High-yielding Lines Research Articles

The Role of Phytohormones in Plant Response to Flooding.

Climatic variations influence the morphological, physiological, biological, and biochemical states of plants. Plant responses to abiotic stress include biochemical adjustments, regulation of proteins, molecular mechanisms, and alteration of post-translational modifications, as well as signal transduction. Among the various abiotic stresses, flooding stress adversely affects the growth of plants, including various economically important crops. Biochemical and biological techniques, including proteomic techniques, provide a thorough understanding of the molecular mechanisms during flooding conditions. In particular, plants can cope with flooding conditions by embracing an orchestrated set of morphological adaptations and physiological adjustments that are regulated by an elaborate hormonal signaling network. With the help of these findings, the main objective is to identify plant responses to flooding and utilize that information for the development of flood-tolerant plants. This review provides an insight into the role of phytohormones in plant response mechanisms to flooding stress, as well as different mitigation strategies that can be successfully administered to improve plant growth during stress exposure. Ultimately, this review will expedite marker-assisted genetic enhancement studies in crops for developing high-yield lines or varieties with flood tolerance.

Improving Agricultural Traits While Maintaining High Resistant Starch Content in Rice

BackgroundResistant starch (RS) is beneficial for human health. Loss of starch branching enzyme IIb (BEIIb) increases the proportion of amylopectin long chains, which greatly elevates the RS content. Although high RS content cereals are desired, an increase in RS content is often accompanied by a decrease in seed weight. To further increase the RS content, genes encoding active-type starch synthase (SS) IIa, which elongates amylopectin branches, and high expression-type granule-bound SSI (GBSSI), which synthesizes amylose, were introduced into the be2b mutant rice. This attempt increased the RS content, but further improvement of agricultural traits was required because of a mixture of indica and japonica rice phonotype, such as different grain sizes, flowering times, and seed shattering traits. In the present study, the high RS lines were backcrossed with an elite rice cultivar, and the starch properties of the resultant high-yielding RS lines were analyzed.ResultsThe seed weight of high RS lines was greatly improved after backcrossing, increasing up to 190% compared with the seed weight before backcrossing. Amylopectin structure, gelatinization temperature, and RS content of high RS lines showed almost no change after backcrossing. High RS lines contained longer amylopectin branch chains than the wild type, and lines with active-type SSIIa contained a higher proportion of long amylopectin chains compared with the lines with less active-SSIIa, and thus showed higher gelatinization temperature. Although the RS content of rice varied with the cooking method, those of high RS lines remained high after backcrossing. The RS contents of cooked rice of high RS lines were high (27–35%), whereas that of the elite parental rice was considerably low (< 0.7%). The RS contents of lines with active-type SSIIa and high-level GBSSI expression in be2b or be2b ss3a background were higher than those of lines with less-active SSIIa.ConclusionsThe present study revealed that backcrossing high RS rice lines with elite rice cultivars could increase the seed weight, without compromising the RS content. It is likely that backcrossing introduced loci enhancing seed length and width as well as loci promoting early flowering for ensuring an optimum temperature during RS biosynthesis.

Indirect early generation selection for yield in winter wheat

Early generation selection (EGS) aims to accelerate genetic yield gain by applying selection pressure for desirable traits at early generations within breeding programmes. This study was designed to evaluate single plant yield (SPY), harvest index (HI; SPY divided by aboveground biomass) and estimated fruiting efficiency (FE m ; kernels per unit chaff weight) as EGS traits in predominantly F3 populations of winter wheat. Lines were sown as single plants and in plots of pooled family seed in northwest Victoria, Australia in 2018. From the single plant populations, 21–23 lines were selected for each EGS trait and 52 lines were selected at random to estimate true population mean; 25 lines were selected visually from pooled plots. Selected lines were sown in partially replicated plots in 2019. Lines selected for HI yielded 24% more than lines selected at random and 22% more than lines selected visually; selections made for SPY and FE m yielded the equivalent of HI selections, but not significantly higher than the random or visual treatments. In 2020, the 7 highest-yielding lines from the HI, random and visual selection treatments were sown in replicated plots. There was no significant difference in yield between treatments. Nevertheless, EGS for HI successfully culled low yielding lines, and enriched populations with high yielding lines prior to plot-level yield testing. Advancements in high-throughput phenotyping are required before widespread adoption but are anticipated in the near future.

