Multi-trait selection index for high clonal cashew (Anacardium occidentally. L.) yield performance

Multi-trait selection index for high clonal cashew (Anacardium occidentally. L.) yield performance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Multi-trait selection index for high clonal cashew (Anacardium occidentally. L.) yield performance Paul K. K. Adu-Gyamfi, Abraham Akpertey, Godfred Awudzi, Solomon Agyare, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9210569/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The breeding of cashew varieties is expensive and time-consuming and the identification of a selection criterion that could rely on juvenile traits to effectively select for superior clones in later years of production could constitute a viable strategy to sustain production. We evaluated 20 cashew clones of varied origins over a 9 - year period under sub-optimal and near-optimal environment for growth and yield traits respectively. The trial was laid out in a randomized complete block design with four replications. There were significant clone × environment interaction effects for most traits. Under sub-optimal environment, high genotypic correlations were found between overall yield and survival, height, canopy volume, nut weight and the first 2-years, 3-years, 4-years, 5-years and 6-years of production whereas under near-optimal environment height, canopy volume, first 2-years, 3-years, 4-years, 5-years and 6 years of production years were high. Heritability ranged from 0.10–0.51, 0.11–0.52 and 0.20–0.74 for vegetative traits, nut quality traits and yield across years of production respectively. Under sub-optimal environment, selection for survival, height with rapidly expanding canopies and yield during the first 2 years of production were effective whereas under near-optimal environment selection for height with rapidly expanding canopies, shelling and yield during the first 2 years of production were effective. Our study suggest that the set of traits optimal for selection of high yield performers could vary with ecology and the identified criterion has a large potential to identify the most productive clones early in the cashew breeding program. Heritability Anacardium occidentalli. L climate change selection index Biennial bearing Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Cashew ( Anacardium occidentale L.) is perennial nut tree crop belonging to the family Anacardiaceae (mangoes and pistachios family). It originated from North-Eastern Brazil (Mitchell and Mori 1987), and was introduced into West Africa by the early Portuguese settlers in the 16th and 19th century. Currently, over 50% of the raw cashew nut (RCN) produced globally is dominated by West African producing countries and Ivory coast is the leading producer with substantial productions from Nigeria, Ghana, Benin, Burkina Faso, Tanzania, and Guinea-Bissau (ACA 2022 ; Awuah 2022 ). The crop is highly valued for their nuts and the global consumption of these nuts has doubled over a period of ten years and this has been attributed to both their health benefits in preventing heart diseases and the shift in preference of vegan diet over non-vegan diet (Sushma et al. 2025 ). The value of cashew in reducing poverty, boosting rural development and as a major foreign exchange earner for most developing producing countries has been emphasize d(Eze et al. 2023 ; Hinnou et al. 2022 ; Yin et al. 2023 ) . Cashew adapts well to different ecological zones (Dedzoe et al. 2001 ), however, it requires an annual rainfall of 800–2000 mm (Sys et al. 1993) coupled with a well-drained deep light to medium textured soils (Dedzoe et al. 2001 ) with a pH range of 4.5–6.5 (Dendena and Corsi 2014 ) and a temperature range of 25–28 ᵒC (Dendena and Corsi 2014 ) with a pronounced dry period of 5–6 months (Dedzoe et al. 2001 ) for optimum productivity. Nevertheless, long breeding cycles, weak juvenile - mature correlations, changes in climate, market demands and emerging pest and disease pressures, pose, however, daunting challenges. The breeding of a perennial crop like cashew is an expensive and time-consuming due to their large tree size and lengthy juvenile phase (Migicovsky and Myles 2017 ). A typically grafted cashew clone will start bearing in the 3rd year after planting, reach full bearing in the 10th year and continue to give remunerative yields for 20 years (Agrifarming 2020 ). Similarly, tree crops like avocado ( Persea americana ) took up to 15 years to mature before flowering (Janick and Moore 1996 ) while the breeding of some commercial apple ( Malus domestica ) cultivars took about 26 years (Peil et al. 2008 ). It is therefore common for a limited number of elite cashew varieties to be propagated widely by farmers over long periods of time. The propagation of the same cashew cultivars over time, could lead to increasing susceptibility to drought and diseases, since these crops remain genetically frozen while environmental conditions continue change and pathogen continue to evolve. A common strategy employed by plant breeders to maximize genetic gains per unit time and reduce the long breeding cycles in many tree crop breeding programs has been the development of a selection index that could identify the most productive clones early in the breeding program than relying of data in the later years of production. This strategy has been successfully