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Article

Seasonal Variation of Tropical Savanna Altered Agronomic Adaptation of Stock-6-Derived Inducer Lines

by
Paepan Sintanaparadee
1,
Abil Dermail
1,
Thomas Lübberstedt
2,
Kamol Lertrat
3,
Sompong Chankaew
1,3,
Vinitchan Ruanjaichon
4,
Nittaya Phakamas
5 and
Khundej Suriharn
1,3,*
1
Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand
2
Department of Agronomy, Iowa State University, Ames, IA 50011, USA
3
Plant Breeding Research Center for Sustainable Agriculture, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand
4
National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Pahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani 12120, Thailand
5
Department of Plant Production Technology, School of Agricultural Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
*
Author to whom correspondence should be addressed.
Plants 2022, 11(21), 2902; https://doi.org/10.3390/plants11212902
Submission received: 29 August 2022 / Revised: 14 October 2022 / Accepted: 25 October 2022 / Published: 28 October 2022
(This article belongs to the Collection Doubled Haploid Technology in Plant Breeding)
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Abstract

:
Tropicalization is one of the major objectives in breeding haploid inducers to address the poor adaptation of temperate haploid inducers in doubled haploid production in tropical maize. Gaining a better understanding of weather profiles in targeted agroecology is important. This study aimed to investigate the seasonal variation of tropical savanna climate and its impact on agronomic traits and haploid induction rate (HIR) of Stock-6-derived haploid inducer lines. A total of 14 haploid inducers were evaluated across two typical growing seasons between 2020 and 2021. Weather data were collected on daily minimum and maximum temperatures, relative humidity, precipitation, and solar radiation whereas phenotypic data were recorded on plant phenology, tassel attributes, plant stature, ear components, inducer seed rate (ISR), and HIR. The effects of season, genotype, and genotype by season were significant for all traits except season factor on ISR. Seasonal variation existed where the dry season was more suitable for haploid induction and inducer maintenance, as haploid inducers revealed better agronomic performance and seed set, delayed flowering dates, and higher HIR. Since the crossover performance of haploid inducers over seasons was detected, further implications on genotype selection in each season are discussed.

1. Introduction

Doubled haploid (DH) technology has become a part of worldwide commercial maize breeding programs since it fastens the formation of homozygous inbred lines from 6–8 generations to only 2 generations [1]. Haploid induction, the first step of DH technology, may be accomplished with two systems: in vivo and in vitro methods [2]. In vivo haploid induction is preferable and widely adopted in maize [1]. Through this system, haploid inducers act as pollinators of source (donor) germplasm to produce maternal haploids [1]. The proportion between the number of induced haploids and total seeds per induction cross is called haploid induction rate (HIR). The first haploid inducer was Stock 6 with 2.3% of HIR [3], and more recent haploid inducers have HIRs ranging from 8–15% [4,5,6,7,8,9,10]. Most modern haploid inducers are adapted to temperate regions. When introduced to the tropics, poor tropical adaptation results in shorter plant stature, poor flowering synchrony, pollen production, and seed set, and susceptibility to major tropical diseases [11]. This maladaptation syndrome complicates haploid induction and inducer maintenance, hindering the rapid adoptions of temperate inducers in tropical maize breeding programs [12]. Thus, haploid inducers with high HIR and tropical adaptation are essential for use in tropical regions. The International Maize and Wheat Improvement Center (CIMMYT) in collaboration with the University of Hohenheim developed the first generation of tropically adapted inducer lines (TAILs) [11], and recently released CIM2GTAILs as the second generation of TAILs possessing 8–15% of HIR and good adaptation to both tropical and subtropical environments [13]. These inducers are available for a licensing fee; however, the cost can be unaffordable for seed start-ups.
Thailand has a typical tropical savanna climate [14] that covers three seasons, namely, rainy (May to October), cool dry (October–February), and summer dry (February–May). This climate has several features as follows: 1200–1400 mm of rainfall per year, 63–84% of relative humidity, 13–24 °C of seasonal minimum temperature, and 30–40 °C of seasonal maximum temperature (Thai Meteorological Department, Thailand. Available online: http://www.tmd.go.th (accessed on 8 May 2022)). Temperature is one of the critical parameters determining the adaptation and HIR of haploid inducers. Kebede et al. [15] reported that the winter season was more suitable for haploid induction than the summer season in subtropical Mexico. In contrast, De La Fuente et al. [2] noticed higher HIR in a warmer than in a cooler summer under a temperate climate in Iowa. However, there is no study reporting the weather variability and its effect on the agronomic adaptation and HIR of maize haploid inducers under tropical savanna climates.
Khon Kaen University in Thailand has initiated breeding haploid inducers by introducing the temperate inducer ‘Stock 6’, which is a public maize haploid inducer, to Thai maize germplasm possessing tropical backgrounds, aiming to develop new haploid inducers showing agronomic adaptation for tropical savanna regions and sufficient HIR [16]. Favorable traits for tropical maize and vegetable corn include earliness, shorter plant stature, and high grain yield [17,18]. In addition to those criteria, maize haploid inducers with large tassel size, longer pollen-shed duration, high pollen production, and resistance to ear rot are preferable to optimize self- and cross-pollinations for haploid seed production in induction nurseries and inducer maintenance, respectively [19]. Therefore, this study aimed to investigate the effect of seasonal variation of tropical savanna climate on agronomic traits and the HIR of Stock-6-derived haploid inducer lines. Information obtained in this study will assist breeders by means of screening their haploid inducers against different seasons of haploid induction to achieve optimal haploid production and inducer maintenance.

2. Results

2.1. Analysis of Variance

Season (S) effect was highly significant on all measured traits except on inducer seed rate (ISR) (Table 1). The effects of genotype (G) and the interaction between season and genotype (GSI) were highly significant on all observed traits. Genotype accounted for the highest proportion of source of variance on ISR, ear length (EL), husk cover (HC), GR, plant height (PH), ear height (EH), primary tassel branch (PTB), and total tassel branch (TTB). Season largely contributed to ear weight (EW), ear diameter (ED), row number per ear (NRE), seed number per row (NSR), cob diameter (CD), and seed diameter (SD). The GSI was predominant for haploid induction rate (HIR).
The significance of genotype indicated the phenotypic variability among 14 haploid inducer lines on overall agronomic performance, yield components, and HIR. The significance of season suggested that phenotypic means of inducers on most traits changed in different growing seasons. The predominance of the GSI on HIR implied that the HIR of inducer lines was sensitive to seasonal variation, and each genotype expressed different responses to different growing seasons.