Utilization of Intra-Cultivar Variation for Grain Yield and Protein Content within Durum Wheat Cultivars

This study assessed the variations in grain yield (GY) and protein content (PC) within two commercial durum wheat cultivars (Svevo and Maestrale) and evaluated their responses to intra-cultivar selection for both traits. We investigated whether the variations are exploitable and could result in concurrent GY and PC upgrading. The experiments were conducted in the IPBGR, Thessaloniki, Greece (2018–2020). The first year included two identical honeycomb design trials under ultra-low plant density (ULD) where the divergent selection was applied based on single plant yield and protein content. In the second year, progeny evaluation under typical crop density (TCD) for GY and PC occurred in a randomized complete block (RCB) and with three replications for each cultivar selected line. This revealed considerable variation within already improved commercial cultivars. Single-plant selection for GY and PC simultaneously resulted in: (a) one high-yielding line that significantly outperformed the original cultivar Svevo while maintaining high PC, and (b) two high-grain PC lines that outperformed the original cultivar Maestrale significantly while maintaining high GY. ULD allowed efficient selection for GY and PC simultaneously within narrow gene pools by maximizing phenotypic expression and differentiation among individual plants.

Detection of Maternal and Cytoplasmic Effects on Resistance to Zymoseptoria tritici in Durum Wheat.

Septoria tritici blotch (STB) is a major disease problem of wheat worldwide. To optimize the introgression of resistance genes in elite genotypes throughout traditional or molecular breeding programs, a full understanding of the quantitative inheritance of resistance to Zymoseptoria tritici, plant height (PH), and thousand kernel weight (TKW) is needed. In this study, maternal and cytoplasmic effects of resistance to STB were investigated using P1 (susceptible, high-yielding line) and P2 (resistant, low-yielding line) durum wheat lines and their F1, RF1, F2, RF2, BC1, RBC1, BC2, and RBC2 progeny, assessed for resistance to STB during three growing seasons. Duncan mean's analysis revealed significant differences between generation means for STB, PH, and TKW. The two parents had an extreme pattern. The F1 and RF1 segregated close to their respective parents, suggesting the presence of cytoplasmic and maternal genetic effects for Z. tritici resistance, PH, and TKW. Separate generation mean's analysis confirmed the results of the Duncan test. A three-parameter model was found to be not adequate for all traits in all three growing years; while a digenic epistatic model with cytoplasmic or/and maternal effect was adequate for all cases. Narrow-sense heritability was in the range of 50–60%, 30–69%, and 28–31% for STB, PH, and TKW, respectively. For STB, high heritability and the presence of fixable epistatic effect is encouraging and could lead to creating varieties with the right female parent to exploit cytoplasmic and maternal effects in order to improve resistance to Z. tritici in durum wheat.

Multivariate Analysis of Agronomic Traits in M4 Generation of Aromatic Rice Lines.

&lt;b&gt;Background and Objective:&lt;/b&gt; Developing rice (&lt;i&gt;Oryza sativa&lt;/i&gt; L.) varieties with increased yield potential has been a major concern for genetic improvement. This study aimed to evaluate aromatic rice lines and the relationship among their twelve agronomic traits using heatmap Pearson correlation and multivariate analysis to identify high yield lines using grain yield as a marker-trait. &lt;b&gt;Materials and Methods:&lt;/b&gt; Twelve aromatic rice genotypes (eleven mutant lines and one control) were evaluated in the M&lt;sub&gt;4&lt;/sub&gt; generation. The experiment was conducted at Tana Toraja regency following Randomized Complete Block Design (RCBD) with two replications. &lt;b&gt;Results:&lt;/b&gt; The darker and lighter colour scale produced by heatmap revealed contrasting nature of genotypes. A significant positive correlation observed for yield was the number of fertile grains and grain weight per panicle, while a negative correlation was days to flowering. The first four components account for 83.46% of the total cumulative variation. Cluster analysis grouped 11 lines and one control into three clusters. &lt;b&gt;Conclusion:&lt;/b&gt; The results concluded that the PB-A.5.3.45 line could be used for hybridization programs to develop high-yielding mutant-derived aromatic rice varieties for further improvement.

Capturing Genetic Variability and Identification of Promising Drought-Tolerant Lines in Exotic Landrace Derived Population Under Reproductive Drought Stress in Rice.