applied to tree crops like Cocoa ( Theobroma cacao L.) (Padi et al. 2012 ) and Kola ( Cola nitida (Vent) (Akpertey et al. 2017 ). In cashew, selection indices for the development of superior varieties have mostly relied on several traits over several years of data collection, until final varietal recommendations are made (Nkumbula et al. 2023 ; Piria and Manivannan 2001 ). Others have also relied on vegetative traits correlations with early yield traits to select the most productive clones. (Adu-Gyamfi et al. 2019 ). Adeigbe et al. ( 2016 ) has therefore emphasized that by combining these different traits into a comprehensive index, cashew breeders can more effectively identify elite varieties that maximize economic benefits for farmers and processors early in the breeding program than relying on yield data in later years of production. Most tree crop breeding programs aim to improve multiple valuable traits, however, they tend to overlook firstly, the value of each trait in a particular environment, secondly the genotypic correlation among traits and thirdly the varying heritability’s estimates which often leads to sub-optimal selection response (Grattapaglia et al. 2018 ). While selecting for traits with conflicting response can be misleading, as progress in one might harm the other, selecting for traits with synergistic correlations between two or more traits can bias the selection against the remaining traits (Grattapaglia et al. 2018 ). Therefore, the development of a robust selection index that relies on juvenile traits, heritability estimates, together with a favorable genotypic association with yield in later years of production could constitute a viable strategy to reduce the lengthy cashew breeding programs and subsequently save financial resources. The Ghana Cashew Breeding Research Program has planted cashew field gene banks with over 2000 accessions of both local and exotic origin at the Bole Research stations in the Guinea savannah ecological zone and Wenchi Agricultural research station in the Forest transitional zone (Adu-Gyamfi et al. 2019 ; Dadzie et al. 2014 ). Here, we report on a selection criterion that relies on the use of a set of juvenile traits that could be effective as selecting for high yield performing clonal cashew varieties in later years of production. 1. Materials and Experimental design Germplasm materials from Benin: BE 203, BE 204, BE 575, BE 627 and BE 739 and from farmers fields in Ghana : AKD, AKC, BAMBOI 7, BAME 7, IDDM 29, KT 1, KT 2, KT 4, KT 5 and SB 9 (Adu-Gyamfi et al. 2021 ; Adu-Gyamfi et al. 2019 ) together with superior clones; SG 266, SG 278, SG 273, SG 014, SG 004 and SG 224 identified in the Ghana cashew breeding program (Adu-Gyamfi et al. 2019 ) were used for the study (Table S1 ). The trial was established in 2009 at Bole (N 07ᵒ 45.171' W002°05.803') and Wenchi (N 09ᵒ 00.561', W002° 32.237’) research stations in the Guinea savannah and Forest transitional ecologies respectively (Fig. 1). The Guinea savannah zone is characterized by a Unimodal rainfall whereas the Forest Transitional zone is characterized by a bimodal rainfall pattern (Yamba et al. 2023 ). The trial was laid out at a spacing of 10m × 10m and arranged in a randomized complete block design with four replications and eight trees (per clone) per plot. The husbandry practices for this trial followed the recommended agronomic practices for cashew production in Ghana. 2.1 Agro - climatic information The rainfall, temperature and relative humidity information during the period of study were obtained from the weather stations at Bole (Sub-station of the Cocoa Research Institute of Ghana) and Wenchi (Agricultural Research Station of the Ministry of Food and Agriculture) research stations respectively. In order to assess the soil nutrient levels at the experimental site, ten (10) soil core samples were randomly collected from each of the site at a depth of 0–5 and 5–10 cm respectively. These samples from each site were bulked and mixed thoroughly and four sub - samples were collected from each bulk mix and using standard laboratory procedures, the soil levels of C - carbon, N - Nitrogen, P - Phosphorus, Mg - Magnesium, Ca - Calcium and K - Potassium were assessed. 2.2 Agronomic information The agronomic information collected were on growth and yield components. Survival was defined as the number of plants per plot (expressed as a percentage) for each clone living after the first annual drought season − 2009. Canopy volume was estimated as 1/2 x 4/3 x crown area × crown diameter in June, 2011. Where crown diameter is 2 times the mean of the four crown radii and canopy area is 3.142 × (crown diameter ) 2 . Nut yield (kg ha − 1 ) was estimated as the weight of raw cashew nut (RCN) collected annually from each clone throughout the fruiting season from 2012–2018, whereas nut weight (g) was measured from 2014–2015 as the weight of 1 kg of RCN divided by the number of nuts for each clone. Shelling was estimated from 2014–2015 as the proportion of good kernels recovered from I kg of raw nuts for each clone. 