Identifying quality protein maize inbred lines with enhanced seed vigour and longevity using multi-trait seed-quality selection

Abstract

Background

Quality protein maize is a biofortified food crop of significant importance for nutritionally vulnerable populations in low- and middle-income countries. However, poor seed storability and vigour of quality protein maize (QPM) inbred lines remain a major challenge for breeders and the seed industry, limiting the expansion of QPM hybrids. In the current context, it is imperative to evaluate not only yield, but also other equally significant seed quality traits, such as storability and vigour, which substantially affect the marketability and spread of any hybrid.

Results

In this study, 28 advanced QPM inbred lines were evaluated for pre- and post-storage seed viability and vigour using multiple seed quality parameters. The inbred lines exhibited high initial viability but varied in seed vigour and morphological traits. Natural ageing under ambient storage for 18 months led to a faster decline in vigour than in viability, increasing both the time to 50% germination and the mean germination time. Seed longevity, estimated as the half-life period (p₅₀) during dry ageing and as the percentage of normal seedlings after 5 days of accelerated wet ageing, showed significant variation among the inbred lines (p < 0.05). Seed morphological traits, except seed eccentricity, were not significantly associated with seed vigour or longevity. The multi-trait genotype–ideotype distance index (MGIDI) identified four superior inbred lines (MGU-QPM-16, MGU-QPM-47, MGU-QPM-22, and MGU-QPM-31(Opq)) with enhanced pre- and post-storage vigour and seed longevity under both dry and wet ageing conditions. Based on the PCA eigenvalues, the selected quality traits were grouped into three factors, highlighting the strengths and weaknesses of good storers. Among the superior lines, MGU-QPM-47 demonstrated the best longevity and post-storage vigour.

Conclusions

The study identified contrasting QPM inbred lines with superior and poor seed storability and vigour under both dry natural and wet accelerated ageing conditions. The high heritability of the traits included in the multi-trait index underscores the potential use of the identified good-storer QPM inbred lines in hybrid development and crossing programs to improve seed storability and vigour. The identified contrasting inbred lines can be used for developing mapping populations for seed storability and vigour.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12870-026-09345-5.

Background

Maize is considered the queen of cereals and is the third most important cereal crop after rice and wheat [1]. The major storage proteins in maize, prolamins, are deficient in two essential amino acids, lysine and tryptophan. The discovery of a mutant allele of the Opaque-2 (o2) gene at Purdue University, USA, which altered the amino acid profile by nearly doubling the lysine and tryptophan content in maize, was followed by the development of Quality Protein Maize (QPM) at CIMMYT, Mexico [2]. On average, lysine is about 4%, and tryptophan is about 0.8% in QPM cultivars, compared to 2% and 0.4% in non-QPM cultivars, respectively [3]. However, the pleiotropic effect of the opaque-2 mutant exhibited poor agronomic traits, including reduced yield and kernel characters, low dry matter accumulation, soft, chalky kernels, vulnerability to ear rot and stored-grain pests, and inferior food-processing qualities, thereby reducing its acceptance among farmers. Later, with the identification of O2 modifier lines, the endosperm quality of QPM grain was largely improved [4]. However, susceptibility to storage pests, physiological storability, and field emergence are still comparatively lower in QPM genotypes than in normal maize [5–7]. Seed producibility and storability play a critical role in the marketability of any variety.

In cross-pollinated crops such as maize, the development of inbred lines for hybrid production can lead to inbreeding depression, reducing seedling growth and vigour [8]. Seed vigour determines the performance of seed lots under a wide range of environmental conditions, including various stressful field conditions. It is a composite trait encompassing tolerance to ageing, viability, rapid germination, and the capacity for uniform seedling establishment under both optimal and stress-prone conditions [9]. Seed longevity, a key agronomic characteristic, is also essential for ensuring a high germination rate after an extended storage period [10]. These two seed traits are critical for crop performance, particularly in humid tropical regions where environmental conditions accelerate seed deterioration. The maintenance of seed viability and vigour during storage is influenced by several factors, including seed moisture content, relative humidity, the partial pressure of oxygen, and storage temperature [11, 12]. However, the rate of seed deterioration is species-specific and influenced by genotype, seed composition, and post-harvest handling practices [13–15]. Among major food crops, cereals are generally considered moderate storers, exhibiting only mild resilience to storage-induced ageing.

Seed deterioration begins over time, even before harvest, and eventually the seeds gradually lose their viability during storage [16]. Although germination loss is one of the leading indicators of deterioration, the consistency of germination percentage during storage does not imply the absence of deteriorative changes. Thus, seeds with the same high germination may perform differently under field conditions due to differences in vigour [17]. The loss of seed quality during storage initially manifests as a decline in the growth rate of the germinating axis (vigour), followed by a reduction in total germination (viability). The storage behaviour of seeds is studied by subjecting them to an ageing process. It includes both artificial ageing and natural ageing. Artificial ageing uses extreme temperature and humidity conditions to accelerate the ageing process. Natural ageing depends on the ambient temperature and humidity fluctuations to which the seeds are exposed during storage. The natural ageing process spans several months; thus, researchers test seed performance under artificial accelerated ageing by exposing seeds to high relative humidity (80–100% RH) and elevated temperature (35–45 °C). However, recent studies have indicated in-depth variation in deterioration mechanisms between these two ageing processes [18]. Therefore, increased resistance to deterioration under both conditions is more desirable for maintaining germinability and thereby increasing global food security.

In general, inbred development prioritises identifying an optimal cross combination for greater grain yield rather than seed quality. However, for future breeding programs, it is essential to consider not only yield but also other equally significant factors, such as seed vigour and longevity, which are vital for maintaining seed quality over extended periods [9, 19]. Efficient exploitation of QPM in hybrid breeding requires the development of inbred parents with acceptable agronomic performance and seed quality [3]. Identifying inbred lines with superior storability and vigour is crucial for effective parental line seed production and can help overcome annual production challenges and improve the quality of hybrid seeds.

In the present study, we assessed 28 elite QPM inbred lines for multiple seed quality parameters related to seed longevity and vigour before and after ageing to evaluate existing variation and heritability. Furthermore, using the multi-trait genotype-ideotype distance index (MGIDI), we have identified high-vigour, better-storing QPM inbred lines. These lines represent promising parental candidates for developing QPM hybrids with potentially enhanced seed storability and plant establishment.

