Abstract Rice is the staple crop of Nagaland, India and is widely cultivated in traditional shifting cultivation agroecosystems. Despite the existence of germplasm diversity there is limited information on characterization of such traditional rice landraces. This study aimed to evaluate grain morphological diversity of traditional rice collected from Mon, Nagaland. A total of 147 rice accessions were collected from 24 villages across eight administrative blocks comprising of 41 sticky and 106 non-sticky rice types. Considerable variability was observed among the accessions for grain length (GL), width (GW), ratio (GR), and grain weight (GWt). Compared to upland, submerged habitat showed 26, 38 and 19% greater GL, GR and GWt and 10% less GW. In upland habitat, sticky rice had 10, 8 and 13% greater GL, GW and GWt, respectively, than non-sticky type. Principal component analysis revealed that PC1 and PC2 explained 89.8% of the total variation, with GL, GW, GWt and GR contributing strongly to the observed diversity. Cluster analysis grouped the rice accessions into three distinct clusters with 82, 23 and 42 accessions in clusters I, II and III, respectively.  Cluster II had accessions with greater GL (8.21 mm) and GR (3.66) and cluster III with greater GW (3.21 mm) and GWt (23.35 g). Several landraces such as Solokhabu, Younghah C, China yam T, Chahlo and Teeyin were identified as distinct based on grain traits. The results highlight occurrence of substantial morphological diversity in the collected traditional rice landraces indicating the importance for germplasm conservation for future rice improvement efforts.

Keywords: Germplasm diversity, Jhum, Standard evaluation system, Sticky rice, Upland rice

Funding: Germplasm collection was funded by Kohima Science College, Jotsoma.

Citation:  Konyak, Z. and Ao, S. 2026. Documentation and seed trait variability of landrace rice from Mon, Nagaland, India. Natural and Life Sciences Communications. 25(3): e2026070.

Graphical Abstract:

INTRODUCTION

Upland rice in India comprises of about 13% land area and it contributes to 4% of the total rice production (Singh et al., 2011). Despite its limited area, upland rice stores a great reserve of genetic diversity that can be effectively used for breeding purposes and develop new varieties that can overcome challenges posed by climate change especially water stress (Yoshida, 1983; Yiping et al., 2007; Hanamaratti et al., 2008; Pusadee et al., 2024). Generally, rice grown in mountain agroecosystems largely consists of traditional landrace varieties having valuable genotypic traits; thus, collecting and assessing such germplasm diversity is important to prevent genetic erosion (Rerkasem and Rerkasem, 2002; Nourollah, 2016; Zapico et al., 2020). In Northeast region of India, rice is grown in jhum or shifting cultivation, upland rainfed, wet terrace rice cultivation, lowland paddy, and deep waters (Kumar et al., 2017). The region has rich germplasm diversity with varieties having high yield potential even in nutrient poor soil condition, pest and pathogen resistance, and better agronomic performance, high iron and zinc contents (Rao and Srinivasan, 1978; Choudhury et al., 2013; Vanlalsanga et al., 2019).

Farmers consider grain characters such as shape, size, color and weight as important traits for selecting rice varieties for cultivation (Das et al., 1983; Rathna Priya et al., 2019). Grain morphological features such as grain size (GS) and weight are vital traits associated with seed vigor and yield (Seshu et al., 1988; Roy et al., 1996; Albert et al., 2024; Fatamatuzzohora et al., 2024). Grain ratio (GR), grain width (GW) and grain length (GL) contribute to the highest variation in rice germplasm (Sarma et al., 2022). Colored rice varieties such as brown, red and black rice contains more anthocyanin, fiber, proteins, carbohydrates, vitamin B6, vitamin E minerals like magnesium, thiamin and phosphorus (Yamuangmorn et al., 2020; Zahra and Jabeen, 2020; Das et al., 2023).