2.2. Seasonal Variation and Plant Phenology

The daily minimum, average, and maximum temperatures during the dry season were 18.3 °C, 26.0 °C, and 33.1 °C, respectively, which were lower than those during the rainy season which had the daily minimum, average, and maximum temperatures of 24.5 °C, 30.2 °C, and 37.7 °C, respectively (Figure 1). Total precipitation in the dry season was much lower than that in the rainy season, as indicated by 2.6 mm against 682.5 mm. Relative humidity during the dry season (56 to 69%) was lower than that during the rainy season (66 to 84%). Meanwhile, the solar radiation of the dry season (21.8 MJ m−2 day−1) was slightly higher than that of the rainy season (20.7 MJ m−2 day−1). These results indicated that seasonal variation between the dry and rainy seasons existed.
The phenology was expressed in days after sowing (DAS) and growing degree days (GDD) (Figure 2). Haploid inducers grown in the rainy season required 1104.9 of GDD or 53 days to anthesis (VT stage) while the same set of genotypes in the dry season required 945.2 of GDD or 61 DAS. In regard to achieving physiological maturity (R6 stage), haploid inducers in the rainy season required 1965.4 of GDD or 98 DAS while it required at least 1689.3 of GDD or 106 DAS. This result indicated that the phenology of overall haploid inducer lines grown in the rainy season was faster than in the dry season, as indicated by higher GDDs but shorter days to anthesis and maturity.

2.3. Performance of Maize Haploid Inducers against Seasonal Variation

Maize haploid inducers grown in the dry season showed a slightly lower germination rate than in the rainy season (Table 2). On the contrary, these inducers had significantly higher values of PSD, DTA, DSI, PH, EH, PTB, TTB, TSL, and SPL in the dry season than in the rainy season, indicating that the weather profiles of the dry season conditioned maize inducers to delay the flowering dates, extend the duration of pollen shed, broaden the tassel architecture, and enhance the vegetative growth that resulted in higher plant stature. Likewise, the considerable increases in genotypic means in EW, ED, NRE, NKR, CD, and KD were noticed in the dry season while slight increases in the means were found in EL and HC. These results illustrated that the dry season may provide suitable conditions for ear development and seed set of maize inducers. Two major parameters, HIR and ISR, showed higher values in the dry season than in the rainy season, suggesting that both activities of haploid induction and inducer seed maintenance were more efficient in the dry season.

2.4. Interaction between Genotype and Season in Maize Haploid Inducers

In the dry season, KHI 65 and KHI 66 had the highest HIR (3.4% and 3.3%, respectively) among 14 haploid inducers, followed by KHI 54 (2.5%) (Table 3). In regard to ISR, the highest values were noticed in four haploid inducers, namely, KHI 47 (94.2%), KHI 42 (93.6%), KHI 5 (92.0%), and KHI 55 (91.8 %). The results showed that haploid inducers with the highest HIR were from the moderate group while haploid inducers with the highest ISR were noticed from each group. In this growing season, there was no clear association between HIR and ISR where haploid inducers with high haploid production tend to possess moderate inducer seed set.
In the rainy season, the highest HIR was found in three haploid inducers: KHI 42 (1.8%), KHI 50 (1.8%), and KHI 66 (1.5%). In addition, four haploid inducers, KHI 56 (97.5%), KHI 5 (95.6%), KHI 42 (95.2%), and KHI 72 (94.3%), had the highest ISR. In this season, both HIR and ISR seemed to be correlated as more haploids were induced from the inducer genotypes with higher ISR. For instance, KHI 42 having 95.2% of inducer seed set showed a 1.8% haploid frequency per cross.

3. Materials and Methods

3.1. Plant Materials

A total of 14 Stock-6-derived maize inducer lines were used in this study (Table 4). The origin and pedigree of these lines were described by Dermail et al. [16]. Briefly, base populations were established from intercrossing between temperate inducer Stock 6 with 2.3% of HIR [7] and eight tropical corn genotypes including three waxy corn (KND, TL, and TB), two sweet corn (101L and WST), and three field corn genotypes (Pacific339, NS3, and NSX).
About 78 S3 families were obtained in the dry season of 2019, and those materials were further utilized for dual studies, namely, the first study on selection gain through the modified ear-to-row method [16] and the second study on seasonal variation which was emphasized in this paper. Unweighted selection index, a simultaneous selection method without considering certain economic values of traits of interest, [20] was performed at the preliminary study to sort all 78 genotypes based on HIR, inducer seed rate, and agronomic score. The top rank genotype had the highest indices (z). Then, we determined the thresholds of selection indices (z) to categorize the sorted genotypes into three groups: high (genotypes with z ≥ 2.5), moderate (genotypes with 0.5< z < 2.5), and low (genotypes with z ≤ 0.5). According to the groups established, representative five, five, and four genotypes, respectively, were selected based on the top rank within the group. The list of the genotypes is presented in Table 4.

3.2. Field Experiment

Fourteen Stock-6-derived maize inducer lines were evaluated under field conditions at the Agronomy Field Crop Research Station, Khon Kaen University, Khon Kaen, Thailand (16°28’27.7” N, 102°48’36.5” E; 190 m above sea level (masl)) in two different growing seasons, namely, the dry season (November 2020–February 2021) and the rainy season (April–August 2021). The inducer lines were assigned in a randomized complete block design (RCBD) with three replications. The plot size was 4 rows of 5 m in length. The plant spacing was 0.75 m × 0.25 m; thus, the plant density was about 80 plants per plot. In both seasons, standard agronomic practices were used following the Department of Agriculture, Thailand, recommendations (Thai Agricultural Practice, Department of Agriculture, Thailand. Available online: http://www.doa.go.th (accessed on 12 June 2022)) including land preparation, fertilization, irrigation, and pest, disease, and weed control.
The weather profiles such as daily minimum and maximum temperatures (°C), relative humidity (%), precipitation rate (mm), and solar radiation (MJ m−2 day−1) were collected daily during the experiment from the Agricultural Weather Station, Agronomy Field Research Station, Khon Kaen University, Thailand. Growing degree days (GDD) [21] of each growing season were calculated for every day after planting by accumulating the temperature per day using the following formula:
°C day−1 = ((Tmin + Tmax)/2) – 10
where Tmin is the daily minimum temperature (°C) and Tmax is the daily maximum temperature (°C). The base temperature for maize is 10 °C.

3.3. Haploid Induction and Ploidy Identification

Two commercial F1 hybrids S7328 and P789 released by Syngenta Seeds and Pacific Seeds, respectively, were used as the donor parent or tester. Three staggered planting dates for donor genotypes with intervals of seven days were carried out to ensure flowering synchrony. The donor was placed adjacent to the inducer plots. About ten inducer plants per plot were selected and self-pollinated for inducer maintenance, and those selected plants per plot were also individually cross-pollinated to ten ears of each donor genotype for haploid induction.
All dried seeds from each donor ear were classified based on the R1-nj anthocyanin biomarker on the crown (top endosperm tissue) and scutellum of the embryo [22]. They were classified into putative diploid if the seeds showed purple colorations of the endosperm and embryo and putative haploid if the seeds showed purple endosperm and colorless embryo. Haploid induction rate (HIR) and inducer seed rate (ISR) were calculated as follows:
HIR   ( % ) = seed   number   of   putative   haploid total   seed   number   per   ear  ×  100
ISR   ( % ) = seed   number   of   inducer total   seed   number   per   ear  ×  100