2.3 Data Analysis Analysis of variance based on Best Linear Unbiased Predictions (BLUPS) was used to test the significance of the genotype, environment and genotype ×environment interaction effects for the various agronomic traits measured using Genstat statistical package, version 12 (VSN International Ltd, Hemel Hempstead, UK) with environment considered a random effect and clones as a fixed effect respectively. Analysis was performed using the following model. Yijk = µ + REP k + Gi + Ej + GEij+ Ɛijk Where, Y ijk = observed value; µ - grand mean, REP k - is the replicate effect (k = 1; 2; :::; r), G j - effect of genotype, Ej - Environmental effect, GEij - the interaction effect of genotype i with Environment j and Ɛ ijk - residual effect. The differences among genotype and environmental means were tested by LSD at the 5% probability level. Heritability and genetic correlations among traits across environments were estimated using META-R (Alvarado et al. 2018). The heritability was classified as low (0–30%), moderate (30–60%), or high (> 60%) as suggested by (Wickham 2016 ). In order to assess the effect of retrospective selection for high yields performance based on survival rate in the early years of production, we employed a t-test to assess differences in yield of two sets of clones with contrasting survival rates. For this analysis, the first set (high survivors) consisted of the clone with the highest survival rate and those with survival rate not significantly ( p < 0.05) different from this clone and the second set (low survivors) consisted of the clone with the lowest survival rate and all clones with survival rate not significantly ( p < 0.05) different from this clone. Similar analysis were carried out for canopy volume, shelling and nut weight Further, we used a t-test to assess differences in yield of two sets of clones (high and low yielding) with contrasting yield performance based on first 2 - years, first 3 - years, first 4 - years, first 5 - years and first 6 - years average yields to assess the effects of possible retrospective selection for yield based on early production year yields. For this analysis the first set (high early yields) included the clones with the highest average yield and all the clones that were not significantly different ( P > 0.05) from this clones whereas the second set (low early yields) consisted of the clone with the least average yield and other clones that were not significantly different ( P > 0.05) from this clone. 2. Results 3.1 Environmental conditions The rainfall amount, temperature and humidity values during the drought period of October - March varied for the vegetative and reproductive phases at Bole and Wenchi research stations respectively (Table S2). Over the period, Bole recorded a mean rainfall of 41.6 mm in the range 27.3–52.4 mm whereas in Wenchi, a mean rainfall of 62.1 mm in the range of 41–82 mm was recorded. For, temperature, Bole recorded a mean value of 35.4 ᵒC in a range of 32.7–40.9 ᵒC whereas Wenchi recorded a mean of 32.5 in the range of 31–38 ᵒC. Interestingly, Bole and Wenchi recorded a remarkably high (40.9 and 38.1 ᵒC ) rise in temperature in 2015 compared to the other years. Relative humidity at 0900 hr and at 1500 hrs recorded a mean value of 79.1% and 22.3% at Bole whilst in Wenchi, mean values 79.6 and 56.4% were recorded respectively. Comparatively, Bole consistently recorded low rainfall amounts, high temperatures, low humidity (0900hrs) and low humidity (1500hrs) values by 33.1%, 8.2% ,10% and 60.4% than Wenchi respectively. The soil characteristics both experimental sites at has been reported (Adu-Gyamfi et al. 2019 ). The soils at both sites were of acidic reaction and Bole was predominantly Ferric Luvisol while Wenchi was mainly Lithosol. Against the standard developed by Dedzoe et al. ( 2001 ), the organic carbon contents, phosphorus, exchangeable potassium levels were relatively lower at Bole. However, for total nitrogen, the levels were comparable to the critical value at both sites. Overall, the Bole site appear to be sub-optimal whereas Wenchi appeared to near-optimal based on the consistently low rainfall amount, low humidity and high temperatures recorded at Bole coupled with the low soil fertility compared to Wenchi. Hence, our report will utilize the terms sub-optimal and near-optimal field conditions to denote the Bole and Wenchi environments respectively. 3.2 Overall agronomic trait performance The combined variance analysis of agronomic data of the 20 cashew clones of divers origin evaluated in sub-optimal and near optimal environments showed that genotype, environment and genotype × environment interaction effects were highly significant ( p < 0.01) for survival, height, nut weight, shelling, first 3 - year average yield, first 4 - year average yield, first 5 - year average yield, first 6-year average yield and overall 7-year average yield (Table S3). However, for canopy volume and the first 2 - year average yields, only the effects of genotype and environment were significant. Survival rate among the clones were in the range of 49% in clone SG 273 to 76% in clone BE 575 and BE 739 with average rate of 64.3% in the sub-optimal environment whereas in the near optimal environment, it was 44.3% in clone AKD to 84.1% in BE 203, BE 204, BE 627, KT 4, SB 9, SG 224 with average rate of 67.8% (Table 1 ). Fluctuations among the clones for the tested environments were evident, with clones BE 575, BE 739, KT 5 being top three best clones in the sub - optimal environment whereas BE 203, BE 204, BE 627, KT 4, SB 9, SG 224 were among the top three best clones in the near - optimal environment. A comparative reduction of 12.8% in survival rate was observed in