Nagaland has several collections of traditional rice varieties with great genetic diversity having high heritability for traits such as high 1,000 grain weight (GWt), panicle weight, and grains per panicle (Chakraborty and Chaturvedi, 2014; Gurung et al., 2018). Studies conducted on rice germplasm from Nagaland reported that grain characteristics varies considerably in the collected germplasm (Roy et al., 2014). Singh and Misra (2014) reported wide variations in GR and grain color among rice accessions collected from four districts of Nagaland viz., Dimapur, Kohima, Mokokchung and Tuensang. Mon district with its diverse agro-climatic conditions, stores rich genetic diversity of rice varieties because large section of the farming community grow rice as their main crop in their jhum fields. Thus, research on rice germplasm collection and grain morphology characterization from Mon district of Nagaland is vital. Previous germplasm collection has reported 12 rice accessions collection by Roy et al. (2014) and 35 rice accessions by Pradheep et al. (2014) from Mon, Nagaland. However, detailed collection from all the blocks was not undertaken. Despite previous efforts, comprehensive characterization of rice landraces across all administrative blocks of Mon district remains limited. Furthermore, multivariate approaches integrating grain morphology for diversity assessment are limited for this region. Therefore, the objectives of this study were to understand the traits of local rice accessions and to evaluate germplasm diversity of rice accessions using grain morphological characters. Principal component analysis (PCA) and cluster analysis were employed to identify key grain traits that contribute to diversity and to classify accessions into morphologically distinct groups. The information from this study is expected to characterize traditional upland rice landraces that could serve as a resource for selecting germplasm for breeding programs aimed at improving grain quality, yield and germplasm conservation.

MATERIALS AND METHODS

Study area

This study was conducted in Mon district, Nagaland located in the Northeast India (26°59′11″ N, 95°10′26″E and 26°21′12″ N, 95°55′49″E). Mon district is divided into 8 administrative blocks consisting of several villages in each block. The eight blocks of Mon district are Tizit, Mon, Wakching, Tobu, Aboi, Angjangyang, Phomching and Chen (Figure 1).

Sampling design and germplasm collection

The study was conducted through a survey method using a stratified random sampling approach, each block considered as a stratum. Field trips were conducted from December 2021 to January 2023. Three random villages were chosen from each block and a total of 24 villages were visited (Figure 1). Five farmers from each village nominated by the respective village council were interviewed using a semi-structure interview method to collect qualitative data about their agriculture management practices and rice types cultivated in their fields were collected. Information regarding agroecosystem (upland or submerged), grain characteristics and rice types (sticky or non-sticky) was obtained through interviews with the farmers during germplasm collection.

Standard field data recording techniques was conducted using both traditional and digital media including field notebooks, standardized paper forms, and portable digital devices to ensure accurate sample labeling, collection site localization via GPS (Way, 2011). Rice samples were obtained from the farmers’ store, labelled, and the samples were assigned with a unique collection number (Hay and Probert, 2011). Passport data for the rice was recorded according to the format provided by ICAR-NBPGR and deposited in the department of Botany, Kohima Science College, Jotsoma, India for further studies.

Seed analysis

Seed morphology of the collected rice germplasm such as GL, GW, GR, GS, grain shape (GSh), dehusked kernel- length (KL), width (KW), ratio (KR), size (KS) and shape (KSh) was determined following the Standard Evaluation System (Cruz and Khush, 2000; International Rice Research Institute, 2002). Grain and kernel characteristics were determined by measuring 10 grains per accession. For GWt, seeds were oven-dried until constant mass and measured according to protocols provided by International Seed Testing Association (2019). Final weight was adjusted to 14% moisture content.

Statistical analysis

Grain and kernel characteristics were evaluated to find the Pearson’s correlation coefficient between variables using SAS software (SAS^® Studio, SAS Institute Inc., 2024). Principal component analysis and cluster analysis were performed using the R statistical software package (R Core Team, 2023). For PCA and cluster analysis, GL, GW, GR, GS, GSh and GWt data were used. Cluster analysis was performed using Ward D2 method. The collected rice germplasms were subjected to t-test to compare means between upland and submerge non-sticky rice type and sticky and non-sticky rice types of upland habitat.

