Introduction
Phosphorus (P) is a major macronutrient required for proper plant growth and reproduction. It is entailed in various key physiological and biological processes of the plant such as photosynthesis, energy transfer, nutrients mobilization, carbohydrate transportation including metabolism and also a key component of nucleic acids (Lambers et al., Reference Lambers, Martinoia and Renton2015; Meng et al., Reference Meng, Chen, Wang, Huang, Ye, Chen and Yang2021). Very obvious symptoms like purple-coloured leaves, reduced plant height and reedy stem can be noticed when plants face phosphorus starvation (Zribi et al., Reference Zribi, Hessini, Trabelsi, Zribi, Hamdi, Ksouri and Abdelly2017). The photosynthetic efficiency of plants is severely affected by phosphorus deficiency (Carstensen et al., Reference Carstensen, Herdean, Schmidt, Sharma, Spetea, Pribil and Husted2018; Meng et al., Reference Meng, Chen, Wang, Huang, Ye, Chen and Yang2021). Reduced number of pods and tillers in legumes and cereals, respectively, has been recorded upon inadequate P supply (Fageria, Reference Fageria2007; Fageria and Santos, Reference Fageria and Santos2008). In particular, leguminous crops need more P than other crop species owing to heavy consumption of this macronutrient during nitrogen fixation by legumes (Sprent, Reference Sprent1999; Lyu et al., Reference Lyu, Tang, Li, Zhang, Rengel, Whalley and Shen2016). However, in almost all crop species, plants use only 10–30% of the applied P (Syers et al., Reference Syers, Johnston and Curtin2008) while rest of P remains in soil creating pool of residual P where it leads to negative environmental impacts (Conijn et al., Reference Conijn, Bindraban, Schroder and Jongschaap2018). Moreover, phosphorus is entering into the list of depleting macronutrients predominantly in acidic and alkaline soils of tropical and sub-tropical regions (Krishnappa et al., Reference Krishnappa, Umesh and Hussain2011). It has been postulated that in coming next 60–130 years, the exploitable P reserves will be completely depleted (Steen, Reference Steen1998; Liu et al., Reference Liu, Villalba, Ayres and Schroder2008; Cordell et al., Reference Cordell, Drangert and White2009). Additionally, mining of the phosphorus from other possible sources will affect the cost of fertilizer use. Breeding for improved phosphorus use efficiency (PUE) can help to solve both ecological and cost issues (Bovill et al., Reference Bovill, Huang and McDonald2013). PUE can be enhanced by improving phosphorus uptake and utilization efficiency (van de Wiel et al., Reference van de Wiel, van der Linden and Scholten2016). P uptake efficiency is more important under low phosphorus environment, whereas P utilization efficiency is more significant under surplus P availability to improve PUE.
Chickpea (Cicer arietinum L.) is one of the important legume crops cultivated widely in more than 50 countries. India is the world's leading producer of chickpea contributing about 75% of total global production (Dixit et al., Reference Dixit, Srivastava and Singh2019; Gaur et al., Reference Gaur, Samineni, Thudi, Tripathi, Sajja, Jayalakshmi, Jayalakshmi, Mannur, Vijayakumar, Rao, Ojiewo, Fikre, Kimurto, Kileo, Girma, Chaturvedi, Varshney and Dixit2019). Regardless of having huge potential, chickpea productivity is constrained by various biotic and abiotic stresses along with its poor response to management practices. It is evident that conventional breeding method is not enough to cope up with these problems (Varshney et al., Reference Varshney, Thudi, May and Jackson2010; Garg et al., Reference Garg, Bhattacharjee and Jain2015; Jain et al., Reference Jain, Wettberg, Punia, Parihar, Lamichaney, Kumar, Gupta, Ahmad, Pant, Dixit, Sari, Sari, Maruf, Toker and Toker2023). One of the major bottle necks of the chickpea improvement programme is the use of existing variability with limited genetic base. Further, the replacement of landraces and traditional cultivars by genetically uniform high-yielding varieties has led to loss of variability accompanied by more vulnerability to various biotic and abiotic factors (Ficiciyan et al., Reference Ficiciyan, Loos, Sievers-Glotzbach and Tscharntke2018). Therefore, the genetic potential of chickpea along with stable higher yield with minimal environmental effects needs to be improved that can be achieved by the exploitation of desirable alleles from diverse genotypes as base materials (Sharma and Sharma, Reference Sharma, Sharma, Dixit, Singh and Singh2015). All these factors emphasized the development of stable high-yielding and stress resistance cultivars for which there is a need of conservation and maintenance of different germplasm accessions and further exploit underutilized alleles within wild relatives, landraces and exotic lines. Considering the importance of preservation and utilization of gene pool, a reference set of 300 accessions using allelic diversity data to represent the whole genetic diversity in genus Cicer was developed (Upadhayaya et al., Reference Upadhyaya, Furman, Dwivedi, Udupa, Gowda, Baum, Crouch J, Buhariwalla and Singh2006; Upadhyaya et al., Reference Upadhyaya, Dwivedi, Baum, Varshney, Udupa, Gowda, Hoisington and Singh2008). This diverse chickpea reference set can be utilized for future chickpea breeding programmes to study and explore underrated or neglected traits like PUE.