Drought is one of the most predominant abiotic stresses in this century, leading to a drastic reduction in the yield of rainfed rice ecosystems. Breeding of drought-resilient rice varieties is very much in demand for sustainable rice production in drought-prone rainfed ecology. An experiment was designed under irrigated non-stress and drought-stress situations involving an exotic drought-tolerant landrace (Chao Khaw) and a high-yielding aromatic rice cultivar (Kasturi), and an F2:4 derived population of 156 breeding lines was developed at IRRI South Asia Hub, Hyderabad. The objective of the study was to assess the genetic variability, drought tolerance behavior, and identify promising breeding lines for different rice ecologies and drought breeding programs. Restricted maximum likelihood (REML) analysis using the mixed model approach revealed a considerable genetic variation in the population for yield and yield contributing traits in non-stress and drought-stress conditions. We observed very high heritability for all the selected traits under stress 2015 WS (73.8% to 85.3%) and 2016 WS (72.4% to 93.5%) and non-stress 2015 WS (68.2% To 92.9%) and 2016 WS (61.4% to 92.6%) environments, indicating possible selection for grain yield under drought stress and non-stress with the same precision level. None of the secondary traits except harvest index and biomass included in our study showed a positive association with grain yield, indicating indirect selection’s ineffectiveness in improving yield under drought. A total of 48 promising breeding lines were found to have a better yield than donor Chao Khaw (up to 38% advantage) and popular drought-tolerant cultivars Shabhagidhan (up to 48% advantage) in stress conditions and recommended for rainfed upland ecology, 34 breeding lines under the well-watered condition suited for rainfed lowland ecology. Overall, the study found 21 common breeding lines that showed their superiority in non-stress and under drought stress situations, fitting best in rainfed lowland ecology with occasional drought occurrence. The large genetic variation found in this population can be exploited further to develop a few forward breeding high-yielding lines with better drought tolerance ability and used as drought donors in drought breeding programs.

Study on the inheritance of oleic acid content in reciprocal F1 hybrids of winter rapeseed at V.S. Pustovoit All-Russian Research Institute of Oil Crops

The purpose of the research was to study the inheritance of the trait of oleic acid content in oil of winter rapeseed seeds in reciprocal F1 hybrids. We carried out the research in 2019-2020 under field and greenhouse conditions. We used two high oleic lines for hybridization: BH 1844 (82.2 %) and BH 1848 (83.0 %), and two high-yielding lines from the varieties Sarmat and Selegor with a standard level of oleic acid of 62.1 and 60.5 %, respectively. Analysis of the C18:1 content of F1 hybrids, under field conditions, showed that in the case of crossing high oleic lines BH 1844 and BH 1848 with high-yielding lines from the varieties Sarmat and Selegor, five of eight combinations had an intermediate type of inheritance (h/d from -0.10 to 0.28). In the remaining three cases there was incomplete dominance of the trait (h/d from 0.56 to 0.64). We carried out similar studies in the phytotron greenhouse complex. On average, the content of C18:1 in the greenhouse conditions was 5.5 % lower in the high oleic lines, 0.3 % lower in the variety Sarmat, and 0.9 % lower in the variety Selegor, as oleic acid is synthesized less intensively at low air temperature. All the combinations of the greenhouse conditions showed an intermediate type of inheritance (h/d from -0.43 to 0.48). With this type of inheritance, lines combining high yield with high content of oleic acid can be isolated in the future.

Prediction of plant-level tomato biomass and yield using machine learning with unmanned aerial vehicle imagery

BackgroundThe objective of this study is twofold. First, ascertain the important variables that predict tomato yields from plant height (PH) and vegetation index (VI) maps. The maps were derived from images taken by unmanned aerial vehicles (UAVs). Second, examine the accuracy of predictions of tomato fresh shoot masses (SM), fruit weights (FW), and the number of fruits (FN) from multiple machine learning algorithms using selected variable sets. To realize our objective, ultra-high-resolution RGB and multispectral images were collected by a UAV on ten days in 2020’s tomato growing season. From these images, 756 total variables, including first- (e.g., average, standard deviation, skewness, range, and maximum) and second-order (e.g., gray-level co-occurrence matrix features and growth rates of PH and VIs) statistics for each plant, were extracted. Several selection algorithms (i.e., Boruta, DALEX, genetic algorithm, least absolute shrinkage and selection operator, and recursive feature elimination) were used to select the variable sets useful for predicting SM, FW, and FN. Random forests, ridge regressions, and support vector machines were used to predict the yield using the top five selected variable sets.ResultsFirst-order statistics of PH and VIs collected during the early to mid-fruit formation periods, about one month prior to harvest, were important variables for predicting SM. Similar to the case for SM, variables collected approximately one month prior to harvest were important for predicting FW and FN. Furthermore, variables related to PH were unimportant for prediction. Compared with predictions obtained using only first-order statistics, those obtained using the second-order statistics of VIs were more accurate for FW and FN. The prediction accuracy of SM, FW, and FN by models constructed from all variables (rRMSE = 8.8–28.1%) was better than that from first-order statistics (rRMSE = 10.0–50.1%).ConclusionsIn addition to basic statistics (e.g., average and standard deviation), we derived second-order statistics of PH and VIs at the plant level using the ultra-high resolution UAV images. Our findings indicated that our variable selection method reduced the number variables needed for tomato yield prediction, improving the efficiency of phenotypic data collection and assisting with the selection of high-yield lines within breeding programs.

