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Rising Kashmir > Blog > Viewpoint > Providing Food for All by 2050: Outside and inside box strategies – II
Viewpoint

Providing Food for All by 2050: Outside and inside box strategies – II

DR. MUSHTAQ AHMAD
Last updated: January 10, 2023 10:12 pm
DR. MUSHTAQ AHMAD
Published: January 10, 2023
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Outside box strategies

If we want to survive, we must shift our attention from rice and wheat to other alternative crops that are nutritious, short-lived, and most importantly, climate adaptable. If neglected crops like oat, buckwheat, quinoa, and finger millet were put under cultivation, they could feed people by 2050 while also preserving the environment because they are typically disease-resistant and environmentally friendly. This is especially true of our Kashmir valley. We have a significant difficulty in the Kashmir valley’s wheat and rice crop rotation if we plant oats for human consumption and cultivate this crop in the rabi season while also making it suitable for rice rotation.

 

Oat for human consumption was recently designated a future food by the WHO due to its extremely valuable nutrients and soluble fibre. The whole grain oat (Avena Sativa L.) is the best alternative for treating the majority of common health problems, including celiac disease, diabetes, high blood pressure, obesity, colon cancer, weight reduction, and high cholesterol. It is also a gluten-free food. Its growing in the valley benefits the farmers’ livelihoods as well as their health. Oat cultivation is very simple, requires little resources, is easy to maintain, and is an environmentally beneficial crop because it uses very little water, fertilizers, fungicides and pesticides.

 

The most crucial aspect of the oat crop is that its commercial cultivation is very suitable for Kashmir Valley’s temperate climate and has a high demand worldwide. India imported oat for human consumption from 23 nations, primarily from Australia, Canada, and Chile, with a total value of $40 billion. What’s more, the demand for oat for human consumption in India is growing by 23% annually.

 

Its cultivation in the valley is advantageous to the farmers’ livelihoods and physical well-being. Under the direction of the honorable VC, SKUAST Kashmir is continuously focusing on new ideas and challenges to help the valley reach its objective of becoming entirely self-sufficient (SKUAST-Kashmir). These innovative concepts and ideas were conceptualized by Professor Nazir Ahmad Gania, who has continuously shown unwavering confidence and full support. On that vision and to improve the livelihood of both marginal and small farmers, SKUAST-Kashmir is very nearer to release (One oat variety) for human consumption, the first of its kind to be grown in our country, is planned for cultivation in the valley, helping farmers’ economies not only in Kashmir but also in some other regions of the nation. Same is the case for other underutilized crops. These crops have an ability that will give us future food security which is a burning issue around the world. In order to feed the alarmingly rising population not by 2050 but for more than a decade, we must at least partially adopt the remedies outlined below if we continue to use the new crops as our principal food crops.

 

Modernizing Plant Breeding

Machine Learning /Artificial Intelligence and Speed Breeding:

Plant breeding has always been crucial for modernizing agriculture to feed the world’s constantly expanding population, but now is the moment to change the innovations and problems we focus on when there isn’t enough food to sustain the world’s alarmingly growing population. Genomic analysis can be combined with advanced breeding techniques to address difficulties with food productivity, quality, and production stability. Our knowledge of crop diversity at the species and gene levels, as well as DNA markers for genetic variation, has increased as a result of advances in plant genomics. We must have improved these most recent breeding procedures with unique, unconventional techniques like speed breeding, machine learning, and artificial intelligence. These techniques may abbreviate the breeding cycle, allowing us to develop cereals over four generations in a single year, or they may change a crop’s genetic makeup so that it produces two or three panicles rather than one.

 

Machine learning, which is still in its infancy, mostly uses artificial intelligence, which may be characterized as cutting-edge computer-based systems that let the machine to learn automatically and enhance its potential without being rigidly computed. Crop breeding cycles are accelerated through genomic selection, which also permits speedy screening of superior germ plasm. The recovery of massive genotyping data sets linked to agronomically important phenotypic variables and improvements in machine learning methods are now the two main requirements for genomic selection. The major objective of machine learning (ML) is to categorize or accurately describe new experiences by quickly leveraging existing experiences to identify fundamental patterns, resemblances, and differences in data.

 

Machine learning-based methods can manage large data sets with high levels of noise, dimensionality, and/or incompleteness. Machine learning interprets the techniques that computers use to complete tasks by learning from data rather than by strictly adhering to explicit instructions. Semi-supervised learning, unsupervised learning, and supervised learning are the three main approaches. In supervised learning, which is the most common type of machine learning, each example in the data set is given a certain category. The most fascinating technology, known as speed breeding, has captured the attention of the entire globe. NASA provided the motivation for a University of Queensland researcher to grow wheat seedlings in orbit.

 

Speed breeding is an effective method for expediting crop improvement breeding programmes and cutting the time it takes to produce crops. Rapid gene identification, crossing, population mapping, backcrossing, and trait pyramiding may all be completed more quickly. To reduce the generational interval in various crops, techniques including in vitro/embryo culture, double haploid technology, and off-season nurseries and shuttle breeding have all been used. In comparison to conventional greenhouse and field settings, this causes a generation time reduction of 2.5 to 5. For wheat, canola, barely, and chickpeas, 2-3 crop generations are normally attained in a controlled greenhouse; however, speed breeding allows you to reach 4-6 crop generations in a year, providing you with an excellent opportunity to generate variations quickly. Other crops where speed breeding has been effectively applied include rice, soybean, sorghum, millets, rapeseed, sugarcane, tomato, and potato. This is optimistic for addressing challenges with food security.

 

But in order for any of these technologies to keep up with the growth of data, parallelization and effective computing hardware is needed. Genome editing combined with phenomics and speed breeding may be beneficial for fast-track crop breeding. Therefore, we must adapt and use these strategies in order to prevent starvation and famine among 10 billion people by the year 2050.

 

(Concluded….)

 

(Author is Scientist- MRCFC-Khudwani, SKUAST, kashmir. Email id: [email protected])

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