At present when P is becoming one of the deficient macronutrients in majority of cultivated land, there is a dire necessity of exploitation of genetic diversity in chickpea with special reference to the PUE that has not been utilized yet. Moreover, use of higher levels of P fertilizers induces Zn deficiency in plants (Srinivasarao et al., Reference Srinivasarao, Ganeshamurthy, Ali and Venkateswarlu2006) and depletion of exhaustible natural phosphorus deposits (Reijnders, Reference Reijnders2014). So, to meet the high demands of exhaustible resources of phosphatic fertilizers, intraspecific genetic variability should be studied and exploited. Therefore, designing crop varieties with high productivity and enhanced PUE may help to make optimum use of P fertilizers without compromising seed yields. This may also help in coping with environmental and hydrological issues arising through heavy fertilizer application (Ahmad et al., Reference Ahmad, Gill and Qureshi2001). Keeping in view, the present study was attempted to identify the chickpea genotypes with high PUE that further expose new horizons in chickpea breeding programme facing the problem of low phosphorus.
Materials and methods
Plant material
A set of 288 chickpea genotypes from the reference set was evaluated for PUE based on the performance of genotypes for seed yield under low P compared to high P conditions and yield-contributing traits at Punjab Agricultural University (PAU), Ludhiana, India. The chickpea reference set effectively captures a substantial portion of the genetic variation present in the entire chickpea germplasm across the globe. Specifically, it encompasses 78% of the alleles found in the composite collection, indicating that it is a comprehensive representation of genetic diversity. Furthermore, the reference set exhibits variation in seed types, with desi, kabuli and pea-shaped accessions among cultivated types, in addition to wild Cicer accessions. This diversity is crucial for breeding programmes as it provides a broad genetic base to work with, potentially enhancing resilience, adaptability and overall performance of chickpea varieties.
Evaluation of chickpea reference set
The experiments were conducted for two consecutive years viz., 2018–19 and 2019–20 in alpha-lattice design under two phosphorus regimes (low P – no phosphorus application and high P – phosphorus application at 40 kg/ha). Therefore, four sets of experiments (E) namely, low P 2018–19 (E1), high P 2018–19 (E2), low P 2019–20 (E3) and high P 2019–20 (E4) were set up in two replications. Each genotype was planted in paired rows of 1.5 m length keeping row-to-row and plant-to-plant spacing of 30 cm × 10 cm in Ludhiana. It is positioned at a latitude of 30°54′ N, signifying its placement north of the equator, and with a longitude of 75°48′ E, the experimental site boasted an altitude of 247 m above sea level.
Agro-morphological traits
Data were meticulously recorded on five random plants for each genotype, encompassing a range of vital traits including plant height (cm), number of primary branches, number of secondary branches, number of pods per plant and seeds per 10 pods (g). The data for all other traits were recorded on per plot basis including days to germination, days to flower initiation, days to 50% flowering, days to maturity, as well as crucial photosynthetic parameters such as chlorophyll content at the pre-flowering stage. The chlorophyll content was measured using SPAD Chlorophyll Meter Readings (SCMR) obtained from a SPAD-502 meter (Minolta Konica Co. Ltd., Japan). Additionally, other important traits contributing to yield were documented on per plant basis as an average including biological yield per plant (g), seed yield per plant (g) and harvest index (%). Harvest index (%) was calculated as: economic yield/biological yield × 100; where economic yield corresponds to total grain yield per plant (g); and biological yield is the total dry weight per plant (g).
