1 Introduction

When it comes to corn, the first thing that comes to mind is common corn, but there is actually a more popular variety - fresh corn (Zea mays L. var. saccharata). This kind of corn tastes particularly sweet and the grains are very tender. It has now become a regular on many people's tables. Interestingly, although it looks similar to ordinary corn, it is very different inside. According to research (Revilla et al., 2021), there are some special recessive genes in its endosperm that change the way starch is synthesized. As a result, there is a lot of sugar and less starch. However, it should be noted that this kind of corn is not a recent product. It was actually first cultivated in the United States. Today, this kind of corn is grown all over the world, and both farmers' income and our daily diet have changed a lot because of it.

When it comes to the improvement of fresh corn varieties, it is actually inseparable from the original germplasm resources. You may not know that these resources are like a huge gene bank, which contains various genetic characteristics. Breeding experts often have to look through these resources in order to find good genes to increase yield, disease resistance or improve nutrition (Dang et al., 2023). Take the particularly sweet corn on the market now, for example, their birth is not accidental. The researchers combined different kernel mutation genes together, and the result was not only higher sugar content, but also increased anthocyanins, tryptophan and other good things. Of course, not all attempts are successful, but it is these rich germplasm resources that make it possible to cultivate healthier and more distinctive fresh corn.

Although fresh corn is very popular, it lags far behind ordinary corn when it comes to variety improvement. This is mainly because its gene pool is relatively small and lacks a mature hybrid advantage system (Hu et al., 2021). However, recent studies have found that we must first understand the genetic situation of existing varieties before we can expand its genetic diversity. But the problem is that there are not many genetic changes in fresh corn itself, and the genetic laws of many traits are very complex, and the issue of environmentally friendly planting must also be considered, all of which make research particularly difficult. Interestingly, as the variety is introduced in various places, people have found that different climatic conditions have a great impact on it (Jompuk et al., 2020), which brings up new questions: Can these corns adapt to various environments? Will the performance be compromised?

Our main purpose in this study is to clarify the genetic diversity of fresh corn varieties around the world. To be honest, although molecular marker technology is very advanced now, comprehensive analysis specifically for fresh corn is rare. The research team plans to use the latest genotyping methods to focus on which key genes determine the quality characteristics of corn. For example, why are some varieties particularly disease-resistant and some have particularly high yields? It is important to understand these. Of course, knowing the genes is not enough, we also have to look at the relationship between these genes and actual planting performance. The significance of this work is that it can not only help us better understand the genetic characteristics of fresh corn, but more importantly, it can provide a basis for breeding better new varieties - those with higher yields, better disease resistance, and richer nutrition. In the final analysis, only by continuously improving varieties can fresh corn continue to maintain its market competitiveness, which is also critical to the development of global agriculture.

2 Data and Methods

2.1 Data sources and selection criteria

The data used in this analysis are actually quite interesting. They mainly come from reports from around the world that use molecular markers to study maize genetic diversity. You may have heard of technologies such as SNP and SSR, right? They are methods that can accurately detect genetic differences (Njeri et al., 2017). However, we were very strict when screening the data, and only selected studies published after 2015. Why? Because the newer the research technology, the more reliable it is. There is also a hard requirement, that is, these studies must record the molecular marker data in detail, and the maize samples collected must be comprehensive enough - they cannot come from just one region. After all, what we want to know is the true situation of maize genes worldwide. If the samples are too single, they will have no reference value.

2.2 Selection of genetic diversity evaluation indices

When it comes to assessing genetic diversity, researchers actually use several "rulers" to measure it. For example, they will count how many variants there are at each gene locus (Yang et al., 2022), look at the richness of the gene, and calculate the indicator called PIC, which reflects the amount of information about polymorphism. Interestingly, they pay special attention to those unique genetic variants because these often tell the story. Of course, just looking at these numbers is not intuitive enough, so methods such as cluster analysis and PCA are usually used. You may think these terms are a bit professional. To put it bluntly, it is to classify similar varieties and see how they are related. In this way, we can have a more comprehensive understanding of the genetic differences between different corn varieties, both within and between groups.

