efficient and -informed agricultural practices, emphasising the potential of machine learning in revolutionising yield prediction and crop management.

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The Trilogy of Wild Crops, Traditional Agronomic Practices, and UN-Sustainable Development Goals

et al. 2020

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The world population is projected to become 10 billion by the end of this century. This growing population exerts tremendous pressure on our finite food resources. Unfortunately, the lion-share of the global calorie intake is reliant upon a handful of plant species like rice, wheat, maize, soybean and potato. Therefore, it is the need of the hour to expand our dietary reliance to nutritionally rich but neglected, underutilized and yet-to-be-used wild plants. Many wild plants are also having ethnomedicinal and biocultural significance. Owing to their ecosystem plasticity, they are adapted to diverse habitats including marginal, degraded and other disturbed soil systems. Due to these resilient attributes, they can be considered for large-scale cultivation. However, proper biotechnological interventions are important for (i) removing the negative traits (e.g., low yield, slow growth, antinutritional factors, etc.), (ii) improving the positive traits (e.g., nutritional quality, stress tolerance, etc.), as well as (iii) standardizing the mass multiplication and cultivation strategies of such species for various agro-climatic regions. Besides, learning the biocultural knowledge and traditional cultivation practices employed by the local people is also crucial for their exploitation. The Special Issue “Wild Crop Relatives and Associated Biocultural and Traditional Agronomic Practices for Food and Nutritional Security” was intended to showcase the potential wild crop varieties of nutritional significance and associated biocultural knowledge from the diverse agroecological regions of the world and also to formulate suitable policy frameworks for food and nutritional security. The novel recommendations brought by this Special Issue would serve as a stepping stone for utilizing wild and neglected crops as a supplemental food. Nevertheless, long-term cultivation trials under various agro-climatic conditions are utmost important for unlocking the real potential of these species.

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Pursuing the potential of heirloom cultivars to improve adaptation, nutritional and culinary features in a changing climate

Cited by 14 publications

References 48 publications

Population Characteristic and Genetic Relationship on 25 Bengkulu Heirloom Rice Based on Morpgological Traits

Population Characteristic and Genetic Relationship on 25 Bengkulu Heirloom Rice Based on Morpgological Traits

Prediction of Potato (Solanum tuberosum L.) Yield Based on Machine Learning Methods

The Trilogy of Wild Crops, Traditional Agronomic Practices, and UN-Sustainable Development Goals

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