Materials and methods

Plant material and experimental setup

All experiments were conducted on freshly harvested seeds of 28 distinct advanced QPM inbred lines, obtained from the Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi (Supplementary Table S1). In this study, three experiments were designed to determine the initial variation among inbred lines before storage and their vigour and longevity after storage.

Experiment 1. Initial seed quality and morphological traits: Seeds were dried to a moisture content of 12% on a fresh-weight basis and subsequently the seed morphological traits and initial viability (Total germination % and Normal seedling %) and vigour (root length, RL; shoot length, ShL; radicle emergence, RE; seed vigour index, SVI; and electrical conductivity, EC) were measured in all the 28 QPM inbred lines.

Experiment 2. Changes in seed vigour and viability traits during ambient storage: The initially dried seeds were subsequently stored in cotton cloth bags under ambient laboratory bench conditions, with an average temperature of 26 ± 2 °C and a relative humidity of 60 ± 5%. During ambient storage, a decline in the number of normal seedlings makes it difficult to estimate seedling growth parameters and the seed vigour index. The reduced sample size will limit the statistical robustness of the data and potentially increase the margin of error. Hence, we used the time-based vigour parameters, namely, time to 50% germination (t₅₀), mean germination time (MGT), and area under the cumulative germination curve (AUC), and vigour was measured at 6-month intervals up to 18 months of ambient storage.

Experiment 3. Seed longevity based on natural and accelerated ageing conditions: The seed longevity (storability) was measured both by estimating the seed half-life period (p₅) under dry natural ageing during ambient storage and by using a rapid wet ageing process (5 days of accelerated ageing) under high temperature and humidity.

After evaluating relationships among different seed quality traits before storage (experiment 1) and after storage (experiment 2 and 3), twelve seed quality traits were selected to explore genetic correlations and to identify superior inbred lines with better storability using a multi‑trait genotype–ideotype distance index.

Seed morphological traits

Seven important seed morphological traits, namely, seed area, axial length, axial width, eccentricity (deviation from perfect sphere), perimeter (total length of external boundary of seed), equivalent diameter (nominal diameter for irregularly shaped objects like seeds), and roundness (how closely the 2-D cross-section of a seed resembles perfect circle), were recorded for all the inbred lines using an MATLAB Grain Analyser software developed at the ICAR-Central Institute of Agricultural Engineering, Bhopal [20]. The traits were measured in two replications, with 50 seeds per replication. The extent of endosperm modification in the seeds of QPM inbred lines was assessed using the standard light box method [21].

Seed viability trait

The germination percentage was measured in four replications, with 40 seeds per replication, following the International Seed Testing Association (ISTA) germination test procedure [22] with minor modifications. Prior to the germination test, seeds were treated with the fungicide metalaxyl (C₁₅H₂₁NO₄) at 0.2 g per 100 g of seed to eliminate surface pathogens. Seeds were germinated by the between‑paper method, and after seven days, the total germination percentage (both normal and abnormal seedlings) and the percentage of normal seedlings were recorded. Normal seedlings, which have the potential to develop into satisfactory plants under favourable conditions, were identified according to the criteria outlined in the ISTA Seedling Evaluation Manual [23].

Seed vigour traits

Before storage, we measured the seed vigour parameters, RL, ShL, RE, SVI, and EC. The methods for measuring these parameters are described in detail below.

Root and shoot length (RL & ShL)

Seedling growth was assessed by measuring root and shoot lengths after seven days of germination. Measurements were taken manually with a ruler on three replicates, each consisting of ten randomly selected normal seedlings.

Radicle emergence (RE)

The percentage of radicle emergence was determined according to the ISTA rules [22] with minor modifications. Two replicates of 50 seeds each were treated with the fungicide metalaxyl (C₁₅H₂1NO₄) at 0.2 g per 100 g of seed, then placed between two moistened paper towels. The rolled paper towels were kept upright at 20 °C in germination trays with distilled water at the bottom. Seeds with a radicle length of ≥ 2 mm were counted after 66 h of incubation, and the percentage of radicle emergence was calculated.

Seed vigour index (SVI)

The vigour index was calculated in four replications by multiplying the percentage of normal seedlings by the mean seedling dry weight estimated after drying ten randomly selected normal seedlings per replication at 80 ℃ for 24 h.

Electrical conductivity (EC)

Seed leachate conductivity was measured according to the method of PK Agrawal and M Dadlani [24], with slight modifications. Ten untreated seeds were soaked in 10 mL of double-distilled water at 25 °C for 3 h, in four replicates, to obtain seed leachate. Conductivity was measured with a conductivity meter (Eutech, PC 2700) and expressed as µS cm^{− 1} g^{− 1}.

During ambient storage, the seed vigour parameters, namely, t₅₀, MGT, and AUC were measured at 6-month intervals up to 18 months. The methodologies used to assess these vigour parameters are presented below.

Time to 50% germination (t₅₀)

The time required for 50% of the total seeds to germinate is denoted as t₅₀ and is expressed in hours [25].

WhereNrepresents the final number of seeds germinated,_iand_jare the total numbers of seeds germinated in adjacent counts at times andT_j, respectively, when N_i< < N_j.

Mean germination time (MGT)

The average time (h) required to reach maximum germination is measured as follows [26].

Where N_i is the number of seeds germinated corresponding to the ith interval, and T_i is the time in hours from the start of the experiment at the ith interval. k is the total number of time intervals.

Area under the curve (AUC)

The cumulative germination curve was generated by fitting daily radicle emergence (≥ 2 mm) data to the four‑parameter Hill function described by YA El-Kassaby, I Moss, D Kolotelo and M Stoehr [27], and the area under the fitted curve up to 144 h after imbibition was taken as the AUC value.

Seed longevity traits

Seed half-life period (p₅₀)

The seed half-life, denoted as the time required for seed viability to decline to 50%, is a reliable measure of seed longevity and is expressed in days [28].

Where is the viability (total germination %) expressed as normal equivalent deviates (NED) of seeds after p days in storage; K_i is the initial viability (in NED), and σ is the time for viability to decline by 1 NED.