2.3 Meta-analysis methods and model construction

We chose a random effects model for this analysis, mainly considering the differences between studies - after all, there will always be discrepancies in the data produced by different laboratories. In terms of specific operations, we first converted the genetic diversity indicators reported in each paper into effect sizes, and then used the I² statistical method to look at the degree of difference in these research results (Shu et al., 2021). Interestingly, through the weighted average method, we finally obtained the overall level of genetic diversity of global maize germplasm. However, it is not enough to just look at the overall picture. We also made special group comparisons, such as looking at the differences in maize in different regions, or comparing different types of genetic diversity such as local old varieties, inbred lines and open-pollinated varieties. After this analysis, the results are much more comprehensive.

2.4 Statistical and analytical tools

The data analysis of this study mainly relies on tools such as R software and Meta-Analyst. You may not know that there is a meta package in R that is particularly useful. We use it to calculate effect sizes and evaluate data differences. When it comes to drawing pictures to show the genetic relationship between varieties, we have to mention the two R packages adegenet and factoextra (Bedoya et al., 2017)-they can intuitively present the results of cluster analysis and PCA. However, the most troublesome thing is to analyze linkage disequilibrium. Thanks to the LDheatmap package (Chiu et al., 2022), we can figure out the genetic recombination of different corn varieties. To be honest, although these tools are very professional, they are not as complicated to operate as imagined.

3 Overview of Genetic Diversity in Global Sweet Corn Germplasm

3.1 Distribution and classification of global germplasm resources

When it comes to fresh corn germplasm resources, they are actually distributed all over the world, but the United States, Brazil and China have made the greatest contributions. You may not know that many varieties can be traced back to a few old varieties, such as 'Stowell's Evergreen' and 'Country Gentleman' (Chhabra et al., 2022)-they all belong to the northern hard corn population. Interestingly, the National Plant Germplasm System (NPGS) of the United States has a collection of many inbred line resources from all over the world, which is a very comprehensive resource library. How do researchers generally classify these germplasms? It mainly depends on three points: genetic markers, appearance characteristics, and their "genealogical" relationship (Stansluos et al., 2023) (Figure 1). Through these methods, we can figure out what genetic connections there are between different populations and how diverse they are.

Figure 1 New ICT based fertility management model in private dairy farm India as well as abroad

3.2 Diversity assessment based on morphological, molecular, and genomic data

To understand the genetic diversity of fresh corn, researchers have put a lot of effort. They not only look at what corn looks like (morphological traits), but also use high-tech means such as molecular markers and genomic data. For example, they first classified different inbred lines in an "appearance association" style, and found that the genetic differences between them are really not small. When it comes to molecular markers, SSR and SNP are the most used technologies (Mahato et al., 2018). SSR markers can generate clear bands, and the degree of genetic variation can be known by calculating the PIC value. SNP markers are more powerful. They can not only find genetic differences, but also classify corn varieties according to hybrid advantages and grain types. But having said that, although these technologies are professional, their purpose is simple-to have a more comprehensive understanding of the genetic characteristics of fresh corn (Nguyen et al., 2023). With these data, breeders will be more confident in selecting new varieties.

3.3 Genetic differences in germplasm resources across geographic regions

There are actually quite a lot of genetic differences between fresh corn varieties in different places. For example, researchers in Brazil and the United States have found some interesting phenomena. In Brazil, RAPD and SSR markers were used to detect that the similarity between different varieties was higher than the similarity within the same variety (Lopes et al., 2015). This is a bit counterintuitive, right? The situation in the United States is different. When SNP markers were used to detect American inbred lines, it was found that although there were some differences between the main variety groups, the degree of differentiation was only moderate. Interestingly, some unique genetic variants can be found in different breeding groups. In fact, these differences are not difficult to understand. After all, temperate and tropical/subtropical corn are originally divided into different groups. Breeding experts will also divide them into more detailed groups based on characteristics such as hybrid vigor and corn kernel color. So now everyone thinks that in order to breed better varieties, we must first understand the genetic characteristics of these local varieties, which is also important for protecting these germplasm resources.