3.4. Data Collection

Germination rate was calculated as the percentage of emerged seedlings per plot at 14 days after sowing (DAS). At the reproductive stage, the following agronomic traits were recorded using the sample basis of 10 plants per plot except for flowering dates which were plot-based measurements: plant height (cm), as a distance from ground level to the node bearing the flag leaf; ear height (cm), as a distance from ground level to the node bearing the uppermost ear; days to anthesis, as the number of days from sowing to when 50% of the plants shed pollen; days to silking, as the number of days from sowing until silks emerged on 50% of the plants; pollen-shed duration (days), as the number of days from the last day of pollen shedding minus the first day of pollen shedding; primary tassel branching, as the number of primary tassel branches having anthers emerged; total tassel branching, as the total number of tassel branches including the primary and secondary branches; tassel length (cm), as the length from the lowermost primary branch to the tip of the tassel; and spike length (cm), as the length from the uppermost branch to the tip of the spike.
Yield components were measured on ten ears per plot at the physiological maturity stage approximately 45 days after pollination (DAP). The parameters included ear weight (g), ear diameter (cm), ear length (cm), husk cover, the number of rows per ear, the number of kernels per row, cob diameter (cm), and kernel diameter (cm).

3.5. Statistical Analysis

All observed data were subjected to Bartlett’s test for homogeneity of variance and the Shapiro–Wilk test for normality. Then, combined analysis of variance was performed considering season and genotype as random effects and replication as a fixed effect by using PROC MIXED of SAS ver. 9.0 (SAS Institute. SAS for Windows Version 9.0; SAS Institute: Cary, NC, United States, 2002) using the following linear model:
Yijk = µ + si + rj(si) + gk + sigk + εijk
where i = 1, 2; j = 1, 2, 3; k = 1, 2, 3…14; Yijk denotes the phenotype of genotype k in season i and replication j; µ is the overall mean; si is the effect of season i; rj(si) is the effect of replication k nested within season i; gk is the effect of genotype k; sigk is the effect of the interaction between season i and genotype k; and εijk is the pooled error of season i, replication j, and genotype k.
Duncan’s multiple range test (DMRT) at 0.05 probability level was used for mean comparison [23].

4. Discussion

4.1. Phenotype of Maize Haploid inducers Is Affected by Genotype, Season, and their Interaction

In this study, all agronomic traits and haploid induction rate clearly showed quantitative inheritance, with continuous variation, and respective phenotypes resulting from genotype, environment, and the interaction between genotype and environment [24]. The significance of genotype for all observed traits may be explained by the fact that the 14 haploid inducers used in this study were derived from different groups, based on haploid induction rate, R1-nj expression, and agronomic trait performance. Genotype had a strong impact on for ISR and several agronomic traits because we included several tropical non-inducer genotypes as founder parents, which had different plant ideotypes including plant stature, flowering behaviors, and yields, and the alleles of those traits may be segregated during population improvements. ISR was defined as the proportion of inducer seed per ear that expressed the R1-nj anthocyanin marker. Chaikam et al. [25] reported that tropical maize showed a high frequency of complete inhibition of R1-nj due to the presence of C1-I, a dominant anthocyanin inhibitor gene. In addition, the minor contribution of genotype on HIR might be due to the common founder parent used which was Stock 6.
The significant effect of season on most attributes indicated the presence of weather dynamics of tropical savanna climate from the dry season to the rainy season which altered the phenotypic means of haploid inducers. This result corroborated previous studies where seasonal variation under tropical savanna regions significantly contributed to the agronomic traits and yield components of vegetable corn [26,27]. Meanwhile, the predominant effect of GSI on HIR implied that the HIR of haploid inducers was sensitive to seasonal variation and each genotype responded differently in different growing seasons. GSI reflects genotype by environment interaction (GEI) and illustrates the failure of genotypes to be stable in different environmental conditions [28].

4.2. Seasonal Variation Is Responsible for Unstable Performance of Maize Haploid Inducers

In our region, the tropical savanna climate has two common maize-growing seasons, namely, the rainy and the dry seasons. In this study, the rainy season was identified with a high precipitation rate, relative humidity, and daily temperature, while the opposite weather features were clearly noticed in the dry season. The effect of contrasting temperature profiles over two seasons on maize phenology was illustrated with growing degree days [21,29]. Growing degree days (GDD) is one of the thermal units and is represented by the accumulated temperature above a base level for a whole crop growing period [30]. The values vary depending on the environmental conditions [31]. In maize, it has been adopted for estimating plant phenology including flowering, maturity, and harvest dates [32], for assessing the suitable growing environments [33], and for simulating crop growth such as in hybrid-maize models [34]. Our study found that the phenology of overall haploid inducer lines grown in the rainy season was faster than in the dry season, as indicated by higher GDDs but shorter days to anthesis and maturity. This corroborated previous studies in maize reporting that a warm-temperature zone had a higher accumulation of GDD and shorter sowing–silking interval than a cold-temperature zone in the tropical climates of Thailand and Mexico [35], the semi-humid and semi-arid climates of China [33], the semi-arid and humid subtropical of Texas [36], and the temperate climate of Czech Republic [37]. Lower daily temperatures led to increased maize vegetative growth [31] while, on the contrary, warmer daily temperatures accelerated the maize growth rate, which in turn shortened both vegetative and reproductive stages [38]. In our study, we also noticed variations during the vegetative period but fewer variations during the reproductive period. The result confirmed previously similar studies in maize, stating that the silking–maturity period was less variable than the sowing–silking period [39,40].
Weather plays critical roles in crop growth and phenology [41,42], aboveground biomass, and yield [31]. Among weather parameters, temperature, solar radiation, and precipitation are three major factors determining the development rate, biomass, yield components, and grain yield of maize under diverse climate regions from subtropical to temperate [31,37,43,44]. Our findings suggest that the dry season is more suitable than the rainy season for growing maize haploid inducers, as indicated by taller plant stature and ear position, later flowering, bigger tassel size, higher tassel branching, longer pollen-shed duration, larger ear and seed sizes, better seed set, and higher haploid induction rate. Kebede et al. [15] reported that the winter season was more suitable for haploid induction than the summer season in the subtropical climate of Mexico. Colder temperatures resulted in the maize plants being left for longer durations in the field [32]. Since the dry matter accumulation in maize relied on plant growth rate and growth duration [40], a prolonged vegetative stage and photoperiod made the maize utilize the abundant resources including radiation, water, and nutrients [45] to produce more photosynthates for more leaves [46,47], taller plant stature [36], later flowering and harvesting times without significantly altering the pollen production [48,49], and higher aboveground biomass [50] and grain yield [51]. In addition, cool nights in the dry season may benefit maize plants especially at the flowering and grain-filling stages by enhancing the accumulation of assimilates through photosynthesis and respiration processes [49,52].
In contrast, the conditions during the rainy season were unfavorable for haploid induction due to early flowering, smaller tassel size, and short pollen-shed duration, and prevalence of tropical diseases such as downy mildew, northern corn leaf blight, and rust. This led to poor pollination and seed set of both inducer and test crosses. High daily temperature, relative humidity, and precipitation during the rainy season were likely responsible. De La Fuente et al. [2] noticed that high precipitation rates during the pollination period dropped the haploid induction rate due to the significant damage by fungal ear diseases. In maize, increasing temperature and GDD significantly shorten the growth period and rate, resulting in reduced post-silking aboveground biomass [31], 1000-kernel weight, and grain yield [53]. There was a negative association between increasing temperature and maize yield [54,55] in which each additional GDD30+ led to a yield reduction of about 1.0–1.2% [29,56]. High temperatures contributed to yield reduction, not only because of the damage to maize flowers during daytime [30], but also because of increased respiration and decreased net dry matter accumulation during nighttime [57]. The impairment of maize flowers was further explained by the pollen sterilility [38,58] and the reduced floret elongation rate and number [59,60], leading to poor fertilization synchronization and high kernel abortion [61]. Since the potential kernel number and kernel weight rely on the number of florets [62] and the kernel growth rate [44], respectively, this condition may cause a reduction in the final seed set as the maize grain yield is composed of the kernel number per unit area and weight per kernel [63]. In addition, nitrogen is one of essential macronutrients for optimum maize growth, photosynthesis, and grain formation [64]; thus, excessive precipitation combined with warm daily temperatures during the rainy season may contribute to more yield losses due to nitrogen leaching and denitrification [65,66,67].