the sub-optimal environment compared to the near-optimal environment. Table 1 Mean survival (%), height (cm), canopy volume (m 3 ) of 20 cashew germplasm clones evaluated under sub-optimal (Bole) and near - optimal (Wenchi) environment. Clone Survival Height Canopy volume Bole Wenchi Bole Wenchi Bole Wenchi AKC 56.2 (34.7) 68.8 (44.0) 0.58 0.85 3.81 84.8 AKD 56.1 (34.6) 56.2 (34.7) 0.61 0.77 3.94 83.3 BAMBOI 7 87.5 (60.0) 75.0 (54.3) 0.85 1.33 4.12 97.3 BAME 7 87.5 (75.0) 56.2 (35.4) 0.77 0.81 3.96 93.2 BE 203 81.2 (71.1) 100.0 (90.0) 1.04 1.4 4.32 102.5 BE 204 81.2 (64.7) 100.0 (90.0) 0.77 1.48 4.00 120.9 BE 575 100.0 (90.1) 87.5 (75.0) 0.88 0.95 4.25 107.1 BE 627 56.2 (41.1) 100.0 (90.0) 0.49 0.99 3.68 103.1 BE 739 100.0 (90.0) 81.2 (59.0) 0.83 1.18 3.72 95.1 IDDM 29 87.5 (75.0) 87.5 (69.3) 0.71 0.91 3.87 115.2 KT 1 56.2 (41.1) 81.2 (64.7 0.55 0.89 3.60 114.1 KT 2 87.5 (75.0) 87.5 (69.3) 0.61 0.94 3.73 78.8 KT 4 81.2 (71.1) 100.0 (90.0) 0.9 0.96 3.60 88.1 KT 5 100.0 (75.0) 81.2 (59.0) 0.77 1.19 3.72 81.3 SB 9 75.0 (60.0) 100.0 (90.0) 0.53 1.2 3.81 99.5 SG 004 75.0 (49.7) 81.2 (64.7) 0.74 1.43 4.13 119.0 SG 014 68.8 (45.8) 75.0 (60.0) 0.78 1.58 4.37 120.7 SG 224 68.8 (60.0) 100.0 (90.0) 0.65 1.41 3.70 120.3 SG 266 87.5 (60.0) 75.0 (54.3) 1.07 1.44 4.33 95.0 SG 273 43.8 (26.1) 87.5 (69.3) 0.7 0.93 3.70 95.4 Mean 76.9 (60.1 ± 4.0) 84.1(67.7 ± 4.1) 0.74 ± 0.03 1.1 ± 0.05 3.91 ± 0.25 100.7 ± 13.6 SED (Clone) - - 40.0 SED (Location) - - 42.5 SED (Clone × Location) 17.58 0.18 - In the sub-optimal environment, plant height increments ranged from 0.49 in BE 627 to 1.07 m in SG 266 with an average increment of 0.74mm whereas in the near optimal environment, a range of 0.77 in AKD to 1.58 m in SG 014 with average increment of 1.1mm was recorded (Table 1 ). The top three best clones in the sub-optimal environment with the highest height increments were SG 266, BE 203 and KT 4 whereas those whereas in the near optimal environment, clones SG 014, BE 204 and SG 266 were outstanding. A comparative reduction of 52.7% in plant height was observed in the sub - optimal environment compared to the near - optimal environment For canopy volume, a range of 3.6 m 3 in KT 1 and KT 4 to 4.37 m 3 in SG 014 with average volume of 3.91 m 3 was recorded in the sub-optimal environment whereas a range of 78.8 m 3 in KT 2 to 120.9 m 3 in BE 204 with an average volume of 100.7 m 3 in the sub-optimal environment (Table 1 ). Across the two environments, canopy volume values were 26 fold lower in the sub - optimal environment than the near - optimal environment. In the sub-optimal environment, nut yields in the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year were in the range of 79.3–220.1 kg ha − 1 , 76.2–304.5 kg ha − 1 , 215.6–380.3 kg ha − 1 , 230–505 kg ha − 1 , 287.1–589.6 kg ha − 1 and 306.9–607.4 kg ha −1 with average yields of 122.1, 145.5 kg ha − 1 , 285.5 kg ha − 1 , 361.9 kg ha − 1 , 438.7 kg ha − 1 , 453.6 kg ha − 1 respectively (Tables 2 and 3 ). On the other hand, the near-optimal environment recorded a range of 184.4–352.6, 244.2–577, 342.9–631.2, 387.6–900.4, 456.1–961.1, 447.4–1143.6 nut yields in the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year with average nut yield of 251.1 kg ha − 1 , 386.3 kg ha − 1 , 468 kg ha − 1 , 637.9 kg ha − 1 , 726.3 kg ha − 1 , 811.9 kg ha − 1 respectively. Table 2 Mean year yields, nut weight (g) and shelling (%) of 20 cashew germplasm clones evaluated under (Sub-optimal) Bole and near near optimal (Wenchi) environment. Clone 2-years 3-years Nut weight Shelling Bole Wenchi Bole Wenchi Bole Wenchi Bole Wenchi AKC 79.3 192.1 79.5 244.8 4.9 5.9 27.2 29.2 AKD 86.2 197.0 81.1 244.2 4.5 5.9 28.6 30.1 BAMBOI 7 114.7 184.4 126.3 329.2 4.6 6.3 29.4 31.3 BAME 7 147.2 237.1 167.2 350.0 5.1 6.0 28.8 31.1 BE 203 149.1 243.6 186.9 451.5 4.4 5.2 29.5 30.9 BE 204 149.0 242.2 166.4 451.7 4.6 5.3 27.1 27.1 BE 575 147.5 257.4 214.0 372.1 5.0 5.9 27.6 29.6 BE 627 100.7 247.6 111.9 398.7 4.2 6.0 28.6 30.6 BE 739 117.6 245.3 185.3 327.4 4.1 6.3 29.4 29.5 IDDM 29 124.4 257.3 131.8 365.4 4.6 6.2 30.4 30.4 KT 1 133.3 234.6 162.4 281.3 4.8 5.3 28.1 28.9 KT 2 91.0 244.4 108.3 350.0 4.7 5.3 28.0 32.8 KT 4 99.8 226.3 118.4 315.8 4.6 6.3 28.9 30.5 KT 5 132.2 291.5 162.0 408.5 5.3 5.8 28.7 30.2 SB 9 80.4 242.7 76.2 371.4 4.5 6.1 29.6 30.3 SG 004 148.3 283.6 147.8 505.5 4.7 5.8 29.0 29.9 SG 014 117.5 302.7 162.8 520.2 4.5 5.2 28.8 31.2 SG 224 106.8 323.7 117.2 577.0 4.7 6.0 30.1 30.0 SG 266 220.1 352.6 304.5 525.4 3.9 5.8 27.0 30.0 SG 273 98.4 215.2 99.2 336.5 5.3 5.4 28.9 29.2 Mean 122.1 ± 7.4 251.1 ± 15 145.5 ± 12 386.3 ± 27.1 4.8 ± 0.11 5.8 28.6 ± 0.43 30.1 SED (clone) 40.9 - - - SED (location) 12.9 - - - SED (clone × location) _- 55.7 0.34 1.6 Table 3 Mean year yields of 20 cashew germplasm clones evaluated under sub-optimal (Bole) and near optimal (Wenchi) environment. Clone 4-years 5-years 6-years 7-years Bole Wenchi Bole Wenchi Bole Wenchi Bole Wenchi AKC 215.6 364.6 230.0 470.5 287.1 573.4 306.9 608.6 AKD 318.1 342.9 328.3 387.6 389.3 456.1 407.7 447.4 BAMBOI 7 314.7 422.7 394.2 560.3 503.4 649.4 519.8 711.0 BAME 7 306.0 460.9 412.1 557.5 463.7 686.9 467.9 719.7 BE 203 284.4 526.8 411.2 877.2 557.7 912.3 587.6 1134.4 BE 204 304.3 509.6 407.7 655.3 482.9 692.4 485.6 766.7 BE 575 380.3 472.3 465.9 715.8 529.1 856.3 543.9 994.6 BE 627 233.0 489.4 313.3 700.0 393.9 850.0 424.9 965.4 BE 739 313.4 378.8 430.4 489.6 501.1 