Soil analysis and phosphorus use efficiency
The soil texture in the experimental site was loamy sand as the content of sand, silt and clay in the experimental field was 78.8, 7.9 and 13.2%. On soil test basis, the average pH of the experimental site was 7.8 and EC was 0.11 dS/m. Organic carbon, available nitrogen (N), phosphorous (P) and potassium (K) were 0.26%, 128 kg/ha, 9.85 kg/ha and 152 kg/ha, respectively. The available Zn, Fe and Cu were 0.82, 5.32 and 24 ppm, respectively. PUE was estimated using equation adopted from Moll et al. (Reference Moll, Kamprath and Jackson1982): seed yield (kg/ha)/PSoil + PApplied; where PSoil corresponds to natural P content of soil (kg/ha) and PApplied is P dose allocated through fertilizer (kg/ha).
Statistical analyses
The data were subjected to analysis of variance (ANOVA) using proc GLM procedure of SAS software (SAS 2013). Correlation among various traits was estimated using R software (R Core Team, 2020). Phenotypic and genotypic correlation coefficients were estimated using the standard procedure suggested by Miller et al. (Reference Miller, Williams, Robinson and Comstock1958) and Kashiani and Saleh (Reference Kashiani and Saleh2010).
Results
Phenotypic variation under different phosphorus (P) regimes
The ANOVA results revealed significant variability among the genotypes for all the investigated traits under both phosphorus regimes for two cropping seasons during 2018–19 and 2019–20 except chlorophyll content in individual environments (Table 1; online Supplementary Tables S1 and S2).
Table 1. Pooled analysis of variance for low P and high P regimes (2018–19 and 2019–20)
SV, source of variation; DF, degrees of freedom; GERMI, days to germination; FI, days to flower initiation; F50, days to 50% flowering; SCMR, chlorophyll content; NPB, number of primary branches; NSB, number of secondary branches; DTM, days to maturity; PH, plant height (cm); NOP, number of pods per plant; SP10P, seeds per 10 pods; SW100, 100-seed weight (g); BY, biological yield (g); SY, seed yield per plant (g); HI, harvest index (%); G, genotype; Rep, replication.
*Significant at P = 0.05.
Days to germination in all four environments ranged from 7 to 10 days with a mean of 8.06 in E1, 8.65 in E2, 8.18 in E3 and 8.46 in E4. Days to flower initiation was observed to be increased under high P conditions in both years, mirroring the trend observed for days to 50% flowering (Table 2). The mean values for number of primary branches were 2.26 in E1, 2.07 in E2, 1.58 in E3 and 1.70 in E4. Similarly, for number of secondary branches, observed mean values were 13.54 (E1), 16.39 (E2), 14.07 (E3) and 16.06 (E4) (Table 2) revealing positive impact of high P on the trait.
Table 2. Mean and range of various traits across different environments
The days to maturity showed a decline under high P conditions, while plant height was observed to be more under high P than low P regime. The number of pods per plants showed positive effect of high P in both the years of experiment, although seeds per 10 pods decreased (Table 2). The 100-seed weight also followed a similar (decreasing) trend under high P conditions. Biological yield reduced in the first year but increased in the second year under high P. Mean seed yield per plant demonstrated a positive effect of high P; 13.52 g (E1), 14.01 g (E2), 14.77 g (E3) and 16.40 g (E4). The positive effect of high P on harvest index was observed only during the first year with a mean of 33.11, 36.38, 33.45 and 33.29 in E1, E2, E3 and E4, respectively. The mean values and range for morphological data have been given in Table 2.
Better performing genotypes under different phosphorus conditions
The genotype ICC 5639 was found with highest mean increase (44.65%) in seed yield during the cropping seasons 2018–19 and 2019–20 under low P conditions in comparison to high P conditions followed by genotypes namely, ICC 7413, ICC 11584, ICC 13357, ICC 9590, ICC 2072, ICC 4418, ICC 4567, ICC 9702, ICC 5504, ICC 1161, ICC 1098, ICC 1052, ICC 1083, ICC 4991 (Fig. 1(a)). These results indicated that these genotypes were more efficient for P-use efficiency for seed yield. In addition, PUE under low P conditions was compared with PUE at high P conditions through scatter diagram to determine the efficiency of genotypes. This classified the reference set into four classes viz., non-efficient non-responder, efficient non-responder, non-efficient responder and efficient responder (Fig. 1(b)). Under low P conditions, above average genotypes were considered as efficient. Overall, efficient genotypes have higher utilization of absorbed P over non-efficient genotypes.
Figure 1. (a) Promising genotypes for seed yield per plant under low P conditions in comparison to high P conditions. (b) Scatter plot representing relationship between genotypes performance for PUE under two phosphorus regimes.
