Molecular Plant Breeding
Mojtaba Khayam Nekouei; Mohammad Reza Ghaffari; Mohsen Mardi; Zahra Ghorbanzadeh; Rasmieh Hamid; Mehrshad Zeinalabedini
Abstract
Today, using advanced technologies such as the global positioning system (GPS), agricultural drones, satellite mapping, remote sensors, and precision agriculture machinery provides farmers with a lot of big data during production. According to the reports, this can be considered a part of the digital ...
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Today, using advanced technologies such as the global positioning system (GPS), agricultural drones, satellite mapping, remote sensors, and precision agriculture machinery provides farmers with a lot of big data during production. According to the reports, this can be considered a part of the digital economy in precision agriculture and be economically exploited. The analysis of this data cannot be processed by traditional processing systems due to its complexity. Given the size and complexity of big data, artificial intelligence can transform this data into valuable information through machine learning algorithms. This technology is being used to performance prediction algorithms, reducing agricultural inputs such as fertilizers and poisons, monitoring the growing conditions, pest management, breeding, molecular studies and finally value chain management. Developing programs using artificial intelligence technology will soon be able to manage the time of agricultural products entering the market, in addition to determining the planting time in order to increase productivity. The production of bio fertilizer from agricultural waste can be another achievement of the development of algorithms based on artificial intelligence to reduce the negative environmental effects and increase the economic productivity of the remaining waste from agricultural products. This study discusses the important applications of artificial intelligence in agriculture and its impact on Precision agriculture.
Molecular Plant Breeding
Parvaneh Mahmodi; Ahmad Moeini; Seyed Mojtaba Khayam Nekoie; Mohsen Mardi; Ghasem Hosseini Salekdeh
Volume 4, Issue 6 , October 2014, , Pages 35-46
Abstract
Saffron (Crocus sativus L.), is the most valuable and popular spice in the word. It is a triploid species of the Iridaceae family. Its long, red, and aromatic stigma distinguishes this species from others in its family. With the rapid advances in next generation sequencing technology, RNA sequencing ...
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Saffron (Crocus sativus L.), is the most valuable and popular spice in the word. It is a triploid species of the Iridaceae family. Its long, red, and aromatic stigma distinguishes this species from others in its family. With the rapid advances in next generation sequencing technology, RNA sequencing has risen as a cost-effective and powerful method for transcriptome study. De novo assembly of transcripts provides main solution to transcriptome analysis for organisms without reference genome. Precise sequencing and assembly of transcriptome reliable data are necessary for the downstream analysis. Accordingly, this work was analyzed by two of the most popular software's Trinity and SOAPdenovo for saffron stigma transcriptome to study the effective programs for transcriptome assembly. The results showed that the mean sequence length and the number of unigenes obtained by Trinity were more than SOAPdenovo (Trinity: 689, SOAPdenovo: 624). Translation of the better results produced by the appropriate assembler to protein led to a significant increase in the number of its records obtained at databases. Furthermore, these unigenes might help to identify more metabolite pathways. Assembled unigenes by Trinity had no lacking distance and were about twice the unigenes assembled by SOAPdenovo. As a general conclusion, it seems that selection of an appropriate software and its parameters is not easy without comprehension understanding of different software operation and their setting. Thus, comparison of the different softwares efficiency on the different organisms could provide some practical suggestions and choose an appropriate software.