537.4 507.6 579.0 IDDM 29 343.7 412.4 400.1 554.4 454.9 612.9 452.1 631.6 KT 1 252.1 353.0 311.1 458.4 393.6 525.6 412.7 575.6 KT 2 252.1 436.8 306.0 625.2 371.1 697.1 378.0 782.1 KT 4 278.2 438.1 358.7 549.3 422.1 659.2 440.4 691.4 KT 5 352.6 480.3 452.5 624.1 479.7 706.0 472.3 754.4 SB 9 220.6 471.9 268.8 673.6 337.9 813.7 357.5 922.1 SG 004 243.7 574.1 348.2 789.0 480.5 878.8 517.9 1004.3 SG 014 290.1 610.3 360.8 900.4 477.2 961.1 489.5 1143.6 SG 224 218.7 631.2 285.5 861.2 351.0 958.4 365.2 1097.7 SG 266 372.9 552.1 505.0 724.6 589.6 841.5 607.4 934.3 SG 273 215.7 431.0 248.7 584.2 308.4 657.0 328.0 773.3 Mean 285.5 ± 11.8 467.9 ± 28.3 361.9 ± 16.8 637.9 ± 43.1 438.7 ± 18.5 726.2 ± 47 453.6 ± 18.4 811.8 ± 57.8 SED(Clone) SED(Location) SED(Clone x Location) 71.7 83.1 89.1 86.8 In the sub-optimal environment, clones SG 266, BE 575 and BE 203 consistently stood high among the top five clones for the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year (overall) average yields whereas in the near optimal environment clones SG 266, SG, 224, SG 014, SG 004 stood high (Tables 2 and 3 ). On the other hand, for the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year average yields, clones KT 2, SG 224, SB 9, SG 273 and AKC consistently stood low among the 5 worst clones whereas in the near-optimal environment near optimal environment, it was clones AKC, AKD, KT 1, KT 4, IDDM 29 and BE 739.. In comparing the two environments for average nut yields, the sub-optimal environment consistently recorded a low yield by 35%, 45.2%, 24.2%, 28%, 25%, and 28.3% for the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year average yields respectively (Tables 2 and 3 ). In the sub-optimal environment, an average nut weight of 4.8 g was recorded and the top five clones with the largest nut weight (≥ 5.1g) included BE 739, KT 5, SG 273, BAME 7 and BE 575 whereas in the near-optimal environment an average nut weight of 5.8g was recorded and BAMBOI 7, BE 739, KT 4, KT 5 and IDDM 29 were outstanding (nut weight ≥ 6.3g) (Table 2 ). In comparing the two environments, the sub-optimal environment recorded a lower nut weight reduction of 21% than the near optimal environment. For shelling, the sub-optimal environment gave an average value of 28.6% and the top five clones with the highest shelling (≥ 28%) were IDDM 29, SG 224, SB 9, BE 203 and BAMBOI 7 whereas in the near-optimal environment an average of 30.1% was recorded with clones KT 2, BAMBOI 7, BAME 7, SG 014, and BE 203 being outstanding (shelling ≥ 30%) (Table 2 ). Comparatively, a shelling reduction of 6.4% was observed in the sub-optimal environment compared to the near - optimal environment. 3.3 Nut yield patterns and response to selection based on early growth and yield traits For this study, the first 2 - year, 3 - year, 4 - year, 5 - year, 6 - year and 7 -year(overall) average yields of the 20 cashew clones displayed a moderate biennial yield increase pattern under both sub-optimal and near optimal environment (Fig. 2). Average year yield increments in the sub - optimal environment were in the rates of 16%, 49.1%, 21,1%, 17.5% and 3.3% whereas in the near optimal the rates of 35%, 17.4%, 26.6%, 12.2% and 11% for the first 2 - year, 3 - year, 4 - year, 5 - year, 6 - year and 7 -year(overall) respectively (Fig. 2). In the sub - optimal environments, there was a significant response to selection for yield ( p = 0.002) based on survival rates, where the set of clones with the highest survival rates out yielded those with low survival (Table 4 ). However, in near - optimal environments, there was no significant difference in yield between the set of clones producing high survival rates and those producing low survival rates respectively. On the other hand, for height increments, there was a significant difference in yield selection between the set of clones producing taller trees than those producing shorter ones under both the sub-optimal ( p = 0.003) and near - optimal environments ( p = 0.001) (Table 4 ). For canopy volume, there was a significant difference in yield between the set of clones producing canopies with high volumes than those producing low canopy volumes and selection response was significant under both near optimal (p = < 0.047) and sub-optimal environment (p = < 0.001). Table 4 Yield performance of cashew clones based on retrospective selection for agronomic traits trait under sub-optimal (Bole) and near optimal (Wenchi) environment. Trait Environment Yield (kg/ha) High Low df t Probability Survival Sub-optimal 502.3 376 8 4.47 0.002 Height Sub-optimal 533.2 396.2 8 4.09 0.003 Canopy Volume Sub-optimal 549.2 394.3 8 5.15 < 0.001 Nut weight Sub-optimal 531.9 447.8 8 1.29 0.244 Shelling Sub-optimal 485.9 457.5 8 0.33 0.753 Average yield for first 2 years Sub-optimal 548.5 355.6 8 6.67 < 0.001 Average yield for first 3 years Sub-optimal 542.9 355.6 8 6.01 < 0.001 Average yield for first 4 years Sub-optimal 496.7 356.5 8 3.45 0.009 Average yield for first 5 years Sub-optimal 523.6 347.1 8 6.43 < 0.001 Average yield for first 6 years Sub-optimal 553.3 347.1 8 8.88 < 0.001 Survival Optimal 896 684.2 8 1.9 0.093 Height Optimal 989.3 596.6 8 4.92 0.001 Canopy Volume Optimal 928.8 656.8 8 2.34 0.047 Nut weight Optimal 880.5 707 8 1.38 0.206 Shelling Optimal 898.2 660.6 8 2.18 0.016 Average yield for first 2 years Optimal 986.9 646.3 8 3.84 0.005 Average yield for first 3 years