Yield Stability of Different Elite Wheat Lines under Drought and Irrigated Environments using AMMI and GGE Biplots

Wheat is the principal winter crop in Nepal. Drought affects 44% of the lands of the total wheat area in the country with a yield loss of 15–20%. This research focuses to minimize this loss through the identification of high-yielding lines stable across the drought stress and irrigated environments. The experiment was conducted in Alpha Lattice Design with 20 genotypes replicated twice with five blocks per replication from November 2019 to April 2020. The findings showed that genotypes, environments, and genotype-environment interaction have a highly significant effect on grain yield and explained 28.95%, 52.57%, and 18.47% of variation on yield, respectively. The which-won-where model revealed elite line NL 1420 is the most responsive line in the drought environment, followed by BL 4407, while elite line NL 1179 is the most stable line in irrigated environment. The mean vs stability model with principal component 1 and 2 explaining 65.76% and 34.24% respectively, showed that elite line NL 1420, BL 4407, BL 4919, Bhrikuti are both high yielding and stable lines while line NL 1179, Gautam, and NL 1384 are less stable in both test environments. Similarly, the ranking genotypes model indicated lines close to the ideal line are NL 1420, BL 4407, BL 4919, Bhrikuti as the most representative line for genotype evaluation. Thus, elite wheat line NL 1420 and NL 1179 are recommended as specifically adapted to drought and irrigated environments, respectively, and elite line NL 1420, BL 4407, BL 4919, Bhrikuti are recommended for further evaluation for stability.&#x0D; Int. J. Appl. Sci. Biotechnol. Vol 9(2): 98-106

AMMI and GGE biplot analysis of yield of different elite wheat line under terminal heat stress and irrigated environments

Wheat crop contributes to a major portion of the agriculture economy of Nepal. It is ranked as the third major cereal crop of the country even though, it faces terminal heat stress which speeds up the grain filling rate and shortens the filling period, causing reduction in grain weight, size, number and quality losses. We can minimize this loss through a genotypic selection of high-yielding lines by understanding the genotype-environment interaction. The objective of this research is to obtain a high yielding line with a stable performance across the environments. In order to do so, we conducted an experiment using eighteen elite wheat lines and two check varieties in alpha-lattice design with two replications in different environments viz. irrigated and terminal heat stress environment from November 2019 to April 2020. The analysis of variance revealed that genotype, environment and their interaction had a highly significant effect on the yield. Furthermore, the which-won–where model indicated specific adaptation of elite lines NL 1179, NL 1420, BL 4407, NL 1368 to the irrigated environment and Bhirkuti to the terminal heat-stressed environment. Similarly, the mean-versus-stability study indicated that elite lines BL 4407, NL 1368, BL 4919, NL 1350, and NL 1420 had above-average yield and higher stability whereas elite lines Gautam, NL 1412, NL 1376, NL 1387, NL 1404, and NL 1381 had below-average yield and lower stability. The ranking of elite lines biplot, PC1 explaining 73.6% and PC2 explaining 26.4% of the interaction effect, showed the rank of elite line, NL 1420 > NL 1368> NL 1350 > other lines, close to the ideal line. On the basis of the obtained results, we recommend NL 1420 with both the high yield and stability is suited across both the environments, while NL 1179 and Bhirkuti is adapted specifically for irrigated and terminal heat stress environment, respectively.