The genotypes ICC 4567, IG 10419, ICC 13187, ICC 1923, IG 6343, ICC 8350, ICC 5504, ICC 13357, ICC 3410, ICC 1715, ICC 7668, ICC 15762, ICC 8151, ICC 15888 and ICC 8200 recorded remarkably higher number of pods per plant under low P conditions as compared to high P conditions during both the cropping seasons 2018–19 and 2019–20 (Fig. 2(a)).
Figure 2. Variation for (a) number of pods per plant, (b) seeds per ten pods, (c) biological yield, (d) harvest index, in chickpea reference set under low P conditions in comparison to high P conditions.
Likewise, the genotypes having variation for seeds per 10 pods, biological yield and harvest index with highest per cent increase under low phosphorus conditions than high phosphorus conditions have been depicted in Fig. 2(b)–2(d), respectively. The genotype ICC 13357 performed better for seed yield and yield-contributing traits like number of pods per plant and harvest index under low P conditions (Figs 1(a), 2(a), 2(d)). Similarly, the genotype ICC 11584 performed better under low P conditions for seed yield and harvest index (Figs 1(a) and 2(d)). Some other genotypes showed remarkably higher values for the yield-contributing traits viz., number of pods per plant, seeds per 10 pods, biological yield and harvest index under low P conditions. The genotypes ICC 4567 and ICC 5504 performed better under low P for the seed yield and yield-contributing traits namely number of pods and biological yield (Figs 1(a), 2(a), 2(c)). Genotype ICC 16654 also showed promise for seeds per 10 pods and biological yield (Fig. 2(b) and 2(c)). The genotypes ICC 1161 and ICC 4991 performed better under low P regime as compared to high P conditions for seed yield and seeds per 10 pods (Figs 1(a) and 2(b)). The observations for number of pods per plant and biological yield were higher for the genotypes ICC 7668 and ICC 8200 under low P conditions as compared to high P regime (Fig. 2(a) and 2(c)).
Overall, 15 desi chickpea genotypes ICC 1052, ICC 1083, ICC 1098, ICC 1161, ICC 2072, ICC 4418, ICC 4567, ICC 4991, ICC 5504, ICC 5639, ICC 7413, ICC 8350, ICC 9590, ICC 9702, ICC 11584 and one kabuli chickpea genotype ICC 13357 were considered as promising for PUE with respect to higher yield and yield-attributing traits (Table 3). Thus, the outcomes of the present investigation are encouraging for low input chickpea breeding. Under high P regime the genotypes ICC 6579, ICC 6263, IG 10500, ICC 5337, ICC 16487, ICC 13124, ICC 16374, ICC 15610, ICC 13863 and ICC 1915 were found promising for yielding ability. These genotypes can thus be considered as good sources for breeding for high phosphorus conditions to improve productivity. Moreover, the genotype ICC 15610 was in the top ten entries in term of yield under both high and low P regimes, thus exhibiting stable PUE across the P regimes as well as cropping seasons.
Table 3. Promising genotypes based on seed yield and yield contributing under low P in comparison to high P conditions
Correlation studies
Correlation analysis revealed significant and positive correlations between seed yield and biological yield, number of pods, harvest index, number of primary branches with Pearson coefficient values (r) of 0.74 and 0.82; 0.66 and 0.55; 0.47 and 0.32; 0.23 and 0.16 under low and high P conditions, respectively (Fig. 3(a) and 3(b)). Phenotypic and genotypic correlation coefficient among the traits under low and high phosphorus regimes during both the years of experiment is presented in online Supplementary Tables S3–S6. These results revealed that under both phosphorus regimes, selection for harvest index, biological yield, seeds per 10 pods and number of pods per plant will help in improving seed yield of chickpea. Under low P regimes (online Supplementary Tables S3 and S4), significant positive correlations of biological yield with seeds per 10 pods, number of pods per plant and number of primary branches; seeds per 10 pods with number of pods per plant and days to maturity and significant negative correlation with 100-seed weight were observed. Positive correlations were observed for the trait number of secondary branches with plant height, number of primary branches with number of pods per plant, days to 50% flowering with days to maturity and days to flower initiation.
Figure 3. Correlation chart among estimated traits under (a) low P, and (b) high P conditions.