Figure 1. Rice germplasm collection sites in Mon district of Nagaland.

RESULTS

Rice distribution and seed morphology characterization

A total of 147 rice accessions were collected comprising of 41 sticky and 106 non-sticky rice types, there were 132 upland, 2 lowland, and 13 wet terrace rice accessions (Table 1). Both the lowland and wet terrace rice were cultivated as submerged rice. The number of rice accessions was highest from Ukha village under Angjangyang block with a total of 13 traditional rice accessions, followed by Pesao (Tobu block) and Longchang village (Angjangyang block) with 11 rice each. The least were from Chenloisho and Chenmoho villages (Chen block) with two accessions each. Among the blocks, Angjangyang had the highest rice collection with 32 accessions, followed by Tobu block with 28 accessions. Chen block ranked the least with seven rice accessions.

Table 1. Number of rice accessions from 24 villages of 8 administrative blocks of Mon district, Nagaland, India and altitudinal variations of the collection sites.

The average GWt was 17.99 g across all accessions. Thousand grain weight was greatest for Solokhabu rice with 33.2 g and least for Wangtah rice with 9.4 g. Atleast 41% of the rice grains were very long followed by medium, long and short. Majority of the grain shape was medium, followed by bold and slender. Frequency distribution of grain characters on size and shape is tabulated in Table 2.

Table 2. Grain size and shape profile of rice accessions from Mon, Nagaland, India.

Comparison of GL, GW, GR and GWt between upland and submerge rice collections showed significant differences (Table 3). Compared to upland rice, submerged rice exhibited greater GL, GR and GWt by 26, 38 and 19%, respectively, but GW decreased by 10%. With respect to upland rice type, there were significant difference between sticky and non-sticky rice in GL, GW and GWt. Sticky rice had 10, 8 and 12%, greater GL, GW and GWt, respectively, compared to non-sticky type.

Table 3. Comparison of grain traits between submerged and upland non-sticky rice, and between sticky and non-sticky rice types of upland habitat.

Correlation, principal component and cluster analysis

A Pearson’s correlation matrix was initially performed to identify redundant variables for further performing PCA and cluster analyses. The Pearson’s correlation coefficient between seven characteristics of 147 rice accessions were determined (Table 4). The correlation analysis among grain and kernel characteristics revealed several significant relationships. Grain length showed a positive correlation with GW at r = 0.224 (P < 0.01), GR at r = 0.619 (P < 0.01), GWt at r = 0.707 (P < 0.01), KL at r = 0.910 (P < 0.01), KW at r = 0.180 (P < 0.01), and KR at r = 0.502 (P < 0.01). Additionally, GW had a negative correlation with GR at r = -0.613 (P < 0.01) and a positive correlation with GWt at r = 0.648 (P < 0.01) and KW at r = 0.835 (P < 0.01). Grain ratio exhibited a positive correlation with KR at r = 0.774 (P < 0.01). Grain weight was correlated with KL at r = 0.685 (P < 0.01). Kernel length showed a significant positive correlation with KR at r = 0.652 (P < 0.01).

Table 4. Pearson’s correlation coefficient among seven quantitative traits in 147 rice germplasm.

Due to strong correlations between grain and kernel traits (e.g., r = 0.91 for GL and KL; r = 0.84 for GW and KW), kernel-specific traits were excluded to prevent disproportionate influence of grain size related variance in the PCA and cluster analysis. Therefore, six characteristics viz., GL, GW, GR, GS, GSh and GWt were used to evaluate the germplasm diversity of 147 rice accessions. The first two principal components (PC1 and PC2) explained 89.8% of the variations. PC1 explained 51.2% of the variations while PC2 explained 38.6% of the variations (Figure 2-A). Five traits such as GL, GS, GSh, GWt and GR explained majority of the variations in PC1 (Figure 2-B). While GW, GR, GSh and GWt were the major contributors in PC2. The PCA biplot segregated the germplasm diversity by grain traits explained by the first two PCs (Figure 3).  China yam T, Younghah C and Solokhabu had longer GL and greater GWt. Yeangkok khaibu, Zamzang and Lamkhao had wider GW. Yeamsheang La, Chahlo, Teeyin, Wangchahlah and Wangjah lahlo were some of the accessions having greater GR. Salei C and Phehsa T were segregated as short GS and Phehsa T, Poamansa, Hahkit, Matoi and Shahgo were segregated as having bold GSh. Hahmei, Menyu and Khopcho were isolated as slender GSh and medium GS.