Accelerated ageing test (AAT5D)

Seeds were placed in a single layer in a desiccator containing 200 mL of distilled water and incubated at 40 ± 1 °C for five days. At the end of the test, the percentage of normal seedlings was recorded.

Data analysis

To understand the relationships among seed viability, vigour and longevity parameters and their association with inbred lines, we conducted Pearson Correlation and Principal Component Analysis (PCA).

The estimation of MGIDI values for QPM inbred lines was based on two-way Best Linear Unbiased Predictions (BLUPs) for each inbred line (row) and parameter (column). The process was carried out in four steps: (i) defining the ideal condition, (ii) rescaling the studied parameters, (iii) performing exploratory factor analysis to reduce dimensionality, and (iv) calculating the Euclidean distance between the inbred lines and the ideotype, which was used to construct the MGIDI index [29].

Defining an ideal condition

The ideal condition is defined by assigning desired values to all studied traits. Based on the traits evaluated before and after storage, inbred lines with high germination and vigour are preferred. Traits for which shorter durations (t₅₀, MGT) or lower values (EC, eccentricity) are advantageous, are considered negative traits, and minimal values for these are desirable.

Rescaled means

The trait values of seeds within replicates, wherever applicable, were averaged to avoid pseudo-replication. According to Olivoto et al. [30], the re-scaling of_ij to obtain rX_ij was performed based on the knowledge of an ideal treatment.

Here η_nj and φ_nj are the new maximum and minimum values, respectively, for the trait j after rescaling; η_oj and φ_oj are the original maximum and minimum values for the trait j, and θ_ij is the original value of the trait j for treatment i. For traits where higher values are desirable, viz., NS_0M, RE_0M, ShL_0M, RL_0M, SVI_0M, p₅₀, AA5d, TG_18M, NS_18M, AUC_18M, we set η_nj = 100 and φ_nj = 0. For all the other traits, where lower values are desirable, we set η_nj = 0 and φ_nj = 100. In the rescaled two-way table r_ij), each column ranges from 0 to 100, with 100 representing the most desirable value. Thus, the ideal treatment would score 100 for every trait after rescaling.

Factor analysis

The factorial scores for each QPM inbred line were estimated by performing an exploratory factor analysis with rescaled values (rX_ij), which grouped correlated traits into “factors”. The initial loadings were derived from traits associated with eigenvalues greater than one, obtained from the correlation matrix of rX_ij. Then, final loadings were estimated by using the varimax rotation criterion [30].

Multi-trait genotype-ideotype distance index

The ideotype was designed under the assumption that it would possess the highest rescaled value, i.e., 100 for all the analysed traits. The Euclidean distance between the various trait scores of inbred lines and the ideotype was computed as follows,

where MGIDI_i is the multi-trait genotype-ideotype distance index for the ith treatment; γ_ij is the score of the ith inbred line (row) in the jth factor (i = 1, 2,…, g; j = 1, 2,…, f) and γ_j is the jth score of the ideotype. The inbred lines with the lowest MGIDI values, i.e., inbred lines closer to the ideotype, exhibited the desired values for all the traits studied.

The strengths and weaknesses of an inbred line were represented by the proportion of the MGIDI index of the ith inbred line explained by the jth factor as described by T Olivoto, MI Diel, D Schmidt and AD Lucio [30]. A low contribution of a factor indicates that the traits within that factor are close to the designed ideotype.

Statistical software

Descriptive statistics and analysis of variance (ANOVA) followed by mean comparison using Tukey’s HSD were performed in Minitab v.21. Pearson correlations between longevity-related traits, seed morphological traits, and initial physiological quality traits were calculated, and graphs were generated in OriginPro v.2023b. The principal component analysis was done using the factoextra package in R (v. 4.4.1). The genetic correlations and multi‑trait genotype‑ideotype distance index (MGIDI) were computed using the metan package in R (v. 4.4.1). The area under the cumulative germination curve, t₅₀, and MGT were calculated in R (v. 4.4.1) using the germinationmetrics package (v. 0.1.7.9000) [31].

Results

Initial seed quality and seed morphological traits

The initial viability, measured as the percentage of normal seedlings, exceeded 80% (the Indian minimum seed standard) in all QPM inbred lines except PMIQ-3 (78.6%) and MGU-QPM-41 (76%). The mean viability across the inbred lines was 93%, despite inter-genotypic variability and significant differences among them. Overall, this indicates the high initial viability of the studied inbred lines. The seedling growth parameters, namely shoot length (ShL) and root length (RL), of normal seedlings showed little variation among the initial traits studied. In contrast, the vigour parameters, viz., radicle emergence (RE), seed vigour index (SVI) and electrical conductivity (EC) exhibited considerable variation among the inbred lines, highlighting differences in vigour despite their uniformly high initial viability (Fig. 1). The maximum ShL was observed in VQL-1 (19.8 cm), RL in MGU-QPM-32 (26.2 cm), RE in MGU-QPM-16 (96%), SVI in MGU-QPM-29 (87.9) and the lowest EC in MGU-QPM-14 (15.3 µS cm^− 1g^− 1) (Supplementary Table S2). This shows the diversity in vigour parameters among the studied inbred lines.

Fig. 1.

Distribution of initial seed quality traits among the 28 QPM inbred lines and the significance of the existing variation measured through ANOVA was depicted as F value and p value

The seed morphological traits obtained from spatial profiles through image analysis showed significant variation among inbred lines (p ≤ 0.001; Table 1). Seed area showed greater variation and dispersion than other morphological traits. Among the inbred lines, MGU-QPM-30 recorded the maximum seed area (111.21 mm²), perimeter (43.59 mm) and equivalent diameter (11.88 mm). The highest axial length and width were observed in MGU-QPM-29 (11.88 mm and 10.44 mm), followed closely by MGU-QPM-30 (11.11 mm & 10.42 mm), which were statistically at par. In contrast, the minimum seed area (62.27 mm²), perimeter (30.86 mm), equivalent diameter (8.89 mm) and width (8.19 mm) were observed in the MGU-QPM-31 (Mod) inbred line (Supplementary Table S3). The opaqueness of seeds was studied using the lightbox method to confirm endosperm quality in the QPM inbred lines. The majority of inbred lines (19) exhibited 50% opaqueness, followed by 25% opaqueness in 8 lines, while only one inbred line fell into the 75% opaqueness category. This indicates that the homozygous QPM lines exhibited the desired opacity without affecting genotypic variability in seed storability.