Under high phosphorus regimes (online Supplementary Tables S5 and S6) during both the seasons 2018–19 and 2019–20, biological yield was found to be significantly and negatively correlated with harvest index whereas positively correlated with 100-seed weight, plant height and number of secondary branches. For the trait 100-seed weight, negative correlations with seeds per 10 pods and number of pods per plant and positive correlation with plant height and chlorophyll content were observed. The trait seeds per 10 pods were found to be negatively correlated with plant height and chlorophyll content. Number of pods per plant had significant negative correlations with days to flower initiation and days to 50% flowering and significant positive correlation with number of secondary branches. Chlorophyll content was found to be positively correlated with days to maturity. The trait days to flower initiation was found to be positively correlated with days to 50% flowering but it was negatively correlated with number of secondary branches (online Supplementary Tables S5 and S6).
Discussion
Chickpea stands as a vital legume crop globally, contributing significantly to food security and agricultural sustainability. Harnessing genetic diversity and employing modern molecular tools can facilitate the development of chickpea varieties with enhanced PUE, ensuring sustainable crop productivity in phosphorus limited environments. Henceforth, understanding the mechanisms underlying phosphorus acquisition, uptake and utilization in chickpea plants is fundamental to address this issue.
ANOVA indicated presence of significant variability among the genotypes in all the four experimental environments for all the traits except chlorophyll content. This significant variance implies the scope for selection and utilization of the diversity within the reference set for chickpea improvement programmes. The results concur with the various studies on core and mini core subsets of ICRISAT germplasm collection and other collections that reported significant variability for various traits such as days to 50% flowering, days to maturity, plant height, number of primary and secondary branches, 100-seed weight, number of pods per plant, seed yield per plant (Upadhyaya and Ortiz, Reference Upadhyaya and Oritz2001; Upadhyaya et al., Reference Upadhyaya, Bramel and Singh2001; Gowda et al., Reference Gowda, Upadhyaya, Dronavalli and Singh2011; Chrigui et al., Reference Chrigui, Sari, Sari, Eker, Cengiz, Ikten and Toker2021; Eker et al., Reference Eker, Sari, Sari, Tosun and Toker2022) and seeds per 10 pods (Upadhyaya et al., Reference Upadhyaya, Ortiz, Bramel and Singh2002). In disparity to present results, Chaturvedi et al. (Reference Chaturvedi, Mishra and Kumar2009) reported non-significant results for plant height and seeds per pod in chickpea germplasm collection. This difference and extent of variability can be ascribed to various causes including magnitude of the environmental impact on the expression of traits.
In the present study, different genotypes from the reference set were recognized as P-efficient genotypes under low P regimes. Similarly, Pang et al. (Reference Pang, Zhao, Bansal, Bohuon, Lambers, Ryan and Siddique2018) studied P-use efficiency in a set of 100 genotypes taken from the reference set and reported the genotype ICC 8350 to be more efficient for P use, which supported the results of present study as the same genotype also revealed higher values for the traits namely number of pods per plant and seed yield. Similarly, the genotype ICC 2277 that showed higher harvest index (Fig. 2(d)) was also reported as phosphorus-efficient by Pang et al. (Reference Pang, Zhao, Bansal, Bohuon, Lambers, Ryan and Siddique2018). In another study, Keneni et al. (Reference Keneni, Bekele, Assefa, Imtiaz, Debele, Dagne and Getu2015) identified the genotype ICC 4918 as P-efficient which had higher seeds per 10 pods in the current study. In the present investigation, on overall mean basis, seed yield per plant was observed to be increased with P application revealing the positive effect of high P on the trait. These results are in tune with the earlier report by Madzivhandila et al. (Reference Madzivhandila, Ogola and Odhiambo2012) where grain yield was reported to be increased with P fertilizer application but only on summer sowing in chickpea cultivars. But on the contrary, Wen et al. (Reference Wen, Chen, Neill, Wichman and Jackson2008) reported no response of the chickpea varieties to P fertilization with negligible increase in grain yield with P fertilizer. These findings can be attributed to the fact that most of the current cultivars have been bred for yield only, without any emphasis on nutrient use efficiency. Thus, the present study has facilitated the identification of potential germplasm lines that perform better under low phosphorus conditions. The improvement of PUE of chickpea can be achieved by using the P-use efficient genotypes identified in the present study as potential donors. Additionally, genotypes ICC 6579, ICC 6263, IG 10500, ICC 5337, ICC 16487, ICC 13124, ICC 16374, ICC 15610, ICC 13863 and ICC 1915 were identified as best performing under high P conditions, facilitating breeding for high input chickpea cultivation.