Optimal 989.3 580.4 8 5.3 < 0.001 Average yield for first 4 years Optimal 1062.9 568.4 8 9.58 < 0.001 Average yield for first 5 years Optimal 1062.9 580.4 8 8.55 < 0.001 Average yield for first 6 years Optimal 1074.9 568.4 8 11.24 < 0.001 The retrospective effect of selection for high yields in the later years based on yields averaged over the first 2 - years, 3 - years, 4 - years, 5 - years and 6 - years of yield data recording years were also assessed with a t-test. There was a significant response to selection based on early average yields in first 2 - years ( p = < 0.001; p = < 0.005 ), 3 - years( p = < 0.001; p = < 0.001), 4 - years ( p = < 0.009; p = < 0.001), 5 - years ( p = < 0.001; p = < 0.001) and 6 - years ( p = < 0.001; p = < 0.001), for later years’ under sub-optimal and near optimal environments where the set of clones with high (n = 5) early year average yields consistently out-yielded the set of clones with low (n = 5) early year average yields respectively (Table 4 , Figs. 3 & 4). Among these clones, although the response was significant during the overall average yield period (7 -years of production), the response in the relatively early production years (first 2 years average production) under both sub-optimal and near optimal environment were equally pronounced respectively (Figs. 3 and 4). Retrospectively, we also assessed the effects of selecting for higher yields based on nut weight and shelling values obtained in the early years of production. Interestingly, the were no significant selection response for nut weight under both sub-optimal and near optimal environments but there was significant selection response for shelling under near - optimal environment respectively. Overall, the response to selecting yields in later years based on survival, height, canopy volume and first − 2 year average early yield were more pronounced in sub-optimal environments, whereas under near optimal environments, height, canopy volume and shelling were more pronounced. 3.4 Genotypic correlations among traits Survival showed a strong and positive genotypic correlation coefficients (r = 0.80) with the overall average yield data recording in the sub - optimal environment, whereas a moderate (r = 0.47) correlation coefficient was recorded in the near- optimal environment respectively (Table 5 ). However, for plant height increments, a strong positive genotypic correlation coefficients with the overall yield data recording period was observed in both the sub - optimal environment (r = 0.98) and near - optimal environment ( 0.80) respectively. Canopy volume also showed strong positive genotypic correlation coefficient with overall average yield recording in both the sub - optimal environment (r = 0.80) and in the near-optimal environment (r = 0.84) respectively. The first average yields at two-years (r = 0.97), three-years (r = 0.94), four-years (r = 0.87), five-years (r = 0.96) and six-years (r = 0.98) of production showed strong significant genotypic correlation coefficients with overall yield period (seven - years) in the sub - optimal environment. Similarly, in the near optimal environment, average yields for the first two - years (r = 0.75), three-years (r = 0.88), four-years (r = 0.95), five-years (r = 0.98) and six-years (r = 0.98) of production also showed strong genotypic correlation coefficients with overall average yield recording period. On the other hand, while nut weight showed a strong negative correlation with overall yield under sub-optimal environment, shelling showed a strong positive genotypic correlation coefficient with overall yield data recording (Table 5 ). Table 5 Genotypic correlation coefficient estimates between survival, height, crown volume, nut weight, shelling, 2-year, 3-year, 4-year, 5-year, 6-year and overall average yield among 20 cashew clones evualueted at Bole (sub-optimal) and Wenchi (near optimal). Trait Bole Wenchi Survival (%) 0.80*** 0.57 Height (cm) 0.98*** 0.80*** Canopy volume (m3) 0.98*** 0.84*** 2-years average yield (kg ha − 1 ) 0.97*** 0.75** 3-years average yield (kg ha − 1 ) 0.94*** 0.88*** 4-years average yield (kg ha − 1 ) 0.87*** 0.95*** 5-years average yield (kg ha − 1 ) 0.96*** 0.98*** 6-years average yield (kg ha − 1 ) 0.98*** 0.98*** Nut weight (g) -0.72** -0.31 Shelling 0.04 0.28 3.5 Variance and Heritability of traits The high genotype × environment interaction variance recorded in this study accounted for the variable heritability values observed for the traits studied (Table S4). Heritability estimates generally decreased for average year yields. The highest heritability estimate was observed for the first 2-years ( h 2 bs = 0.74) and first 3-years ( h 2 bs = 0.60) average yield, whereas moderate estimates were obtained for shelling ( h 2 bs = 0.52), height ( h 2 bs = 0.51), first 4-years average yield ( h 2 bs = 0.50), first 6-years average yield ( h 2 bs = 0.42) and first 7-years average yield ( h 2 bs = 0.47). However, low heritability estimates were obtained for survival ( h 2 bs = 0.12), canopy volume ( h 2 bs = 0.10), nut weight ( h 2 bs = 0.11) and first 5 - years average yield ( h 2 bs = 0.20) (Table S4). 