4.3. Crossover Performance of Maize Haploid Inducers and Implication for Haploid Induction

The significant interaction between genotype and season was revealed by the inconsistent performance of haploid inducers to produce haploid seeds over contrasting maize growing seasons. When cool temperatures during daytime and nighttime and low relative humidity occurred during the dry season, two haploid inducers, KHI 65 and KHI 66, were the best option. In contrast, when the weather conditions were getting worse, indicated by increasing temperatures, rainfall, and relative humidity, other haploid inducers such as KHI 42 and KHI 50 were the most viable option. In in vivo haploid induction, flowering synchrony between the silking of donor germplasm and the anthesis of haploid inducers is important, and occasionally incompatible pollinations occur when it comes to the male reproductive organ which has a shorter flowering period than the female one. In general, five to seven days are the total pollen-shed duration of maize inbred lines [49,68], while the stigmas of female plants are still receptive for 13 days after the silking initiation [69]. Since the pollen-shed duration of our haploid inducers was not only shorter than that normally reported, but also affected by the seasonal variation from five days in the dry season to three days in the rainy season, performing multiple planting dates with constant interval days of haploid inducers as the pollinator was feasible to extend the pollen production for haploid induction. The situation might be more complicated if vast germplasm with diverse silking dates are included. If so, utilizing two or more haploid inducers, having similar HIR with a different anthesis date, and multiple planting dates for those inducers with irregular interval days can be applied.

5. Conclusions

The effects of season, genotype, and genotype by season were significant for all traits except that season factored on inducer seed rate. Under a tropical savanna climate, the dry season was more suitable for growing haploid inducers for haploid production and inducer maintenance, as they revealed better agronomic performance and seed set, delayed flowering dates, and higher haploid induction rate (HIR). Two haploid inducers KHI 65 and KHI 66 (HIR~3.3–3.5%) were proposed to be used in the dry season when the weather conditions were suitable for maize growth, flowering, and seed development. Meanwhile, the other two inducers, KHI 42 and KHI 50 (HIR~1.8%), were the best option in the rainy season when high temperature, high precipitation, relative humidity, and disease incidence occurred. Applying two or more haploid inducers and using multiple planting dates for those inducers was suggested to achieve optimal seed set and potential haploid seeds per induction cross.

Author Contributions

Conceptualization, K.L., K.S., and P.S.; methodology, K.S., V.R., N.P., and P.S.; formal analysis, P.S., K.S., and S.C.; writing—original draft preparation, P.S., A.D., K.S., and S.C.; writing—review and editing, P.S., A.D., K.S., S.C., V.R., N.P., and T.L.; funding acquisition, K.S. All authors have read and agreed to the published version of the manuscript.

Funding

The National Science and Technology Development Agency (NSTDA) (grant no. P-20-50493 and P-20-52286).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors would like to thank the National Science and Technology Development Agency (NSTDA) (grant no. P-20-50493 and P-20-52286) and the Plant Breeding Research Center for Sustainable Agriculture, Faculty of Agriculture, Khon Kaen University, Thailand, for funding and providing plant materials and research facilities.