Individual Selection Soybean (Glycine max L.) The Genotype of Cross Argomulyo and Tanggamus Based on Character of Yield Component

Selection is one of plant breeding techniques to obtain a desired character. The objective of this research was to determine information about the trait variance in F3 lines in terms of yield and yield components, knowing character could be improved through selection to obtain high yield lines. This study was conducted on june until august 2020 in the village Karang Bangun Rambung Merah Kecamatan Pematangsiantar, kabupaten Simalungun 500-550 with an elevation place, use augmented design. 20 × 30 cm plant distance, data observed for each individual plant, and done to find genetic variance, environment variance, phenotif variance, GCV, broad-sense heritability and Coefficient correlation. The result show that the value of heritability all character was moderate until high except the days of harvest was low. The value of GCV was narrow to the days to flowering and harvest, while other character value of the GCV was moderate until broad. Coefficient correlation indicated that Seed weight per plant was positively and significantly correlated with all studied traits except the days to flowering was negative and non-significant. Based on high heritability and broad GCV, selection process on seed weight per plant so 10 selected lines with highest seed weight.

Two Novel QTLs for the Harvest Index that Contribute to High-Yield Production in Rice (Oryza sativa L.)

BackgroundThe harvest index (HI) is a measure of the biological success of forming harvestable products. However, our understanding of the genetic basis of HI in rice (Oryza sativa L.) is limited, because it is a complex trait consisting of various yield-related traits and physiological attributes. YTH183 is a high-yielding line with large panicles and high HI derived from a cross between the Indica Group variety IR 64 and the NPT line IR 69093-41-2-3-2 (YP5).ResultsHere, we detected two novel QTLs for HI, designated qHI5.1 on chromosome 5 and qHI8.1 on chromosome 8, by using 155 recombinant inbred lines (RILs) derived from the cross between IR 64 and YTH183. The YTH183 allele at qHI5.1 contributed to a wide grain, resulting in heavy grain weight and panicle weight, and was consistently effective under the different environmental conditions of subtropical (Ishigaki) and temperate (Tsukuba) regions. Genetic polymorphism revealed that qHI5.1 was identical to GSE5/GW5, which is known to control the grain weight. On the other hand, although qHI8.1 functioned additively with qHI5.1 for higher HI, it did not show any significant effect on grain or panicle weight. In addition, its effects on HI were shown only in the first seasons at Ishigaki but not at Tsukuba or in the second season at Ishigaki.ConclusionOur results indicate that qHI5.1 controls the grain size, regardless of whether environmental conditions are of subtropical or temperate regions, while qHI8.1 might be involved in controlling the physiological processes of source ability or the translocation of photosynthesis products from vegetative organs to grains depending on environmental conditions during the maturing stage. These QTLs will be useful genetic resources for future breeding programs to break through the ceiling of maximum yield in Indica Group varieties.

New selection strategies for determining the traits contributing to increased grain yield in wheat (Triticum aestivum L.) under aluminum stress

Finding the suitable traits that mediate grain yield under stress condition represent an important challenge to plant breeders in order to improve production. Meaningful progress in computational analysis enables us to solve this challenge in a more efficient way. In this frame of study, our objective was to determine the most important traits associated with wheat yield improvement under aluminum stress using attribute weighting as well as supervised algorithms. To meet this goal, we studied, under normal and stress conditions, 167 bread wheat recombinant inbred lines. The lines were obtained from a cross of two semi-dwarf spring wheat varieties featured with considerable yield potential; Seri M82 and Babax. A total of 50 different traits including phenological, morphological, agronomic, physiological and biochemical traits were recorded. Ranking traits by attribute weighting algorithms indicated that among the 50 traits, five and eight traits were respectively the most probable candidates under normal and stress conditions, as highlighted by at least six weighting algorithms. According to the performance of decision tree algorithms employed, traits that were pinpointed traits by attribute weighting can be utilized to efficiently discriminate high-, medium-, and low- yield lines with up to 74.92% and 81.47% under normal and stress conditions, respectively. Moreover, valuable basis can be extrapolated from our decision tree models to guide plant breeders for selecting high yield lines going by the key traits highlighted herein. In addition, having an early prediction of yield helps farmers to make informed decision and take efficient steps to improve grain yield.

High-yielding varieties and lines for breeding durum wheat

High-yielding varieties and lines for breeding durum wheat

Normalization method for canopy temperature as an indirect indicator of yield potential in wheat breeding programs.