3. Discussion To develop a robust selection index which focuses on using juvenile traits that would be effective as selecting for yield in later years, we utilized cashew germplasm clones of varied origin and evaluated them in sub - optimal and near optimal field ecologies over a period of nine years. In our study, retrospective selection for high yields in later years of production based on survival, height, canopy volume and first 2 - years average yield in sub-optimal environment were effective whereas in the near - optimal environment height, canopy volume, shelling and first 2 - years average yields were effective. These observations imply that the set of juvenile traits optimal for selecting high cashew yield performers could vary with ecological conditions and this could be attributed to the significant clone, environment and clone × environment interaction effects recorded in the current study. Our results in this study are therefore consistent with the findings of Kumar et al. ( 2016 ) who emphasized that in a sub - optimal ecologies, traits related to drought tolerance would receive higher weighting as an effective selection index compared to a near - optimal or irrigated environment, where the index might prioritize traits that maximize yield potential under favorable conditions. The effectiveness of selection indices that rely on a combination of juvenile traits in both the vegetative and early reproductive phases has been highly emphasized in many tree crop improvement programs (Akpertey et al. 2019 ; Akpertey et al. 2017 ; Padi et al. 2012 ). In the present study, juvenile traits like high survival rate, faster tree height gain with rapidly expanding canopies volumes and shelling together with the first 2 - year average yields were effective. These observations are consistent with the findings Akpertey et al. ( 2017 ) who emphasized that selection for stable high yields in later years for Kola ( Cola nitida M. ) may effectively rely on a combination of fast vegetative growth and the first 2-year average yields. Similarly, in Cocoa, early season vigour ratings in combination with early year yields were found to be effective as varieties with poor juvenile growth rate and low early yields were found to have poor yields (Padi et al. 2012 ). In coffee, the use of fruit set, span and the first three-year yields were over 70% as efficient as using overall seven-year yields in selecting superior varieties (Akpertey et al. 2022 ). Consequentially, the huge financial resource investment that could accrue from relying on early years’ performance to select for stable high cashew yields in later years compared to recording yield data over many years before final varietal recommendations is emphasized. Interestingly, over the 9 - year duration of study, the biennial/ alternate bearing nature where a year of heavy yield (on-year) is followed by a year of low or light yield (off-year) was evident in the average year yield pattern in both the sub-optimal and near optimal environment. This phenomenon has been attributed to both heavy fruit load, which suppresses flower bud formation for the next season and depleting tree resources, which are influenced by hormones like gibberellins (GAs) and auxins (Krasniqi et al. 2017 ; Salari 2016 ). While this biennial bearing habit could vary with crop species, genetics play a significant role as some cultivars of other crops inherently favor this cycle. Nevertheless as the alternate bearing phenomenon affects both high and low yielding varieties, selection of clones like SG 266, BE 203, BE 204, SG 004, BE 575 for sub-optimal environment and SG 266, SG 224, SG 014, KT 5, SG 004 for near optimal environment in the early production years and advancing them in the breeding cycle would allow the cultivation of only targeted clones that can be planted in larger orchards to increase production. While a typical cashew orchard will reach full bearing in the 10th year after planting (Agrifarming 2020 ), in our present study, average yields continue to increase exponentially even at the 9th year of production. Such yield increases are expected and could vary with the environment until canopies close interlock/overcrowd before yields decline will set in. This phenomenon has been expressed in other tree crops where a yield decline from interlocking canopies and has been attributed to reduced light interception and utilization by the photosynthetic surface (Akpertey et al. 2017 ). Further, in many tree crops breeding trials, varietal selections are made when the trees had attained maturity, because the high environmental effect (error) decrease with age (Jones et al., 1957; Padi et al., 2016). Contrastingly, our study which relied on average year yields build up to maturity reported moderate to high heritability values in the early year yields and decreased towards maturity. Our result are consistent with other findings, as moderate heritability estimates for early year average yields in cashew have been reported (Das 2019 ). Our reports therefore re-emphasize the higher weights attached to the use of higher early year yield traits as an effective selection index for superior clonal cashew varieties. On the other hand, low heritability estimates were recorded for survival, nut weight and canopy volume in our study and our results are in concurrence with similar values reported for these traits in other studies (Adu-Gyamfi et al. 2019 ; Dadzie 2020 ; Daouda et al. 2019 ; Das 2019 ). Nevertheless, their high correlation with the overall yield performance in later years at the genotypic level suggest that selection for high yielding cashew clones based on these