Figure 2. Scree plot and contribution of variables to principal components. A) The x-axis represents the principal components (PC1–PC6), while the y-axis shows the percentage of explained variance. The first two components (PC1: 51.2%, PC2: 38.6%) collectively account for the majority of the variance. Subsequent components contributed progressively less than PC1 & 2. This plot helps in determining the optimal number of components to retain for effective dimensionality reduction and data analysis. B) Contribution of seed morphological traits, grain length (GL), grain width (GW), grain ratio (GR), grain weight (GWt), grain size (GS) and grain shape (GSh) to six principal components (PC1–PC6) represented as a heatmap where the size and color intensity of the circles indicate the level of contribution. Darker and larger circles represent greater contribution.

Figure 3. Principal component analysis (PCA) biplot showing distribution pattern of 147 germplasm based on their grain traits. The first two Principal components (PC 1 & PC 2) which collectively explain maximum proportion. Each point represents germplasm accession while the vectors indicate contributing factors to clustering.

Cluster analysis was performed on 147 rice germplasms and dendrogram was generated based on six grain morphological characters (Figure 4). The number of accessions was 82, 23, and 42 for clusters I, II, and III, respectively. The mean values of each cluster were calculated for each variable (Table 5). The comparison of grain morphological characteristics between the three clusters revealed differences across various traits. Compared to cluster II and III, cluster I had generally shorter GL by 19 and 17%, respectively; 18% narrower and 16% broader GW than cluster II and III; 32% greater GR than cluster II; and 20 and 36% lesser GWt than cluster II and III, respectively. Cluster II had greater GL and GR and cluster III had greater GW and GWt. In cluster I, there was collection of bold, medium and slender GSh with 79% medium and 17% bold GSh; GS consisted of very long, long, medium and short grains with 55% medium and 26% long and 17% very long GS. All accessions in cluster II were slender GSh and 74% very long, and 13% each of long and medium GS. In cluster III, 93% were medium and the rest slender GSh and 69% were very long and the rest were long GS. Kernel size was predominantly short across all clusters, accounting to 66, 78 and 74% for cluster I, II and III. Medium rice grains comprised of 26, 22 and 26% while long kernel (7 accessions) were observed only in Cluster I. Kernel shape showed clear deviation from GSh. In Cluster I, 50% of the kernels were mostly medium grains, 44% bold and 6% slender. Despite all grains being slender in Cluster II, 48% of rice grains shifted towards medium, 39% bold and 13% slender. Similarly, in Cluster III, kernels were mainly medium (67%) and bold (31%) with very few slender grains (2%).

Figure 4. Dendrogram generated based on six seed morphological characters of 147 traditional rice accessions collected from Mon district, Nagaland. The dendrogram visually represents the relationships based on grain characteristics with distinct colour branches signifying clusters with similar morphological traits.

Table 5. Comparison of grain morphological characteristics between three clusters.