Table 1.

Mean sum of squares of seed morphological traits of QPM inbred lines

Source	df	SA	S_Eccen	SP	SR	SED	SL	SW
Genotype	27	221.85***	0.009***	13.52***	0.005**	0.85***	0.90***	0.65***
Error	28	10.31	0.002	1.55	0.001	0.04	0.22	0.05

df degrees of freedom, SA seed area (mm²), S_Eccen seed eccentricity, SP seed perimeter (mm), SR Seed Roundness, SED seed equivalent diameter (mm), SL seed length (mm), SW seed width (mm)

^***P ≤ 0.001; ^**P ≤ 0.01

Ambient seed storage

The average total germination of the QPM inbred lines declined progressively over 18 months of storage, during which temperatures fluctuated between 14 ℃ and 36 ℃ and relative humidity ranged from 35% to 79%. The initial total germination showed significant differences among inbred lines (Table 2).

Table 2.

Mean sum of squares for seed quality traits during 0, 6, 12, and 18 months of ambient storage of QPM inbred lines

Storage Period	Source of variance	df	Total germination (%)	Normal seedlings (%)	t50 (h)	MGT (h)	AUC
0 Months	Genotype	27	0.105***	0.27***	7.19ns	9.03ns	80.31***
	Error	28	0.005	0.03	4.46	5.20	8.98
6 Months	Genotype	27	174.83***	210.62***	80.41***	75.82***	109.09***
	Error	28	28.11	28.65	4.77	5.42	12.53
12 Months	Genotype	27	359.12***	412.07***	422.80***	365.55***	909.57***
	Error	28	26.34	42.54	23.39	18.97	33.72
18 Months	Genotype	27	467.82***	422.45***	1062.26***	998.77***	889.87***
	Error	28	6.67	27.71	62.03	51.25	26.92

The germination and normal seedlings percentage values were analysed after square root or arcsine transformation as per the data

ns non-significant, df degrees of freedom, t₅₀ time to reach 50% germination in hours, MGTmean germination time in hours, AUC area under the cumulative germination curve

^***P ≤ 0.001

However, except for four inbred lines, viz., PMIQ-3 (90.4%), MGU-QPM-39 (89.7%), MGU-QPM-40 (89.6%), and MGU-QPM-41 (82%), it was at par in the remaining 24 QPM inbred lines at zero months of storage. Further, there was no significant decline in the mean germination capacity of the inbred lines during the initial six months of storage (Fig. 2A). Conversely, as the storage period progressed, the inbred lines began to show significant (p ≤ 0.001) variation in total germination. The mean viability of the inbred lines declined by 24% and 62% at 12 and 18 months of ambient storage, respectively. After 18 months of ambient storage, the total germination declined to less than 10% in MGU-QPM-39 and PMIQ-3 inbred lines. In contrast, it was above 75% in MGU-QPM-16, MGU-QPM-22 and MGU-QPM-47, with a confidence interval of 70% to > 80% (Supplementary Table S4). Of the total seeds germinated, the normal seedlings, which have a better chance of establishment under the field conditions, varied among the inbred lines, even at the initiation of storage, ranging from 76% to 100% (Supplementary Table S2). Further, with the increase in the storage period, a significant decline in normal seedling percentage across diverse inbred lines was observed (Fig. 2B). Up to 12 months of storage, all the genotypes possessed ≥ 10% of normal seedlings, and 18 genotypes had ≥ 50% normal seedlings. However, after 18 months, 9 genotypes have ≤ 10% normal seedlings, and only 4 genotypes have ≥ 50% normal seedlings. At the end of 18 months of storage, the normal seedling percentage (NS_18M) ranged from a minimum of 0% (PMIQ-3) to a maximum of 66% (MGU-QPM-22) (Supplementary Table S5).

Fig. 2.

Changes in total germination (A), normal seedlings (B), time to reach 50% germination (C), mean germination time (D) and area under the cumulative germination curve (E) at different months of ambient storage. The mean values of storage periods are compared using analysis of variance and are marked with small case alphabets for each seed quality parameter. Storage periods with the same alphabet have no significant difference, and those with different alphabets were significantly distinct from one another for each parameter

Along with viability, seed vigour decreased during storage, with a significant (p < 0.001) increase in time to reach 50% germination (t₅₀) and the mean germination time (MGT). The t₅₀ and MGT were prolonged to 75 h and 74 h, respectively, from an initial ~ 14 h, with a > 5-fold increase in duration after 18 months of ambient storage (Fig. 2C and D). The difference between the maximum and minimum values (range) among inbred lines for t₅₀ and MGT was extended from the initial 5.5–6 h to 25 h, 48–55 h, and 91 h after 6, 12, and 18 months of storage, respectively (Supplementary Table S6). This indicates greater variation in seed vigour among inbred lines as the storage period increases. The decline in both total germination and the rate of germination has led to a sharp reduction in the area under the cumulative germination curve (AUC) during storage (Fig. 2E). A 77% decline in AUC was observed over 18 months of storage. Further, a substantial increase in the dispersion of AUC values across inbred lines with storage was observed, with the standard deviation increasing from 6 to 21 over 18 months (Supplementary Table S6). Thus, both viability and vigour of the QPM inbred lines declined sharply over 18 months of ambient storage, with progressively greater variability among inbred lines as the storage period extended.

Seed longevity

The half-life period of seeds (p₅₀), which denotes the time to a 50% loss of viability, is a reliable measure of seed longevity. A highly significant (p ≤ 0.001) variation among inbred lines was observed for p₅₀ measured under ambient storage conditions (Fig. 3). The inbred line MGU-QPM-16 exhibited the longest predicted time to reachp₅₀ (826.5 days), within a 95% confidence interval of 747 to 906 days. Meanwhile, PMIQ-3 took the shortest time to lose 50% viability (286.5 days), within a 95% confidence interval of 207 to 366 days (Supplementary Table S7).