Conflicts of Interest

The authors declare no conflict of interest. The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Chaikam, V.; Molenaar, W.; Melchinger, A.E.; Prasanna, M.B. Doubled haploid technology for line development in maize: Technical advances and prospects. Theor. Appl. Genet. 2019, 132, 3227–3243. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. De La Fuente, G.N.; Frei, U.K.; Trampe, B.; Nettleton, D.; Zhang, W.; Lübberstedt, T. A diallel analysis of a maize donor population response to in vivo maternal haploid induction: I. Inducibility. Crop. Sci. 2018, 58, 1830–1837. [Google Scholar] [CrossRef] [Green Version]
  3. Coe, E.H. A line of maize with high haploid frequency. Am. Nat. 1959, 93, 381–382. [Google Scholar] [CrossRef]
  4. Tyrnov, V.S.; Zavalishina, A.N. High-frequency induction of matroclinal haploids in maize. Dokl. Biol. Sci.–Akad. Nauk. SSSR 1984, 276, 353–355. [Google Scholar]
  5. Lashermes, P.; Beckert, M. Genetic control of maternal haploidy in maize (Zea mays L.) and selection of haploid inducing lines. Theor. Appl. Genet. 1988, 76, 405–410. [Google Scholar] [CrossRef]
  6. Chalyk, S.T. Creating new haploid-inducing lines of maize. Maize Genet. Coop. News Lett. 1999, 73, 53–54. [Google Scholar]
  7. Röber, F.K.; Gordillo, G.A.; Geiger, H.H. In vivo haploid induction in maize—Performance of new inducers and significance of doubled haploid lines in hybrid breeding. Maydica 2005, 50, 275–283. [Google Scholar]
  8. Chang, M.T.; Coe, E.H. Doubled haploids. In Molecular Genetic Approaches to Maize Improvement. Biotechnology in Agriculture and Forestry; Kriz, A.L., Larkins, B.A., Eds.; Springer: Berlin, Germany, 2009; Volume 63, pp. 127–142. [Google Scholar]
  9. Rotarenco, V.A.; Dicu, G.; State, D.; Fuia, S. New inducers of maternal haploids in maize. Maize Genet. Coop. News Lett. 2010, 84, 21–22. [Google Scholar]
  10. De La Fuente, G.N. Improvement to the Maize (Zea mays L.) In Vivo Maternal Doubled Haploid System. Ph.D. Thesis, Iowa State University, Ames, IA, USA, 2015; pp. 38–51. [Google Scholar]
  11. Prigge, V.; Schipprack, W.; Mahuku, G.; Atlin, G.N.; Melchinger, A.E. Development of in vivo haploid inducers for tropical maize breeding programs. Euphytica 2012, 185, 481–490. [Google Scholar] [CrossRef]
  12. Prasanna, B.M. Doubled haploid (DH) technology in maize breeding: An overview. In Doubled Haploid Technology in Maize Breeding: Theory and Practice; Prasanna, B.M., Chaikam, V., Mahuku, G., Eds.; CIMMYT: Texcoco, Mexico, 2012; pp. 1–8. [Google Scholar]
  13. Chaikam, V.; Nair, S.K.; Martinez, L.; Lopez, L.A.; Utz, H.F.; Melchinger, A.E.; Prasanna, B.M. Marker-assisted breeding of improved maternal haploid inducers in maize for the tropical/subtropical regions. Front. Plant Sci. 2018, 9, 1527. [Google Scholar] [CrossRef] [Green Version]
  14. Beck, H.E.; Zimmermann, N.E.; McVicar, T.R.; Vergopolan, N.; Berg, A.; Wood, E.F. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 2018, 5, 180214. [Google Scholar] [CrossRef] [Green Version]
  15. Kebede, A.Z.; Dhillon, B.S.; Schipprack, W.; Araus, J.L.; Bänziger, M.; Semagn, K.; Alvarado, G.; Melchinger, A.E. Effect of source germplasm and season on the in vivo haploid induction rate in tropical maize. Euphytica 2011, 180, 219–226. [Google Scholar] [CrossRef]
  16. Dermail, A.; Chankaew, S.; Lertrat, K.; Lübberstedt, T.; Suriharn, K. Selection gain of maize haploid inducers for the tropical savanna environments. Plants 2021, 10, 2812. [Google Scholar] [CrossRef]
  17. Abadassi, J. Maize agronomic traits needed in tropical zone. Int. J. Environ. Sci. Technol. 2015, 4, 371–392. [Google Scholar]
  18. Dermail, A.; Fuengtee, A.; Lertrat, K.; Suwarno, W.B.; Lübberstedt, T.; Suriharn, K. Simultaneous selection of sweet-waxy corn ideotypes appealing to hybrid seed producers, growers, and consumers in Thailand. Agronomy 2022, 12, 87. [Google Scholar] [CrossRef]
  19. Uliana Trentin, H.; Frei, U.K.; Lübberstedt, T. Breeding maize maternal haploid inducers. Plants 2020, 9, 614. [Google Scholar] [CrossRef]
  20. Elston, R.C. A weight-free index for the purpose of ranking or selection with respect to several traits at a time. Biometrics 1963, 19, 85–97. [Google Scholar] [CrossRef]
  21. Stewart, D.W.; Dwyer, L.M.; Carrigan, L.L. Phenological temperature response of maize. Agron. J. 1998, 90, 73–79. [Google Scholar] [CrossRef]
  22. Nanda, D.K.; Chase, S.S. An embryo marker for detecting monoploids of maize (Zea mays L.). Crop. Sci. 1966, 6, 213–215. [Google Scholar] [CrossRef]
  23. Gomez, K.A.; Gomez, A.A. Statistical Procedure for Agricultural Research; John Wiley and Sons: Singapore, 1984; pp. 594–600. [Google Scholar]
  24. Acquaah, G. Principles of Plant Genetics and Breeding; Blackwell: Oxford, UK, 2006; pp. 121–134. [Google Scholar]
  25. Chaikam, V.; Nair, S.K.; Babu, R.; Martinez, L.; Tejomurtula, J.; Prasanna, M.B. Analysis of effectiveness of R1-nj anthocyanin marker for in vivo haploid identification in maize and molecular markers for predicting the inhibition of R1-nj expression. Theor. Appl. Genet. 2015, 128, 159–171. [Google Scholar] [CrossRef]
  26. Dermail, A.; Suriharn, B.; Chankaew, S.; Sanitchon, J.; Lertrat, K. Hybrid prediction based on SSR-genetic distance, heterosis and combining ability on agronomic traits and yields in sweet and waxy corn. Sci. Hortic. 2020, 259, 108817. [Google Scholar] [CrossRef]
  27. Khamphasan, P.; Lomthaisong, K.; Harakotr, B.; Scott, M.P.; Lertrat, K.; Suriharn, B. Effects of mass selection on husk and cob color in five purple corn populations segregating for purple husks. Agriculture 2020, 10, 311. [Google Scholar] [CrossRef]
  28. Dudley, J.W.; Moll, R.H. Interpretation and use of estimates of heritability and genetic variances in plant breeding. Crop. Sci. 1969, 9, 257–262. [Google Scholar] [CrossRef]