Canopy temperature (CT) is often related to potential yield and is a possible yield indicator in breeding programs. However, it is difficult to evaluate genetic variations of CT accurately in large-scale investigations, such as breeding programs, because CT is strongly affected by environmental conditions. In this study, to precisely evaluate these genetic variations, we determined the environmental factors that affect CT measurement and proposed a convenient normalization method to minimize their influence. We measured the CT of CT-high or CT-low cultivars in the field under various conditions. We found that as the sun and shade levels were alternated, the CT changed within seconds; the position in the field also critically affected the CT. However, even under these conditions, the differences between cultivars became clearer if CT was normalized by neighboring lines. Additionally, we revealed that CT measurements between 12:00 and 15:00 maximized the difference between cultivars. Using our normalization technique under the favorable conditions specified can help breeders select high-yield lines using CT in breeding programs.

Development of high-yielding soybean lines by using marker-assisted selection for seed yield and lodging tolerance

Genetic analysis of seed yield is important in the breeding of high-yielding cultivars in soybean (Glycine max (L.) Merr.). Generally, the number of quantitative trait loci (QTLs) associated with seed yield, even in a single population, is high, and thus, the effect of each QTL is small. Lodging tolerance is an important trait that affects yield because soybean plants with higher aboveground weights are easily lodged. We previously identified eight QTLs associated with seed yield and a QTL associated with lodging tolerance, qLS19-1, by using a recombinant inbred line (RIL) population derived from a cross between Japanese cultivars Toyoharuka and Toyomusume. There were significant positive correlations over 3 years between seed yield and the number of favourable alleles at QTLs associated with seed yield in the RILs. The aim of this study was to develop high-yielding lines by using marker-assisted selection for seed yield and lodging tolerance. Six pyramiding lines with favourable alleles at seven QTLs associated with seed yield and qLS19-1 were developed from a cross between two RILs in the same population. The seed yields of six pyramiding lines tended to be greater than those of Toyoharuka (114–124%) and Toyomusume (108–117%) in a 2-year yield trial. Four of the six pyramiding lines produced significantly higher yields and were later maturing than both Toyoharuka and Toyomusume. Our results suggest that marker-assisted selection for seed yield and lodging tolerance in the same population will be effective for high-yield breeding.

Money Questions and the Structural Interview.

Kernberg's structural interview integrates exploration of elements of personality organization into the standard initial psychiatric evaluation. The structural interview approach, while essential to transference-focused psychotherapy for patients with borderline personality disorder, is not limited to use in that context. Following the model of the structural interview, clinicians ask a series of questions, which elucidate elements of personality pathology, thereby facilitating comprehensive diagnosis, guiding treatment, and informing prognosis. Direct questioning about finances and the clinician's general curiosity about issues related to money, in the context of the structural interview, can be high-yield lines of inquiry. Patients' history with their finances, attitudes about money, and ways questions about finance emerge in the transference around fees and related concerns, can add an important, often overlooked, dimension to the assessment of personality organization and personality disorder pathology. This article proposes the utility of prioritizing questions regarding money, as might be integrated into the structural interview, as a template for a broader recognition of the value of this line of inquiry in a diagnostic assessment process.

Recent Advancements in Near-Infrared Perovskite Light-Emitting Diodes

Metal halide perovskites have shown excellent properties for lighting applications, including high photoluminescence quantum yield (PLQY), compositional tunability, and narrow emission line widths....

Analysis of Combining Ability for Early Maturity and Yield in Rice (Genus: Oryza) at the Kenyan Coast

The main challenges facing rain-fed rice farming in Kilifi County at the Kenyan coast are inadequate and erratic rainfall, inadequate skills, and poorly developed infrastructure. Of great importance is erratic rainfall that tends to depress towards the end of long rain season, leading to crop failure. Combining ability analysis is one of the most valuable tools used to ascertain gene action effects and help in selecting desirable parents for making crosses and coming up with high yielding and early maturing lines. Combining ability for early maturity and yield has not been studied at the Kenyan coast. This study aimed at determining and identifying good, general, and specific combiners for selecting better parents and better cross combinations in rice crops for developing high yield and short duration lines in rain-fed rice farming. Seven lines were subjected to half-diallel mating design at the Kenya Agricultural and Livestock Research Organization (KALRO), Mtwapa, and at Bahari in Kilifi town. Evaluation for general combining ability (GCA) and specific combining ability (SCA) analysis was done. Combining ability variance and GCA and SCA effects were determined. Based on GCA effects, best parent for early maturity was Dourado Precoce, while for yield, Supaa, Komboka, and NERICA 10. SCA estimates indicated that best crosses for yield were D/S, D/N1, and K/N10, while the best performing cross for early maturity was D/N1.