4 Factors Influencing Genetic Diversity in Sweet Corn Germplasm

4.1 Effects of geography and ecological environments

When it comes to the genetic diversity of fresh corn, it actually has a lot to do with where it grows. Think about it, the climate, soil and other environmental conditions in different regions are not the same. In order to adapt to these differences, corn has gradually formed unique genetic characteristics. Some studies have used microsatellite markers to analyze and found that the environment does affect the genetic structure inside and outside the corn population. Interestingly, researchers also found a phenomenon - artificially selecting the flowering time of corn in different places has not only changed its growth characteristics, but also important indicators such as yield (Beissinger et al., 2015). This fully shows that local environmental conditions have a great impact on the genetic diversity of corn. But then again, although environmental factors are very important, how they affect it may depend on the specific conditions of different regions.

4.2 Impacts of cultivation history and artificial selection pressure

The genetic diversity of fresh corn is actually inseparable from the history of human cultivation. Think about it, since the earliest domestication, farmers have been selecting those corns that grow well for seeds, but the result has narrowed the gene pool (Da Silva et al., 2020). In particular, in pursuit of sweetness, mutant varieties such as su1 and sh2 are specially selected, making the differences between different inbred lines increasingly large. But then again, this kind of artificial selection is not without benefits. At least now using selection indexes for breeding can indeed improve the yield and quality of fresh corn. But the problem is that the "population bottleneck" effect during the domestication process caused a sharp drop in the corn population, resulting in the disappearance of many genetic variants. Thinking about this now, it's a pity.

4.3 Roles of genetic drift and gene flow

The genetic diversity of fresh corn is quite interesting. It is mainly affected by two factors: genetic drift and gene flow. Let's talk about genetic drift first. Simply put, it is the random change of gene frequency - especially for varieties with small planting areas, this change is particularly obvious. Recent studies have found (Li, 2024) that corn has experienced a process of rapid population decline and expansion in history, which has affected the diversity pattern of the entire genome. But interestingly, gene flow can offset this effect. What is gene flow? It is the exchange of genes between different corn varieties. Through marker technologies such as RAPD and SSR (Choquette et al., 2023), we found that fresh corn has gene exchange both within varieties and between different varieties. What's more amazing is that artificial intelligence analysis can now predict what kind of genetic differences these gene flows will bring. To put it bluntly, gene flow is like constantly injecting fresh blood into the corn gene pool, which is particularly important for maintaining diversity.

5 Comparison of Genetic Diversity Analysis Methods

5.1 Analyses based on phenotypic data

When it comes to studying the diversity of corn varieties, the most direct way is to see what they look like. Researchers usually measure visible and tangible characteristics such as plant height, ear height, and grain yield. This method is particularly commonly used in corn germplasm research. Although it sounds simple, it works surprisingly well. For example, in Egypt, scientists have used this method to study commercial hybrids (Al-Naggar et al., 2020). They found that after the morphological data of these corns were processed using PCA and UPGMA cluster analysis, the differences in agronomic traits of different varieties were clear at a glance. Interestingly, the same method was also used in southern Africa (He et al., 2017), and it was found that there were quite large differences between different brands of hybrids.These findings are of great reference value for corn classification and breeding. Although the method is traditional, it does work.

5.2 Analyses using molecular markers

When it comes to analyzing the genetic diversity of corn, the most commonly used molecular markers are SSR and SNP. These technologies are indeed much more accurate than traditional methods. For example, in Portugal, when researchers used SSR markers to detect local corn germplasm (Franco-Duran et al., 2019), they found that the differences between different inbred lines were quite obvious, and confirmed that Portuguese corn is actually "hybrid". But what's interesting is that SNP markers give richer information. When using it to analyze global corn germplasm, temperate and tropical varieties are naturally divided into different groups, and the genetic differences between different hybrid advantage groups are also clearly seen. Even more surprising is the performance of tropical corn-SNP and haplotype analysis shows (Liu, 2024) that tropical corn not only has higher genetic diversity, but also has a faster decay of linkage disequilibrium, which is good news for future breeding work.

5.3 High-throughput analyses based on whole-genome data

The means of studying corn genes are becoming more and more advanced. Take the IRAP technology, for example. It can reveal the ecological adaptation characteristics of corn varieties through retrotransposons, which is quite interesting. But even more powerful is the whole genome SNP analysis (Yang et al., 2022) (Figure 2). This technology has recently discovered more than 1 100 selected genomic regions in temperate and tropical corn. Interestingly, many of these regions are regulatory genes, which seem to play an important role in the process of corn improvement. These new methods have indeed deepened our understanding of the genetic structure of corn. Although the technology is complex, the information obtained is indeed comprehensive.