  29. Lobell, D.B.; Bänziger, M.; Magorokosho, C.; Vivek, B. Nonlinear heat effects on African maize as evidenced by historical yield trials. Nat. Clim. Change 2011, 1, 42–45. [Google Scholar] [CrossRef]
  30. Yin, Y.; Deng, H.; Wu, S. Spatial-temporal variations in the thermal growing degree-days and season under climate warming in China during 1960–2011. Int. J. Biometeorol. 2019, 63, 649–658. [Google Scholar] [CrossRef]
  31. Liu, Y.E.; Hou, P.; Xie, R.Z.; Li, S.K.; Zhang, H.B.; Ming, B.; Ma, D.L.; Liang, S.M. Spatial adaptabilities of spring maize to variation of climatic conditions. Crop. Sci. 2013, 53, 1693–1703. [Google Scholar] [CrossRef]
  32. Dahmardeh, M. Effects of sowing date on the growth and yield of maize cultivars (Zea mays L.) and the growth temperature requirements. Afr. J. Biotechnol. 2012, 11, 12450–12453. [Google Scholar] [CrossRef]
  33. Hou, P.; Liu, Y.; Xie, R.; Ming, B.; Ma, D.; Li, S.; Mei, X. Temporal and spatial variation in accumulated temperature requirements of maize. Field Crop. Res. 2014, 158, 55–64. [Google Scholar] [CrossRef]
  34. Yang, H.S.; Dobermann, A.; Lindquist, J.L.; Walters, D.T.; Arkebauer, T.J.; Cassman, K.G. Hybrid-Maize—A maize simulation model that combines two crop modeling approaches. Field Crop. Res. 2004, 87, 131–154. [Google Scholar] [CrossRef] [Green Version]
  35. Bonhomme, R.; Derieux, M.; Edmeades, G.O. Flowering of diverse maize cultivars in relation to temperature and photoperiod in multilocation field trials. Crop. Sci. 1994, 34, 156–164. [Google Scholar] [CrossRef]
  36. Jiang, W.; Thapa, S.; Jessup, K.; Hao, B.; Hou, X.; Marek, T.; Becker, J.; Bell, J.; Xue, Q. Corn response to later than traditional planting dates in the Texas high plains. Crop. Sci. 2020, 60, 1004–1020. [Google Scholar] [CrossRef]
  37. Žalud, Z.; Dubrovsky, M. Modelling climate change impacts on maize growth and development in the Czech Republic. Theor. Appl. Climatol. 2002, 72, 85–102. [Google Scholar] [CrossRef]
  38. Lizaso, J.I.; Ruiz-Ramos, M.; Rodríguez, L.; Gabaldon-Leal, C.; Oliveira, J.A.; Lorite, I.J.; Sánchez, D.; García, E.; Rodríguez, A. Impact of high temperatures in maize: Phenology and yield components. Field Crop. Res. 2018, 216, 129–140. [Google Scholar] [CrossRef] [Green Version]
  39. Derieux, M.; Bonhomme, R. Heat unit requirement for maize hybrids in Europe. Results of the European FAO subnetwork: II. Period from silking to maturity. Maydica 1982, 27, 79–96. [Google Scholar]
  40. Zhou, B.; Yue, Y.; Sun, X.; Wang, X.; Wang, Z.; Ma, W.; Zhao, M. Maize grain yield and dry matter production responses to variations in weather conditions. Agron. J. 2016, 108, 196–204. [Google Scholar] [CrossRef]
  41. Skaugen, T.E.; Tveito, O.E. Growing-season and degree-day scenario in Norway for 2021–2050. Clim. Res. 2004, 26, 221–232. [Google Scholar] [CrossRef]
  42. Iannucci, A.; Terribile, M.R.; Martiniello, P. Effects of temperature and photoperiod on flowering time of forage legumes in a Mediterranean environment. Field Crop. Res. 2008, 106, 156–162. [Google Scholar] [CrossRef]
  43. Sun, H.; Zhang, X.; Wang, E.; Chen, S.; Shao, L.; Qin, W. Assessing the contribution of weather and management to the annual yield variation of summer maize using APSIM in the north China plain. Field Crop. Res. 2016, 194, 94–102. [Google Scholar] [CrossRef]
  44. Zhou, B.; Yue, Y.X.; Sun, Z.D.; Ma, W.; Zhao, M. Maize kernel weight responses to sowing date-associated variation in weather conditions. Crop. J. 2017, 5, 43–51. [Google Scholar] [CrossRef] [Green Version]
  45. Tsimba, R.; Edmeades, G.O.; Millner, J.P.; Kemp, P.D. The effect of planting date on maize: Phenology, thermal time durations and growth rates in a cool temperate climate. Field Crop. Res. 2013, 150, 145–155. [Google Scholar] [CrossRef]
  46. Chase, S.S.; Nanda, D.K. Number of leaves and maturity classification in Zea mays L. Crop. Sci. 1967, 7, 431–432. [Google Scholar] [CrossRef]
  47. Birch, C.J.; Hammer, G.L.; Rickert, K.G. Improved methods for predicting individual leaf area and leaf senescence in maize (Zea mays). Aust. J. Agric. Res. 1998, 49, 249–262. [Google Scholar] [CrossRef]
  48. Sun, H.; Zhang, X.; Chen, S.; Pei, D.; Liu, C. Effects of harvest and sowing time on the performance of the rotation of winter wheat–summer maize in the North China Plain. Ind. Crop. Prod. 2007, 25, 239–247. [Google Scholar] [CrossRef]
  49. Chassaigne-Ricciulli, A.A.; Mendoza-Onofre, L.E.; Córdova-Téllez, L.; Carballo-Carballo, A.; San Vicente-García, F.M.; Dhliwayo, T. Effective seed yield and flowering synchrony of parents of CIMMYT three-way-cross tropical maize hybrids. Agriculture 2021, 11, 161. [Google Scholar] [CrossRef]
  50. Hunter, R.B.; Tollenaar, M.; Breuer, C.M. Effects of photoperiod and temperature on vegetative and reproductive growth of a maize (Zea mays) hybrid. Can. J. Plant Sci. 1977, 57, 1127–1133. [Google Scholar] [CrossRef]
  51. Baum, M.E.; Archontoulis, S.V.; Licht, M.A. Planting date, hybrid maturity, and weather effects on maize yield and crop stage. Agron. J. 2019, 111, 303–313. [Google Scholar] [CrossRef]
  52. Holzkämper, A.; Fuhrer, P.C.J. Identifying climatic limitations to grain maize yield potentials using a suitability evaluation approach. Agric. For. Meteorol. 2013, 168, 149–159. [Google Scholar] [CrossRef]
  53. Tanaka, W.; Angel Maddonni, G. Maize kernel oil and episodes of shading during the grain-filling period. Crop. Sci. 2009, 49, 2187–2197. [Google Scholar] [CrossRef]
  54. Tao, F.; Yokozawa, M.; Xu, Y.; Hayashi, Y.; Zhang, Z. Climate changes and trends in phenology and yields of field crops in China, 1981–2000. Agric. For. Meteorol. 2006, 138, 82–92. [Google Scholar] [CrossRef]