Yield is a complex character which is jointly determined by a number of yield-attributing traits. So, efficiency of selection for higher yield can be improved with the knowledge of the association between yield and yield-contributing traits. The estimated correlations generally vary with the set of genotypes under study. In the current study, seed yield per plant showed significant and positive association with harvest index under all the four environments. Earlier studies also suggest significant correlation between harvest index and seed yield (Sharma et al., Reference Sharma, Sood and Malhotra1989; Gumber et al., Reference Gumber, Singh, Rathore and Singh2000; Vaghela et al., Reference Vaghela, Poshiya, Savaliya, Davada and Mungra2009; Chopdar et al., Reference Chopdar, Bharti, Sharma, Dubey and Meena2017). Positive correlation of seed yield per plant with biological yield in low and high P regimes was also found effective in crop improvement programme (Thakur and Sirohi, Reference Thakur and Sirohi2009; Vaghela et al., Reference Vaghela, Poshiya, Savaliya, Davada and Mungra2009; Ali et al., Reference Ali, Tahir, Sadaqat, Arshad, Farooq, Ahsan, Waseem and Iqbal2011; Chopdar et al., Reference Chopdar, Bharti, Sharma, Dubey and Meena2017; Hagos et al., Reference Hagos, Desalegn and Belay2018). Under high P conditions major traits viz., seed yield per plant and harvest index were found to be positively correlated with number of pods per plant and seeds per 10 pods suggesting that selection for these yield-contributing traits will help to enhance chickpea productivity (Bahl and Jain, Reference Bahl and Jain1977; Sharma et al., Reference Sharma, Sood and Malhotra1989; Upadhyaya et al., Reference Upadhyaya, Bramel and Singh2001; Malik et al., Reference Malik, Bakhsh, Asif, Iqbal and Iqbal2010; Salgotra, Reference Salgotra2016; Hagos et al., Reference Hagos, Desalegn and Belay2018). Prior studies were conducted with a restricted range of genotypes, contrasting with current research utilizing the chickpea reference set, which encompasses 288 of the most genetically diverse accessions worldwide. This set represents approximately 78% of the alleles present in the broader composite collection, thereby offering a comprehensive representation of genetic diversity, aiming to identify genotypes and key component traits crucial for breeding P-efficient cultivars in the present investigations.
Consequently, it can be concluded that the traits such as number of primary branches, number of pods per plant, seeds per 10 pods, biological yield and harvest index can serve as valuable criteria in a selection programme aimed at enhancing yield under different P regimes. Selecting traits that positively and significantly contribute to yield will ultimately result in increased yields. Therefore, these traits can be used as indirect selection indices for seed yield. The significant correlations identified in the present study will undoubtedly facilitate future achievements in breeding phosphorus use efficient chickpea varieties.
Conclusion
Genetic improvement in PUE of chickpea is most efficient and fundamental approach for sustainable crop growth and yield, particularly under low phosphorus soils. Nonetheless, genetic upgradation of chickpea PUE is determined by the nature as well as extent of genetic variability present in the gene pool. The present study was executed with the aim to identify P-efficient genotypes in a reference set of 288 genotypes under different phosphorus regimes. Sufficient variation was observed for all the traits under study in the current reference set under both the P regimes. The desi chickpea genotypes ICC 1052, ICC 1083, ICC 1098, ICC 1161, ICC 2072, ICC 4418, ICC 4567, ICC 4991, ICC 5504, ICC 5639, ICC 7413, ICC 8350, ICC 9590, ICC 9702, ICC 11584 and kabuli chickpea genotype ICC 13357 proved to be the most efficient in terms of yield and yield-attributing traits under low P conditions for two consecutive years of experiments. Moreover, understanding the correlation between traits linked to PUE is crucial for improving chickpea cultivation in low phosphorus environments. Promising accessions identified within reference set will serve as valuable genetic resources for chickpea breeding programme. Genotypes exhibiting high PUE discovered in this research will be utilized as parental lines in breeding crosses to develop new chickpea varieties suitable for low input conditions, while the best genotypes under high P conditions will be prioritized for breeding cultivars in high input cropping systems.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S1479262124000236
Data availability
All relevant data that support this study are present within the manuscript and supplementary files.
Acknowledgement
We are highly thankful to Chickpea Breeding Unit, International Crops Research Institute for the Semi Arid Tropics, Patancheru, India for providing seeds of reference set.
Funding statement
This research did not receive any specific funding.
Competing interests
No potential conflict of interest is reported by the authors.