DISCUSSION

Rice distribution in Mon district

The collection of 147 rice accessions from Mon district, Nagaland, highlight the existence of rich agrobiodiversity of rice. The altitudinal variation ranging from 500 to 1,800 m above mean sea level, presents unique conditions that contribute to existence of diverse rice landraces. The rice landraces collected from higher altitudes may possess specific traits, such as cold tolerance (Xiao et al., 2018; Lee et al., 2025). The prevalence of upland or jhum agricultural practices is supported by the dominance of upland rice with 132 accessions indicating that local farmers have optimized their agricultural practices to suit the mountainous terrain, leading to a dominance of upland rice landraces over lowland (2 accessions) and wet terrace (13 accessions). Angjangyang block recorded the highest number of rice accessions (32), followed by Tobu block (28). Conversely, Chen block had the least number of accessions (7), possibly due to dependence on maize and millets as the main food source, and or less favourable conditions for cultivation. Villages such as Ukha with 13 accessions, Pessao and Longchang with 11 accessions is indicative of diverse microclimatic conditions within each jhum cycle; also, these areas are located at a higher elevation ranging from 1,220 to 1,710 m.

Grain variations among rice accessions

Grain size analysis indicated that 41% of the rice accessions had very long grains, followed by medium (33%), long (25%), and short grains (1%). These findings align with the previous reports which highlighted the preference for very long and slender grain rice due to their cooking quality, socioeconomic factors and market demand (Cuevas et al., 2016; Mottaleb and Mishra, 2016). The grain shape distribution showed that 71% of accessions had medium grain shape, 10% slender, and 20% bold. This variation in grain shape is related to consumer preference, quality, and commodity value (Harberd, 2015; Hori and Sun, 2022). Based on GS and GSh data, farmers in Mon district prefer medium and very long rice grains.

This study revealed significant variations in grain traits across different habitat and rice types. Submerged rice exhibited greater GL, GR, and GWt comparing with upland accessions indicating the production of longer, more slender and heavier grains. These differences may be attributed to variations in water availability, nutrients and growth conditions between submerged and upland ecosystems. Under submerged habitat, several nutrients become soluble and available for the rice plant which may result in larger and heavier grains (Sahrawat, 2005). In contrast, upland rice is cultivated in rainfed conditions characterized by intermittent drought and lower soil nutrients (Bernier et al., 2008) which may limit grain development resulting in smaller grain size (Nokkoul and Wichitparp, 2014). Sticky rice type showed significantly higher GL, GW and GWt compared to non-sticky rice, however, grain ratios did not differ between the two types. Factors such as temperature, water availability and nutrient content during grain development influence cell division, expansion and grain filling processes, ultimately affecting grain size and shape in rice (Morita et al., 2005; Chen et al., 2025). Therefore, the observed variations within these rice habitat and type likely reflects the combined effects of genetic diversity and ecological adaptation. Overall, these results indicate that sticky rice tends to have larger and heavier grains, although grain shape remains unaffected.

This study also revealed that habitat significantly influence all the traits measured (GL, GW, GR and GWt), highlighting the importance of habitat in determining grain morphology and weight. Rice type also significantly affected grain traits (GL, GW and GWt). Similar genotype by environment interactions affecting grain size have been reported in previous studies on rice germplasm (Wang et al., 2014; Xu et al., 2014). Overall, the variation observed in GS, GSh, and GWt among the rice accessions highlights occurrence of substantial diversity within traditional rice germplasm. Such diversity reflects long-term adaptation to different agroecosystems as well as farmer-driven selection for desirable grain characteristics. Understanding this diversity is important for germplasm characterization, conservation, and potential utilization in rice breeding programs, particularly for improving grain quality and adaptation to diverse environmental conditions.