Fig. 3.

Variation in the seed longevity of QPM inbreds measured as days required to reach 50% germination (p₅₀) and per cent normal seedlings obtained after accelerated ageing for 5 days at 40 ℃ and 100% RH (AA5d). The significance of the measured variation using ANOVA was depicted as F value and p value

The storability measured over five days of accelerated ageing at 40℃ and 100% RH also showed significant (p ≤ 0.001) variability among inbred lines (Fig. 3). After ageing, the normal seedling percentage ranged from 30% to 82%, with a mean of 61%. Among the inbred lines, MUG-QPM-20 performed well with a maximum mean value with a 95% confidence interval of 75.3 to 88.6%, followed by MGU-QPM-16, 22 and 31 (Mod) with 78% mean normal seedling percentage. In contrast, MGU-QM-23 recorded the lowest normal seedling percentage (30%) with a 95% confidence interval of 23.3 to 36.6%, followed by PMIQ-3 and VQL-1 with 32% of mean normal seedling percentage (Supplementary Table S7).

Association between different traits

Pearson’s correlation was performed to find the association of longevity traits with seed morphological and initial physiological quality traits (Fig. 4). A significant strong positive correlation was observed between p₅₀ and viability parameters at 18 months of storage while a significant negative correlation with germination time-based vigour parameters viz., MGT (r = -0.48, p < 0.001) and t₅₀ (r = -0.44, p < 0.001). Meanwhile, the accelerated ageing for 5 days had a non-significant, mild positive relationship with initial viability (TG_0M and NS_0M). However, it showed a significant but weak-to-moderate correlation with the viability and vigour parameters of stored seed, confirming differences in the association of longevity-measuring parameters p₅₀ and AA5d. The longevity under natural (p₅₀) and accelerated ageing (AA5d) conditions had a significant, mild positive association (r = 0.38, p < 0.05). None of the seed morphological traits, except seed eccentricity, showed a significant relationship with longevity or with initial or ambient stored seed viability and vigour traits. Therefore, except for seed eccentricity, further factor analysis did not include other morphological traits.

Fig. 4.

Pearson correlation coefficients of seed morphological, initial quality, longevity and seed quality traits after 18 months of ambient storage

Principal component analysis (PCA) was conducted to assess the effects of storage and the relationships among morpho-physiological traits. The first two principal components (PC) accounted for 61.5% of the total variation, of which PC1 contributed 46.3% and PC2 15.2% (Supplementary Tables S8 & S9). The first component emphasises the significance of viability and vigour traits after 18 months of ambient storage, viz. AUC_18M (loading of 0.891), NS_18M (0.885), TG_18M (0.884), MGT_18M (-0.778) and t₅₀_18M (-0.761) along with longevity trait p₅₀ (0.846). The second component included traits related to the vigour of the initial seed lots prior to storage, viz. EC (0.611) and SVI (-0.770), and the lone morphological trait, seed eccentricity (0.655). The radicle emergence at zero months of storage (0.774) and normal seedlings after 5 days of accelerated ageing (0.685) are highlighted in the third component. Subsequent components elucidate additional variations associated with several characteristics that exhibit lower factor loadings. The genotypes in the upper right quadrant of the PCA-biplot have better storability and higher initial vigour (Fig. 5). Further, factor analysis was performed, grouping all 12 parameters into three factors (FA), as the three principal components have more than 1 eigenvalue. The FA 1 consists of viability and vigour traits after 18 months of storage (TG_18M, NS_18M, AUC_18M, t₅₀_18M, MGT_18M) and longevity parameter p₅₀. The initial viability and vigour traits were distributed between two factors. The FA2 consists of initial germination (NS_0M), indirect vigour parameters (SVI_0M, EC_0M) and seed eccentricity (S_Eccen). Meanwhile, pre-storage direct vigour and storability parameters (RE_0M and AA5d) were grouped into FA3. After the varimax rotation, the mean communality (h) was 0.75 (NS_0M 0.43 ≤ h ≤ AUC_18M 0.95), indicating a high proportion of each variable’s variance (except NS_0M and EC_0M) was explained by the factors (Table 3).

Fig. 5.

PCA Biplot of twelve seed quality parameters in 28 QPM inbred lines, showing trait associations and inbred line distribution

Table 3.

Eigenvalues, explained variance, and factorial loadings after varimax rotation in factor analysis

Variable	FA1	FA2	FA3	Communality (h)	Uniqueness
NS_0M	-0.36	-0.52	0.19	0.43	0.57
RE_0M	-0.04	-0.22	0.87	0.82	0.18
SVI_0M	-0.11	-0.89	0.24	0.87	0.13
P50_AS	-0.83	-0.3	0.07	0.79	0.21
AA5d_NS	-0.22	-0.02	0.82	0.73	0.27
TG_18M	-0.94	-0.2	0.04	0.92	0.08
NS_18M	-0.92	-0.15	0.13	0.89	0.11
AUC_18M	-0.96	-0.12	0.07	0.95	0.05
t50_18M	-0.68	-0.02	0.48	0.69	0.31
MGT_18M	-0.68	-0.05	0.49	0.71	0.29
S_Eccen	-0.1	-0.74	-0.25	0.63	0.37
EC_0M	-0.11	-0.72	0.17	0.56	0.44
Eigenvalues	5.37	2.31	1.79	-	-
Variance (%)	46.32	15.22	13.22	-	-
Cumulative (%)	46.32	61.54	74.76	-	-

NS_0M Pre-storage Normal seedling (%), RE_0M Pre-storage radicle emergence (%), SVI_0M Pre-storage Seed vigour index, p₅₀_AS Time period to reach 50% of initial germination during ambient storage, AA5d_NS Normal seedling (%) after five days of accelerated ageing, TG_18M Total germination after 18 months of ambient storage, NS_18M Normal seedling (%) after 18 months of ambient storage, AUC_18M Area under the cumulative germination curve after 18 months of ambient storage,t₅₀_18M Time to reach 50% germination after 18 months of ambient storage, MGT_18M Mean germination time after 18 months of ambient storage, S_Eccen Seed eccentricity, EC_0M Electrical conductivity of seeds before storage

Variance components and genetic correlations

Highly significant (p ≤ 0.001) genotype effects were observed for all the traits. The contribution of genotypic variance to phenotypic variance was highest in RE_0M (97.83%) and lowest in S_Eccen (63.62%). All traits, except NS_0M and S_Eccen, showed > 80% genotypic contribution to their phenotypic variance. The broad-sense heritability on a genotype mean basis (h²_mg) ranged from 0.78 (S_Eccen) to 0.99 (RE_0M). High values of heritability (h² > 0.8) were observed for RE_0M, SVI_0M, p₅₀, AA5d, TG_18M, NS_18M, AUC_18M, t₅₀_18M, MGT_18M and EC_0M (Table 4). The phenotypic correlations are close to the genotype correlations due to high heritability, and all traits show similar relationships in both sets of correlations (Supplementary Fig. S1). Negative correlations were observed with t₅₀_18M, MGT_18M, EC_0M, and S_Eccen, where lower values indicate better quality.