Figure 2 New ICT based fertility management model in private dairy farm India as well as abroad

5.4 Advantages and limitations of different analytical methods

When studying the genetic diversity of maize, we have several methods to choose from, but each has its pros and cons. The most traditional one is phenotypic analysis, which is simple and cost-effective, and can be used in many breeding projects (Ghonaim et al., 2020). But the problem is that what maize looks like is greatly affected by the environment, and the results measured by different people may be different. In contrast, molecular markers such as SSR and SNP are much more accurate and less interfered by environmental factors, but laboratory operations are complicated and costly. The most comprehensive one is whole genome analysis, which can even show which specific gene regions have been selected (Mhoswa et al., 2016). But to be honest, this method is not only expensive, but also requires a professional bioinformatics team to process massive amounts of data. So you see, the method you choose depends on specific needs and conditions, and there is no perfect method.

6 Conservation and Utilization of Genetic Diversity in Sweet Corn Germplasm

6.1 Identification and evaluation of superior germplasm resources

To protect and utilize the genetic resources of fresh corn, we must first find those truly high-quality varieties. Researchers usually use a variety of molecular markers to evaluate these germplasm resources. For example, a study used microsatellite marker analysis to find that there is significant polymorphism and heterozygosity between different fresh corn varieties (Jompuk et al., 2020). Interestingly, if field observations and molecular testing are combined, more surprises can often be found-some inbred lines not only have outstanding yields, but also have excellent sweetness performance. Although each detection method has its own characteristics, the ultimate goal is to screen out high-quality germplasm for breeding work, which is crucial to improving the key traits of fresh corn. After all, only after finding good materials can we talk about subsequent breeding improvements.

6.2 Genetic improvement potential of germplasm resources

When it comes to the potential for improvement of fresh corn, it is actually much greater than we imagined. Researchers recently discovered that even for those commercial inbred lines, there is still a lot of untapped genetic diversity hidden in the gene pool (Slonecki et al., 2023). Interestingly, when SNP markers were used to detect different breeding groups, it was found that the genetic differences between them were quite obvious-this is not a bad thing, but it provides more possibilities for breeding new varieties. What is even more exciting is that by combining several kernel mutant genes together (Priyanka et al., 2021), the sugar and anthocyanin content of fresh corn can be further improved. Although the varieties on the market are already good, according to this trend, it should not be difficult to develop healthier and more distinctive fresh corn in the future.

6.3 Mechanisms for global germplasm conservation and sharing

When it comes to protecting the germplasm resources of fresh corn, there are actually quite a lot of ways. For example, they can be allowed to grow slowly, or stored at low temperatures, or a special gene bank can be established - all of which are to preserve these precious genetic diversity for a long time. Interestingly, although these technologies have their own characteristics, their purpose is the same: to leave a "backup" for future breeding work. The international community also attaches great importance to this matter. Frameworks such as the Convention on Biological Diversity and the Global Plan of Action (Mahato et al., 2018) particularly emphasize the importance of protecting agricultural biodiversity. However, protection alone is not enough, and these resources must be available to everyone. The current global sharing of germplasm has indeed made it easier for researchers to obtain more diverse genetic materials to improve crops. Although it may be a bit complicated to operate, it is indeed critical for breeding work.

7 Research Challenges and Future Prospects

7.1 Key Issues in current sweet corn germplasm resource research

There is a headache in studying fresh corn germplasm now - the genes between varieties are too similar. Ferreira et al. found in 2018 (Ferreira et al., 2018) that the genetic diversity of fresh corn mainly exists within a single variety, and there is little difference between different varieties. This is troublesome. Think about it, the genetic differentiation between inbred lines is not high, and coupled with this situation, it is particularly difficult for breeders to introduce new traits into corn. Although the internal variation of a single variety is relatively rich, this "dominant" diversity pattern is indeed a considerable obstacle to the breeding of new and improved varieties.