Grain characteristics and its relationships

The results of the Pearson's correlation analysis provide important insights into the relationships between various rice grain and kernel characteristics across 147 rice accessions. Grain length exhibited strong positive correlations with several traits, especially KL, which showed the highest correlation. This suggests that longer grains tend to be associated with longer kernels, a characteristic commonly associated with grain morphology in rice (Takita, 1983; Rajendran et al., 2021). Previous studies have also reported strong associations between GS and KS, reflecting the close morphological relationship between grain and kernel dimensions in rice (Zhang et al., 2025). Additionally, GL was positively correlated with GW, GR, GWt, and KR, pointing to a complex network of relationships that influence overall rice quality. This is consistent with findings from Nirmaladevi et al. (2015), who emphasized the interconnected nature of these traits and their collective impact on rice morphology and quality. Grain weight showed significant positive correlations with both GL and KL, suggesting that accessions with larger grain and kernel sizes tend to have heavier GWt. However, these measurements represent phenotypic characteristics observed in rice samples collected from farmers’ fields and therefore, may reflect the combined influence of management, genetics and environmental factors. Studies by Zuo et al. (2021) also reported associations between grain size and thousand grain weight in rice. Solokhabu, Younghah C and China yam T, three of the distant germplasms among the 147 rice germplasms showed greater GWt primarily contributed by longer GL and wider GW. Grain width and GL were positively related to GWt, suggesting that wider and longer grains tend to weigh more (Song et al., 2007). In terms of kernel characteristics, KL demonstrated a strong positive correlation with KR, suggesting that longer kernels generally have a higher KR, which is often associated with superior milling quality and grains with higher KRs are preferred for their milling recovery and cooking quality (Unnevehr and Juliano, 1992; Lyon et al., 1999; Laborte et al., 2015). On the other hand, KW exhibited a negative correlation with KR, suggesting that narrower kernels tend to have higher KRs. Grain ratio showed a positive correlation with KR and a negative correlation with KW. These findings suggest that rice varieties with greater GRs tend to also have greater KRs, which are indicative of better-quality rice (Hori and Sun, 2022).

Clustering based on grain traits

The cluster analysis of 147 rice germplasms based on grain characters GL, GW, GR, GS, GSh and GWt revealed considerable diversity among the accessions. Cluster I, which consists of 82 accessions, exhibited lowest GL and GWt with intermediate GW and GR comparing with Cluster I and II. This indicates that a large proportion of the traditional landrace rice germplasm in the study area consisted of medium-sized grains with comparatively lighter grain weight. Cluster II, with 23 accessions, was characterized by longest GL and highest GR, indicating the presence of long and slender rice grains. The relatively lower GW observed in this cluster contributed to the higher grain ratio, resulting in slender grain morphology. These characteristics suggest that Cluster II accessions could be valuable for breeding programs aimed at developing rice varieties with long and slender grains, which are often preferred in certain export markets and culinary applications (Fitzgerald et al., 2009; Mottaleb and Mishra, 2016). In contrast, Cluster III, comprising 42 accessions, displayed broader grains with highest GW and GWt among all the clusters. The lower GR observed in Cluster III indicates that the grains were comparatively shorter and wider in shape. The presence of heavy grain types within the cluster indicates that certain traditional landraces possess traits that may represent useful phenotypic variation among traditional landraces. The clustering pattern observed in this study highlights the traditional landrace rice diversity present within traditional rice germplasm of Mon district. This diversity likely reflects the combined effects of genetic variation among landraces, adaptation to diverse micro-environments, and farmer-mediated selection across generations (Konyak and Ao, 2025). Traditional rice cultivation systems often involve the maintenance of multiple landraces within the same field; each adapted to specific ecological conditions or preferences. Such farmer-managed systems contribute significantly to the conservation of genetic diversity in rice (Roy et al., 2024). Previous studies have similarly reported substantial variation in grain morphology among traditional landrace rice, emphasizing the importance of landraces as reservoirs of valuable genetic traits for crop improvement and breeding programs (Ray et al., 2013; Jukanti et al., 2026).

The principal component analysis (PCA) effectively summarized the variation present among the 147 rice accessions by reducing multiple correlated traits into a few informative components. The first two principal components together accounted for 89.8% of the total variation, indicating that the majority of variability in grain morphological traits can be explained using these two dimensions. The high cumulative variance explained by PC1 and PC2 indicates strong trait interdependence and validates the effectiveness of selected grain traits in capturing morphological diversity. Such a high cumulative variance suggests that PCA is highly efficient in capturing the underlying structure of variation in rice germplasm, as also reported in earlier studies (Sanni et al., 2012; Nachimuthu et al., 2015). Overall, the PCA result indicated that GL, GW, GR and GWt contributed strongly to the overall variation among the accessions. Similarly, the cluster analysis grouped the germplasms into distinct categories characterized by differences in GL, GW, GR and GWt. This agreement between PCA and cluster analysis indicates that variations in grain dimensions especially GL, GW, GR, GWt, constitutes the primary factors structuring the diversity among the traditional rice landraces studied.