Table 4.

Genetic parameters of seed quality traits used to differentiate good and poor storers among various QPM inbred lines

Seed quality trait	Gen_var (%)	Res_var (%)	Phen_var	h2mg	CVg	CVr	CV ratio	p-value
NS_0M	78.72	21.28	54.43	0.88	7.05	3.66	1.92	3.23E-07
RE_0M	97.83	2.17	337.53	0.99	25.74	3.83	6.72	2.9E-20
SVI_0M	91.27	8.73	154.13	0.95	19.11	5.91	3.23	3.6E-12
P50_AS	82.52	17.48	17103.36	0.90	23.66	10.89	2.17	2.8E-08
AA5d_NS	90.35	9.65	226.24	0.95	23.35	7.63	3.06	1.34E-11
TG_18M	97.03	2.97	580.60	0.98	60.75	10.62	5.72	2.01E-18
NS_18M	91.85	8.15	400.16	0.96	73.53	21.91	3.36	1.47E-12
AUC_18M	94.09	5.91	458.47	0.97	72.50	18.16	3.99	2.05E-14
t50_18M	88.77	11.23	562.73	0.94	29.69	10.56	2.81	9.7E-11
MGT_18M	90.11	9.89	525.36	0.95	29.37	9.73	3.02	1.84E-11
S_Eccen	63.62	36.38	0.01	0.78	10.06	7.61	1.32	0.000182
EC_0M	96.76	3.24	440.01	0.98	49.25	9.01	5.46	6.67E-18

Gen_var (%) per cent contribution of genotypic variance to phenotypic variance, Res_var (%) per cent contribution of residual variance to phenotypic variance, Phen_var phenotypic variance, h²mg heritability on the entry-mean basis, CVg genotypic coefficient of variation, CVr residual coefficient of variation CV ratio ratio between genotypic and residual coefficient of variation

NS_0M Pre-storage Normal seedling (%), RE_0M Pre-storage radicle emergence (%), SVI_0M Pre-storage Seed vigour index, p₅₀_AS Time period to reach 50% of initial germination during ambient storage, AA5d_NS Normal seedling (%) after five days of accelerated ageing, TG_18M Total germination after 18 months of ambient storage, NS_18M Normal seedling (%) after 18 months of ambient storage, AUC_18M Area under the cumulative germination curve after 18 months of ambient storage, t₅₀_18M Time to reach 50% germination after 18 months of ambient storage, MGT_18M Mean germination time after 18 months of ambient storage, S_Eccen Seed eccentricity, EC_0M Electrical conductivity of seeds before storage

Identification of QPM inbred lines for storability

The multi-trait genotype-ideotype distance index (MGIDI) using the 12 traits with a 15% selection index could identify four genotypes, MGU-QPM-16, MGU-QPM-47, MGU-QPM-22, and MGU-QPM-31(Opq), as good storers (Fig. 6a). Of the four, the MGU-QPM-31 (Opq) is just on the cutoff line, while the remaining three have higher desired values. Evaluation of MGIDI demonstrated that the desired selection gain (SG) across all 12 traits of interest, i.e., positive SG for NS_0M, SVI_0M, RE_0M, p₅₀, AA5d, TG_18M, NS_18M, and AUC_18M and negative gains for the time-based vigour traits (t₅₀_18M, MGT_18M), electrical conductivity (EC_0M) and seed eccentricity (S_Eccen). The total selection gain was 397% in the selected inbred lines compared to the original population, with 332.15% for traits that were targeted for increase and − 41.74% for traits targeted for decrease (Table 5). The maximum selection differential was observed for NS_18M (121%), followed by TG_18M (84.3%) and AUC_18M (82.7%). Meanwhile, the minimum selection differential was noticed for seed eccentricity (1.68%) (Supplementary Fig. S2). The negative sign of the selection differential for t₅₀_18M, MGT_18M, EC_0M, and S_Eccen is ignored, as these are negative desired traits for which lower values are preferable.

Fig. 6.

Selection of good storers using MGIDI analysis (a) and strengths and weaknesses of the selected good storer QPM inbred lines (b)

Table 5.

Selection gains for the mean performance of 28 QPM inbreds based on MGIDI values

Variable	Factor	sense	goal	Mean performance				SG	SG%
				Xo	Xs	SD	SD%
P50_AS	FA1	increase	100	502	630	128	25.5	116	23
TG_18M	FA1	increase	100	39.1	72	32.9	84.3	32.4	83
NS_18M	FA1	increase	100	26.1	57.6	31.5	121	30.2	116
AUC_18M	FA1	increase	100	28.6	52.3	23.7	82.7	23	80.2
t50_18M	FA1	decrease	100	75.3	69.8	-5.49	-7.29	-5.16	-6.86
MGT_18M	FA1	decrease	100	74.1	67.8	-6.31	-8.52	-5.98	-8.07
NS_0M	FA2	increase	100	92.9	98.7	5.85	6.3	5.15	5.55
SVI_0M	FA2	increase	100	62.1	69.7	7.69	12.4	7.34	11.8
S_Eccen	FA2	decrease	100	0.597	0.587	-0.0101	-1.68	-0.0078	-1.31
EC_0M	FA2	decrease	100	41.9	31	-10.9	-25.9	-10.7	-25.5
RE_0M	FA3	increase	100	70.6	87.3	16.7	23.7	16.5	23.4
AA5d_NS	FA3	increase	100	61.2	69.1	7.85	12.8	7.45	12.2
Total (Increase)									332.15
Total (Decrease)									-41.74