  55. Liu, S.; Mo, X.; Lin, Z.; Xu, Y.; Ji, J.; Wen, G.; Richey, J. Crop yield responses to climate change in the Huang-Huai Hai Plain of China. Agric. Water Manag. 2010, 97, 1195–1209. [Google Scholar] [CrossRef]
  56. Wei, T.; Zhang, T.; De Bruin, K.; Glomrød, S.; Shi, Q. Extreme weather impacts on maize yield: The case of Shanxi province in China. Sustainability 2017, 9, 41. [Google Scholar] [CrossRef] [Green Version]
  57. Peters, D.; Pendleton, J.; Hageman, R.; Brown, C. Effect of night air temperature on grain yield of corn, wheat, and soybeans. Agron. J. 1971, 63, 809. [Google Scholar] [CrossRef]
  58. Wang, Y.; Tao, H.; Tian, B.; Sheng, D.; Xu, C.; Zhou, H.; Huang, S.; Wang, P. Flowering dynamics, pollen, and pistil contribution to grain yield in response to high temperature during maize flowering. Environ. Exp. Bot. 2019, 158, 80–88. [Google Scholar] [CrossRef]
  59. Bassetti, P.; Westgate, M.E. Water deficit affects receptivity of maize silks. Crop. Sci. 1993, 33, 279–282. [Google Scholar] [CrossRef]
  60. Rattalino Edreira, J.I.; Carpici, E.B.; Sammarro, D.; Otegui, M.E. Heat stress effects around flowering on kernel set of temperate and tropical maize hybrids. Field Crop. Res. 2011, 123, 62–73. [Google Scholar] [CrossRef]
  61. Jones, R.J.; Gengenbach, B.G.; Cardwell, V.B. Temperature effects on in vitro kernel development of maize. Crop. Sci. 1981, 21, 761–766. [Google Scholar] [CrossRef]
  62. Yan, P.; Chen, Y.Q.; Sui, P.; Vogel, A.; Zhang, X.P. Effect of maize plant morphology on the formation of apical kernels at different sowing dates and under different plant densities. Field Crop. Res. 2018, 223, 83–92. [Google Scholar] [CrossRef]
  63. Cerrudo, A.; Di Matteo, J.; Fernandez, E.; Robles, M.; Pico, L.O.; Andrade, F.H. Yield components of maize as affected by short shading periods and thinning. Crop. Pasture Sci. 2013, 64, 580–587. [Google Scholar] [CrossRef]
  64. Seebauer, J.R.; Moose, S.P.; Fabbri, B.J.; Crossland, L.D.; Below, F.E. Amino acid metabolism in maize earshoots. Implications for assimilate preconditioning and nitrogen signaling. Plant Physiol. 2004, 136, 4326–4334. [Google Scholar] [CrossRef] [Green Version]
  65. Scharf, P.C.; Kitchen, N.R.; Sudduth, K.A.; Davis, J.G. Spatially variable corn yield is a weak predictor of optimal nitrogen rate. Soil Sci. Soc. Am. J. 2006, 70, 2154–2160. [Google Scholar] [CrossRef] [Green Version]
  66. Xie, M.; Tremblay, N.; Tremblay, G.; Bourgeois, G.; Bouroubi, M.; Wei, Z. Weather effects on corn response to in-season nitrogen rates. Can. J. Plant Sci. 2013, 93, 407–417. [Google Scholar] [CrossRef] [Green Version]
  67. Marković, M.; Šoštarić, J.; Josipović, M.; Atilgan, A. Extreme weather events affect agronomic practices and their environmental impact in maize cultivation. Appl. Sci. 2021, 11, 7352. [Google Scholar] [CrossRef]
  68. Westgate, M.; Lisazo, J.; Batchelor, W. Quantitative relationship between pollen-shed density and grain yield in maize. Crop. Sci. 2003, 43, 934–942. [Google Scholar] [CrossRef]
  69. Carcova, J.; Uribelarrea, M.; Borras, L.; Otegui, M.E.; Westgate, M.E. Synchronous pollination within and between ears improves kernel set in maize. Crop. Sci. 2000, 40, 1056–1061. [Google Scholar] [CrossRef]
Plants 11 02902 g001 550
Figure 1. Total rainfall, daily maximum and minimum temperatures, relative humidity, and solar radiation during the experiment in the dry season of 2020/2021 and the rainy season of 2021.
Figure 1. Total rainfall, daily maximum and minimum temperatures, relative humidity, and solar radiation during the experiment in the dry season of 2020/2021 and the rainy season of 2021.
Plants 11 02902 g001
Plants 11 02902 g002 550
Figure 2. Phenology of overall haploid inducer lines evaluated in the rainy season (RS) and the dry season (DS) expressed in days after sowing and GDD.
Figure 2. Phenology of overall haploid inducer lines evaluated in the rainy season (RS) and the dry season (DS) expressed in days after sowing and GDD.
Plants 11 02902 g002
Table
Table 1. Mean squares from the combined ANOVA on HIR, ISR, yield components, and agronomic traits across two seasons between 2020 and 2021.
Table 1. Mean squares from the combined ANOVA on HIR, ISR, yield components, and agronomic traits across two seasons between 2020 and 2021.
SOVdfHIRISRYield Components
EWELEDHCNRENKRCDKD
Season (S)110.1 **164.7 ns57,150.1 **76.9 **40.3 **6.3 **403.3 **1931.5 **10.9 **1.3 **
(14.1)(0.5)(79.5)(13.3)(60.4)(10.4)(47.4)(54.1)(47.7)(46.5)
Rep/S (a)40.141.93.70.30.00.10.41.90.00.0
(0.7)(0.5)(0.0)(0.2)(0.2)(0.7)(0.2)(0.2)(0.2)(0.9)
Genotype (G)131.8 **1674.0 **856.0 **20.9 **1.0 **2.8 **14.1**87.2 **0.5 **0.1 **
(33.0)(64.4)(15.5)(47.0)(17.9)(59.8)(21.5)(31.7)(26.6)(28.0)
G × S132.3 **767.9 **171.6 **14.8 **1.0 **1.0 **16.9 **25.7 **0.4 **0.1 **
(41.5)(29.5)(3.1)(33.4)(18.7)(22.6)(25.8)(9.4)(22.1)(21.8)
Pooled error (b)520.133.325.90.70.00.10.83.20.00.0
(10.7)(5.1)(1.9)(6.1)(2.8)(6.6)(5.2)(4.6)(3.3)(2.8)
C.V.(a)(%) 29.08.44.25.45.914.95.98.36.012.4
C.V.(b)(%) 30.87.511.38.76.313.28.510.76.36.2
SOVdfAgronomic traits
GRPSDDTADSIPHEHPTBTTBTSLSPL
Season (S)1342.5 *19.6 **1288.6 **3375.7 **29,385.2 **10,906.4 **82.4 **199.3 **2979.6 **1818.3 **
(6.3)(41.8)(57.7)(78.8)(42.4)(35.7)(14.9)(20.4)(72.3)(69.1)
Rep/S (a)424.70.12.91.598.741.90.23.44.25.9
(1.8)(0.9)(0.5)(0.1)(0.6)(0.5)(0.1)(1.4)(0.4)(0.9)
Genotype (G)13213.9 **0.7 **44.6 **46.8 **2369.2 **1234.6 **24.6 **42.8 **51.0 **29.3 **
(51.4)(19.2)(26.0)(14.2)(44.5)(52.5)(57.6)(57.0)(16.1)(14.5)
G × S1372.0 **0.9 **11.7 **9.3 **400.9 **135.5 **8.6 **11.3 **24.1 **22.8 **
(17.3)(24.2)(6.8)(2.8)(7.5)(5.8)(20.2)(15.0)(7.6)(11.3)
Pooled error (b)5224.10.13.83.366.932.50.81.22.92.2
(23.2)(13.8)(8.9)(4.0)(5.0)(5.5)(7.2)(6.1)(3.7)(4.3)