Variation in grain and kernel characteristics among clusters

In Cluster I, majority of the GS were medium and long; however, after dehusking, 54 rice accessions were categorized as short and 21 medium rice grains. While grains were predominantly very long and long in Cluster II and III, KS was dominated by short grains, with no occurrence of very long kernels. This indicates that GS does not directly reflect KS, despite the strong correlation between GL and KL. The observed reduction in size from grain to kernel can be attributed to the contribution of the husk, which increases grain length. Grain shape in rice is typically determined by the length-to-width ratio, which is influenced not only by kernel dimensions but also by the enclosing husk that contribute to overall grain morphology (Yu et al., 2024).  In Cluster I, grains classified as medium shifted toward bold kernels. This transition from slender or medium grains to relatively broader KS indicates that that GW and KW do not scale proportionally, leading to changes in KSh classification. Cluster II, which consisted entirely of slender grains, predominantly exhibited medium and bold kernels after dehusking, demonstrating a clear shift in shape classification. While in Cluster III, medium rice grains also shifted towards bold shape.

These results suggest that grain morphology, particularly shape and size alone, may overestimate kernel slenderness and length due to the influence of the husk. Consequently, kernel traits provide a more accurate representation of the true edible portion of the grain. Therefore, solely relying on grain characteristics may lead to misinterpretation of rice quality, highlighting the importance of evaluating both grain and kernel traits in rice characterization and breeding programs.

CONCLUSION

This study with a comprehensive characterization of 147 traditional rice accessions from Mon district, Nagaland, reveals diverse rice genetic resource shaped by traditional farming systems, local preferences and varying altitudes. Principal component analysis identified GL, GW, GR and GWt as the major traits contributing to variation, while cluster analysis grouped the germplasms into three distinct clusters based on these traits. A strong agreement between PCA and cluster results indicates that grain dimension traits are important factors in determining the diversity of rice germplasm in this region. Although traits such as long or slender grains are widely available as modern high-yielding varieties, the traditional landraces rice collection from Mon district represent locally adapted germplasm maintained by farmers over generations had similar characteristics. These landraces may harbor unique genetic variation associated with adaptation to upland and rainfed cultivation systems, making them valuable for conservation and as a potential resource in future rice breeding programs aimed at improving grain quality and adaptability. Overall, this study underscores the importance of conserving and utilizing landrace rice for genetic improvement strategies, ensuring food security, sustainability, and the preservation of agrobiodiversity in such traditional agroecosystems.

ACKNOWLEDGEMENTS

The authors are thankful to villagers and the students’ union of 24 villages for their kind assistance and participation in the data collection processes. Authors appreciate the technical support from Longang Luklem, Thaknei Wangsa, Ahat Konyak and Khampei Wangnao. The first author was supported by NFST fellowship (202122-NFST-NAG-00070), Ministry of Tribal Affair, Government of India.

AUTHOR CONTRIBUTIONS

Zenwang Konyak: Conceptualization (Supporting), Methodology (Equal), Investigation (Lead), Resources (Supporting), Data Curation (Lead), Software (Equal), Formal Analysis (Equal), Writing – Original Draft (Lead), Review & Editing (Equal), Visualization (Equal), Validation (Equal); Samadangla Ao: Conceptualization (Lead), Methodology (Equal), Resources (Lead), Formal Analysis (Equal), Writing – Original Draft (Supporting), Review & Editing (Equal), Software (Equal), Visualization (Equal), Validation (Equal), Supervision (Lead), Project Administration (Lead), Funding Acquisition (Lead).

CONFLICT OF INTEREST

The authors declare that they have no conflicts of interest.

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