FA1 factor 1, FA2 factor 2, FA3 factor 3, FA4 factor 4, Xo mean of the original population, Xs mean of the selected inbreds, SD selection differential, SD% percent selection differential, SG selection gain, SG% percent selection gain

The radar plot (Fig. 6b) depicts the strengths and weaknesses of selected inbred lines. The contribution of each factor to the MGIDI for each selected inbred line is ranked in descending order of influence, with the most influential factor located closest to the plot centre. Traits exhibiting smaller proportions, i.e. positioned closer to the periphery, display greater similarity to the ideotype. The inbred MGU-QPM-47 has the smallest contribution by FA1. This indicates that the viability and vigour after 18 months of storage, and the p₅₀, were maximum for this genotype. The negligible contribution of FA2 for MGU-QPM-31(Opq) suggests that this genotype has high initial germination, seedling growth and seed eccentricity. In contrast, MGU-QPM 16 and MGU-QPM-31(Opq) had maximum strengths for FA3, consisting of high initial vigour in terms of radicle emergence (RE_0M) and per cent normal seedlings after 5 days of accelerated ageing (AA5d).

Along with the good storers, the MGIDI was used to identify poor-storer inbred lines by reversing the sense of the variables, selecting for low viability and vigour at the initial and after 18 months of storage, and for low p₅₀ and AA5d. This resulted in the identification of four poor storer inbred lines, viz., PMIQ-3, MGU-QPM-39, MGU-QPM-41 and PMIQ-1 (Fig. 7). The inbred PMIQ-1 is close to the cut point among the four inbred lines.

Fig. 7.

Selection of poor storers using MGIDI analysis

A heat map in Fig. 8 illustrates the distinctions in viability between identified good and poor storers under initial (NS_0M) and aged conditions (TG_18M, NS_18M). Positive vigour parameters (RE_0M, SVI_0M, AUC_18M) exhibited higher values in superior storage genotypes, while negative parameters (EC_0M, t₅₀_18M, MGT_18M) showed lower values, thereby differentiating good and poor storage performance. Seed longevity under dry (p₅₀) and wet (AA5d) ageing conditions showed significantly higher values for seeds with high storability than for those with low storability. Morphological traits, excluding seed eccentricity, proved ineffective in distinguishing between the seed storage categories.

Fig. 8.

Heatmap visualization of seed morphological traits and pre- and post-storage seed quality parameters for vigour and longevity was categorized according to good and poor storers identified through MGIDI

Discussion

The study focused on identifying QPM inbred lines with superior seed longevity by evaluating multiple viability and vigour traits during both pre- and post-storage stages, using a set of 28 promising inbred lines developed by the Maize Genetics Unit of the Indian Agricultural Research Institute. In general, maize inbred lines tend to exhibit reduced vigour due to inbreeding depression [32], and this is more pronounced in QPM inbred lines because of their poor storability. In the present study, all genotypes had high initial viability, with 64% showing 100% total germination and an overall mean of 93% of normal seedlings. However, they had a considerable variation in their vigour parameters (Fig. 1). Even though seed viability is a fundamental quality trait, it is a poor predictor of the seed lot’s performance under field conditions. The performance potential of viable seeds is better described by seed vigour, and seeds of different cultivars with the same initial viability can vary in vigour [9].

Changes in viability and vigour during ambient storage

Seed viability and vigour decline over time during storage. Bulk storage of high-volume seeds, such as maize, is not economically feasible under controlled conditions and is generally done under ambient conditions. Fluctuating temperatures and relative humidity under ambient conditions favour faster deterioration [13]. Although total germination has not significantly declined after 6 months of storage, the normal seedling percentage has decreased substantially. Simultaneously, a sharp reduction in the area under the cumulative germination curve (AUC) was observed at the end of six months of storage. The loss of vigour always precedes the loss of germination [33], and AUC is a better indicator of seed vigour because it accounts for both germination rate and final germination. A 77% reduction in the AUC was observed after 18 months of storage compared to the initial condition. This can be attributed to a 60 h delay in germination time (t₅₀ and MGT) and a 62% reduction in total germination (Fig. 2). The enhanced germination time with a prolonged storage period was a consistent observation across multiple species, including maize [34–36]. The increase in seed germination time might be due to the extra time required to repair ageing-associated damage during imbibition [37].

Seed longevity under different ageing situations

The assessment of seed longevity or storability employs diverse techniques. Accelerated ageing is a frequently utilised method to assess longevity across various species [38–42]. Better germination in terms of NS after accelerated ageing indicates better longevity. We observed a 52% variation in normal seedlings, ranging from 30% to 82%, after five days of accelerated ageing (AA5d) (Supplementary Table S7). Even though accelerated ageing is a rapid assessment technique, several studies indicated that its mechanism of ageing differs from that of natural ageing [10, 43–45]. The seed ageing environment (wet or dry) significantly affects the outcome of genetic and related studies on seed longevity [46, 47]. Natural ageing is more relevant when considering large-scale warehouse or small-scale farm storage, where temperature and RH conditions fluctuate during storage. The storage period after which 50% of seeds would germinate, p₅₀, is a more reliable estimation under different storage conditions [48]. In the present study, the p₅₀ estimated under natural ageing conditions showed significant variation among genotypes (Fig. 3). A 65% difference in p₅₀ was observed between the poor (286.5 days) and good (826.5 days) storer genotypes. Thus, in the present study, the QPM inbred lines were evaluated under both wet and dry ageing conditions to identify those with contrasting storability. Since the seeds of all inbred lines were produced under similar maternal environments and had high initial germination, the variation in longevity among inbred lines can be attributed to genotypic variance, which is heritable. In the present study, a high per cent contribution of genotypic variance to the phenotypic variance of p₅₀ (82.52%) and AA5d (90.35%) was observed, with broad-sense heritability exceeding 0.9 (Table 4). The initial seed viability of a species positively impacts its seed longevity under similar storage conditions [49]. However, seed longevity exhibits genotypic differences within species [38, 50]. We observed significant variation in the response of individual inbred lines to seed longevity measurements p₅₀ and AA5d (Supplementary Table S7). Further, we found a significant positive correlation of initial viability (TG_0M and NS_0M) with p₅₀ (r = 0.40 and 0.41, p < 0.01), but not with AA5d. This could be attributed to the differences in ageing mechanisms under dry and humid conditions [51].