C.V.(a)(%) 5.88.33.02.27.39.84.014.07.614.0
C.V.(b)(%) 5.88.93.43.26.08.68.28.16.38.5
HIR, haploid induction rate; ISR, inducer seed rate; EW, ear weight; EL, ear length; ED, ear diameter; HC, husk cover; NRE, the number of rows per ear; NKR, the number of kernels per row; CD, cob diameter; SD, seed diameter; GR, germination rate; PSD, pollen-shed duration; DTA, days to anthesis; DSI, days to silking; PH, plant height; EH, ear height; PTB, primary tassel branch; TTB, total tassel branch; TSL, tassel length; SPL, spike length; ns, not significant; and *,**, significant at p ≤ 0.05 and p ≤ 0.01, respectively. The number within the parentheses is the percentage of sum squares to the total sum of squares.
Table
Table 2. Means of agronomic traits, yield components, and haploid induction ability in maize haploid inducers in the dry and rainy seasons.
Table 2. Means of agronomic traits, yield components, and haploid induction ability in maize haploid inducers in the dry and rainy seasons.
SeasonAgronomic Traits
GR
(%)		PSD
(d)		DTA
(d)		DSI
(d)		PH
(cm)		EH
(cm)		PTBTTBTSL
(cm)		SPL
(cm)
Dry83.3 ± 1.24.5 ± 0.161.1 ± 0.563.9 ± 0.6154.1 ± 4.077.7 ± 2.711.7 ± 0.414.8 ± 0.533.0 ± 0.622.1 ± 0.5
Rainy87.4 ± 1.33.5 ± 0.153.3 ± 0.551.2 ± 0.5116.7 ± 2.754.9 ± 2.19.7 ± 0.411.7 ± 0.421.1 ± 0.612.8 ± 0.5
p-value0.033<0.001<0.001<0.001<0.001<0.0010.0010.004<0.001<0.001
SeasonHIR
(%)		ISR
(%)		Yield Components
EW
(g)		EL
(cm)		ED
(cm)		HCNRENKRCD
(cm)		KD
(cm)
Dry1.6 ± 0.278.7 ± 1.971.1 ± 2.410.4 ± 0.23.7 ± 0.12.4 ± 0.113.0 ± 0.221.5 ± 0.52.3 ± 0.10.8 ± 0.1
Rainy0.9 ± 0.275.9 ± 4.019.0 ± 1.78.5 ± 0.52.3 ± 0.11.8 ± 0.18.6 ± 0.511.9 ± 0.81.6 ± 0.10.5 ± 0.1
p-value0.0080.562<0.0010.003<0.0010.007<0.001<0.001<0.001<0.001
Values are means ± SE. GR, germination rate; PSD, pollen-shed duration; DTA, days to anthesis; DSI, days to silking; PH, plant height; EH, ear height; PTB, primary tassel branch; TTB, total tassel branch; TSL, tassel length; SPL, spike length; HIR, haploid induction rate; ISR, inducer seed rate; EW, ear weight; EL, ear length; ED, ear diameter; HC, husk cover; NRE, the number of rows per ear; NKR, the number of kernels per row; CD, cob diameter; and KD, kernel diameter.
Table
Table 3. Means of 14 haploid inducers on haploid induction rate (HIR) and inducer seed rate (ISR) evaluated in the dry season of 2020/2021 and the rainy season of 2021.
Table 3. Means of 14 haploid inducers on haploid induction rate (HIR) and inducer seed rate (ISR) evaluated in the dry season of 2020/2021 and the rainy season of 2021.
GroupHaploid InducersDry SeasonRainy Season
HIR
(%)		ISR
(%)		HIR
(%)		ISR
(%)
HighKHI 491.8 cd (A)74.0 bc (A)0.0 e (B)82.9 b (A)
KHI 590.8 ef (A)81.3 b (A)0.3 e (B)88.7 ab (A)
KHI 542.5 bc (A)62.5 de (B)0.9 d (B)72.8 c (A)
KHI 420.8 ef (B)93.6 a (A)1.8 a (A)95.2 a (A)
KHI 471.7 cd (A)94.2 a (A)1.6 ab (A)92.1 ab (A)
ModerateKHI 51.8 cd (A)92.0 a (A)0.0 e (B)95.6 a (A)
KHI 653.4 a (A)71.4 cd (A)0.0 e (B)66.4 cd (A)
KHI 663.3 ab (A)75.2 bc (A)1.5 ab (B)53.5 e (B)
KHI 501.1 def (B)81.0 bc (A)1.8 a (A)61.0 de (B)
KHI 800.6 f (A)63.8 de (A)0.0 e (B)0.0 f (B)
LowKHI 561.0 def (B)79.4 bc (B)1.5 ab (A)97.5 a (A)
KHI 610.4 f (B)80.9 bc (A)0.9 d (A)71.9 c (A)
KHI 721.5 de (A)60.7 e (B)1.3 bc (A)94.3 a (A)
KHI 551.7 d (A)91.8 a (A)1.0 cd (B)90.6 ab (A)
Means with different letters outside parenthesis in the same column are significantly different by Duncan’s multiple range test (DMRT) at 0.05 probability level. Means with different letters within parenthesis in the same row and trait are significantly different by Tukey’s honest significant difference test (HSD) at 0.05 probability level.
Table
Table 4. Brief profiles of fourteen Stock-6-derived inducer lines used in this study.
Table 4. Brief profiles of fourteen Stock-6-derived inducer lines used in this study.
No.GenotypesPedigreeGroup 1
1KHI 49WST/Stock6-S(C6)-IDLT2A-28-BHigh
2KHI 59WST/Stock6-S(C6)-IDLT2A-WS-BHigh
3KHI 54WST/Stock6-S(C6)-IDLT2A-34-1-BHigh
4KHI 42TL/Stock6-S(C6)-IDLT1B-93-BHigh
5KHI 47WST/Stock6-S(C6)-IDLT2A-24-BHigh
6KHI 5NSX/Stock6-S(C6)-IDLT1A-110-BModerate
7KHI 65KND/Stock6-S(C6)-IDLT2B-22-BModerate
8KHI 66TB/Stock6-S(C6)-IDLT3-4-BModerate
9KHI 50WST/Stock6-S(C6)-IDLT2A-29-BModerate
10KHI 80TB/Stock6-S(C6)-IDLT4-4-BModerate
11KHI 56WST/Stock6-S(C6)-IDLT2A-36-BLow
12KHI 61KND/Stock6-S(C6)-IDLT2B-15-BLow
13KHI 72TB/Stock6-S(C6)-IDLT4-24-BLow
14KHI 55WST/Stock6-S(C6)-IDLT2A-35-BLow
1 Based on unweighted selection index (z) of three attributes, namely, HIR, inducer seed rate, and agronomic score. High: genotypes with z ≥ 2.5; moderate: genotypes with 0.5 < z < 2.5; and low: genotypes with z ≤ 0.5.
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Sintanaparadee, P.; Dermail, A.; Lübberstedt, T.; Lertrat, K.; Chankaew, S.; Ruanjaichon, V.; Phakamas, N.; Suriharn, K. Seasonal Variation of Tropical Savanna Altered Agronomic Adaptation of Stock-6-Derived Inducer Lines. Plants 2022, 11, 2902. https://doi.org/10.3390/plants11212902

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Sintanaparadee P, Dermail A, Lübberstedt T, Lertrat K, Chankaew S, Ruanjaichon V, Phakamas N, Suriharn K. Seasonal Variation of Tropical Savanna Altered Agronomic Adaptation of Stock-6-Derived Inducer Lines. Plants. 2022; 11(21):2902. https://doi.org/10.3390/plants11212902

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Sintanaparadee, Paepan, Abil Dermail, Thomas Lübberstedt, Kamol Lertrat, Sompong Chankaew, Vinitchan Ruanjaichon, Nittaya Phakamas, and Khundej Suriharn. 2022. "Seasonal Variation of Tropical Savanna Altered Agronomic Adaptation of Stock-6-Derived Inducer Lines" Plants 11, no. 21: 2902. https://doi.org/10.3390/plants11212902

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