There is a paradoxical phenomenon in corn breeding: there are many good things in the germplasm bank, but few are actually used in commercial breeding. The reason is that it is too troublesome to use these resources well. Just think about it, just to figure out their genotypes and phenotypes, you have to do a lot of testing and evaluation work. Although the diversity in the resource library is quite rich (Ferreira et al., 2018), in actual operations, breeders often still focus on the few commonly used varieties. This is easier said than done, resulting in many potential excellent genes being idle and failing to play their due value.

7.2 Potential of interdisciplinary approaches in genetic diversity analysis

Now, the old methods alone are no longer enough to study the genetic diversity of fresh corn. Interestingly, the combination of new methods such as molecular biology and bioinformatics with traditional statistical genetics has surprisingly good results. For example, high-throughput sequencing technology such as GBS can obtain massive amounts of SNP data at once, making genetic variation clearly visible. But then again, it is not enough to just look at genes, and we have to evaluate them in combination with actual performance in the field. Although these new technologies are a bit complicated to use, they do allow us to have a more comprehensive understanding of the genetic characteristics of fresh corn. After all, to truly understand these corn varieties, we have to take into account everything from laboratory data to field performance.

New tools for studying fresh corn are becoming more and more interesting. Take artificial neural networks, for example. When combined with GT biplot analysis (Mehta et al., 2017), the relationship between genotypes and traits can be more accurately found. Although these methods sound high-tech, to put it bluntly, they help us find good varieties faster. Interestingly, through these analyses, breeders can lock in those genotypes that may have high yields and high quality in advance, without having to look for a needle in a haystack as before. Of course, these tools are not omnipotent, but they do provide new ideas for breeding better fresh corn varieties.

7.3 Applications of data integration and multivariate analysis in future research

In the future, the key to studying fresh corn germplasm resources is to integrate various data. You see, molecular data such as SNP and microsatellites are not enough. They must be analyzed in combination with field performance data and environmental factors (Diwan et al., 2015). Only in this way can we fully understand the practical role of genetic diversity. In fact, multivariate statistical methods such as PCoA and cluster analysis are quite useful (Kumar et al., 2022), which can help us clarify the genetic background of different corn varieties. Although the operation is a bit complicated, the parent materials selected in this way are indeed more reliable, and the new varieties bred are more adaptable. But then again, it is also a big challenge for researchers to handle so much data.

8 Concluding Remarks

When studying the genetic diversity of fresh corn, molecular markers such as SSR and RAPD are most commonly used. Interestingly, these tests show that the polymorphism of fresh corn is quite high, averaging over 80%. However, a closer look at the data reveals that these variations mainly come from within a single variety, and there is little difference between different varieties - this shows that their genetic basis is indeed relatively narrow. Through cluster analysis, different inbred lines can be clearly divided into several groups, and it seems that the background is quite diverse. Speaking of key genes, the two genes su1 and sh2 that control sweetness are particularly important, and they contribute greatly to the genetic diversity of fresh corn. Although the overall genetic basis is not broad, the diversity patterns revealed by these markers are still quite interesting.

The results of the study on the genetic diversity of fresh corn are quite interesting and can provide inspiration for breeding and conservation work. You see, although the differences between varieties are not large, the genetic variation within a single variety is very rich - this means that breeders actually have a lot of good cards to play. To cultivate new varieties with high yield, high quality and disease resistance, these genetic resources hidden within the varieties are particularly valuable. But then again, how to protect these resources is also a technical job. Methods such as in situ protection and ex situ protection can be considered, and establishing a core germplasm bank is also a good idea. After all, only by maintaining these genetic diversities can the breeding work of fresh corn continue. Although the genetic basis between varieties is still relatively narrow, if we make good use of existing resources, the future breeding prospects are still worth looking forward to.

In the future, we will have to use some new tricks to study the genetic diversity of fresh corn. Now genomic tools are becoming more and more advanced. High-throughput sequencing technologies such as GBS can show the genetic structure of germplasm resources more clearly. However, genetic data alone is not enough. The performance observed in the field and genetic information must be analyzed together to find the key gene markers that determine excellent traits. This is easier said than done. This requires the cooperation of researchers, breeders, and resource protection experts. Although each of them focuses on different points, only when everyone cooperates well can the genetic resources of fresh corn be truly protected and utilized.

Acknowledgments

Members also thank the laboratory team for their support and cooperation.

Conflict of Interest Disclosure

The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

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