Association studies of seed quality and morphological traits

In this study, the seed morphological traits, except seed eccentricity, showed no significant correlation with pre- and post-storage seed viability or longevity traits (p₅₀ and AA5d) (Fig. 3). Several other studies corroborated these findings, indicating that morphological traits such as seed size, shape, and mass are not correlated with seed vigour and longevity [52, 53]. The PCA and factor analysis of the 12 selected traits grouped the 28 QPM inbred lines into four quadrants of the biplot (Fig. 4). The genotypes in the first quadrant have high loadings for negative vigour traits, viz., t₅₀_18M, MGT_18M, EC_0M, and S_Eccen. Meanwhile, those in the fourth quadrant have high loading values for seed longevity and viability after 18 months of storage. This confirms the variation among the QPM inbred lines for various traits and the importance of all the selected traits in identifying good and poor storer inbred lines. The current findings align with previous investigations on diverse crops that employed PCA scatterplots to categorise genotypes based on longevity and vigour traits [38, 54].

Genetic parameters and selection response of evaluated traits

Both genetic and environmental factors influence phenotypic variance. The use of a particular trait for breeding purposes is regulated by the contribution of genotypic variance to phenotypic variance. In the present study, the selected traits are 78% to 99% heritable (Table 4). This outcome is attributable to the minimal environmental variability and highly favourable conditions maintained during the laboratory tests [55]. The high heritability indicates the scope for identifying good storer QPM inbred lines and their use in hybrid development. The selected traits include those targeted for enhancement (p₅₀, G_18M, NS_18M, AUC_18M, NS_0M, SVI_0M, RE_0M, AA5d) and reduction (t₅₀_18M, MGT_18M, S_Eccen, EC_0M) and none of these traits have shown any undesired selection gain (Table 5). The maximum selection gain was observed for NS_18M (116%), suggesting more than double the enhancement in normal seedlings after 18 months of storage with the selected genotypes. On the other hand, high initial germination in all the QPM inbred lines led to a minimal selection gain (5.5%) for the percentage of normal seedlings before storage (NS_0M). The percentage of normal seedlings after storage is a better indicator of longevity, as the abnormal seedlings will increase before the seeds lose their viability entirely [56].

Identification of good and poor storer QPM inbred lines

The MGIDI is a versatile and robust method for choosing genotypes based on multiple traits of interest [30]. Successful application of the MGIDI method is evident in several studies focused on improving crop performance, quality, and adaptability. MGIDI enables flexible selection criteria and helps in viewing the strengths and weaknesses of each genotype [57]. In this study, the MGIDI was employed to identify the good storer QPM inbred lines by taking all the 12 traits consisting of seed morphology (S_Eccen), pre (0 M) and post-storage (18 M) viability (NS_0M, TG_18M, NS_18M) and vigour (SVI_0M, RE_0M, EC_0M, AUC_18M, t₅₀_18M, MGT_18M), and longevity estimated under dry (p₅₀) and wet (AA5d) ageing conditions. The radar plot illustrated the strengths and weaknesses of each selected genotype. Among the identified good storers, the QPM inbred MGU-QPM-47 exhibits the lowest contribution from factor FA1, indicating extended viability after 18 months of storage and a superior p₅₀ value. However, FA1 also consists of t₅₀_18M and MGT_18M; an increase in these negative traits results in slower germination. The inbred MGU-QPM-16 had a comparatively moderate contribution of FA1 (Fig. 6b); however, it was the most preferred genotype (Fig. 6a) due to the least contribution of FA3, indicating higher initial vigour and a higher normal seedling percentage after 5 days of accelerated ageing. Similar studies to assess the strengths and weaknesses of the identified genotypes were conducted on seedling vigour and root traits under moisture stress in wheat [58] and on seedling vigour and yield traits in rice [59].

The good and poor storer QPM inbred lines were identified by inversely targeting the high and low values for selected traits using the MGIDI. A heat map depicting the expression patterns of the selected 12 traits in the identified good and poor storer inbred lines, excluding the inbred lines on the cutoff line, indicates significant differences between the two groups and confirms the selection efficiency (Fig. 8). It also helps determine the QPM inbred lines with desired trait combinations. For example, the inbred MGU-QPM-47 had the lowest t₅₀_18M and MGT_18M, indicating a faster germination rate than the remaining identified good storer genotypes. The present findings agree with earlier studies that reported contrasting physiological and biochemical traits between good and poor storer genotypes in soybean [60, 61] and onion [62].

Conclusions

The present study evaluated 28 distinct advanced QPM inbred lines and identified four good and poor storers. The lines were identified by considering multiple seed viability and vigour traits at pre- and post-storage conditions and by assessing natural and accelerated ageing processes. Among the good storers, the MGU-QPM-47 has better seed longevity and post-storage vigour. Given the high heritability of the traits and the increased selection differential driven by good storers, the identified inbred lines have the potential to serve as parental material for developing QPM hybrids with improved seed longevity and plant establishment. However, further studies involving crossing and developing F₁s are necessary to confirm this. The identified contrasting inbred lines facilitate the development of mapping populations for the identification of genomic regions through QTL analysis. Further, this study paves the way for integrating seed traits into breeding processes to ensure the success of hybrid seed production and adoption of QPM hybrids.

Authors’ contributions

Conceptualisation, Vijay D; Data collection, Ahmad D, Archana HR; Analysis and interpretation of results, Vijay D, Ahmad D, Prasad M; Writing-original draft preparation: Ahmad D, Vijay D; Writing-review and editing, Hossain F, Singh R, Prasad M, Vijay D; Resources, Vijay D, Hossain F, Singh R. All authors have read and approved the final version of the manuscript.

Funding

The research was carried out without financial support from any external research grants.

Data availability

All data generated or analysed during this study are included in this published article and its supplementary information files.

Declarations

Ethical approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.