traits in the early years of the breeding program would be as good as selection in later years. In a Kola selection breeding program, Akpertey et al. ( 2017 ) similarly found low heritability values for vegetative traits, yet they were effective in selecting high yield performing genotypes in later years of production. The value of genotypic correlations among agronomic traits in the development selection index in many studies have been overlooked even though conflicting correlations between multiple traits could result in sub-optimal selection response (Grattapaglia et al. 2018 ). Interestingly, while genotypic correlations between shelling and yield in later years of production were not significant under both environment, their selection were effective under near - optimal environment. Similar observations have been made in other studies which suggest that as long as genetic variance is high selection can still be effective if traits are not genetically correlated (Ata-Ul-Karim et al. 2022 ; Muir and Pease 2014 ). On the other hand, nut weight although gave a significant negative genotypic correlations with yield in later years of production, their response to selection under both environments were not effective. This could be attributed to a combination of genetic, environment and selection methods as highlighted in many studies indicating that significant genotypic correlation between traits does not guarantee effective selection response. Conclusions The lengthy cashew breeding programs is costly and has led to a limited number of cultivated clonal varieties that have been propagated over a long period of time. This has lead to susceptibility to drought, disease and insect. Our trial focused on identifying a set of juvenile traits that would be effective as selecting for high yield performance in later years of production. Retrospective selection for survival, height, canopy volume and first 2 - year average yield resulted in gains in identifying cashew clones with higher yields early in the cashew breeding program under sub-optimal environment whereas in the near - optimal environment height, canopy volume, shelling and first 2 - year average yield were effective. Based average yields across years, a biennial yielding pattern was evident among the clones and their ranking were consistent across the years. Genotypic correlation coefficient estimates were significant between yield in later years of production and survival, height, canopy volume, nut weight and 2 - year average yield under sub-optimal environment whereas under near optimal environment, height, canopy volume, shelling and 2 - year average yield were significant respectively. While, selection response for most correlated traits gave positive response, selcting for high yield in later years using nut weight was not effective. Our results therefore suggest the identified traits would advantageous in selecting productive and efficient clones early in the cashew breeding program, that the set of juvenile traits effective for selection could vary with ecological conditions. Declarations The authors declare that there are no conflict of interest. Data Archiving statement All data generated or analysed during this study are included in this published article. Funding The authors acknowledge the support of the Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ) with funding through Commcashew, the African Development Banak (AfDB) and the Cocoa Research Institute of Ghana (CRIG). Author Contribution PKKAG conceived and designed the experiment. PKKAG, AA, GA, SA, YB, performed the experiment, collected and analyzed data and wrote the manuscript. PA and SOA all assisted with data collection and provided significant editorial and analytical advice. 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(2023) Revisiting the agro-climatic zones of Ghana: A re-classification in conformity with climate change and variability PLOS Climate 2:e0000023 doi: 10.1371/journal.pclm.0000023 Yin L et al. (2023) Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin Remote Sensing of Environment 295:113695 doi: https://doi.org/10.1016/j.rse.2023.113695 Additional Declarations No competing interests reported. Supplementary Files supplementarytables.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9210569","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":613211889,"identity":"4a0cb687-4e46-418a-8d4f-b77597edd977","order_by":0,"name":"Paul K. K. 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K.","lastName":"Adu-Gyamfi","suffix":""},{"id":613211890,"identity":"1e463957-4a55-4feb-9223-47c003646d12","order_by":1,"name":"Abraham Akpertey","email":"","orcid":"","institution":"Cocoa Research Institute of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Abraham","middleName":"","lastName":"Akpertey","suffix":""},{"id":613211892,"identity":"0252333c-c021-4788-82f0-6fdd41428cd6","order_by":2,"name":"Godfred Awudzi","email":"","orcid":"","institution":"Cocoa Research Institute of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Godfred","middleName":"","lastName":"Awudzi","suffix":""},{"id":613211893,"identity":"cc7274e9-897a-4a82-b6a9-fd4ffa651c19","order_by":3,"name":"Solomon Agyare","email":"","orcid":"","institution":"Cocoa Research Institute of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Solomon","middleName":"","lastName":"Agyare","suffix":""},{"id":613211901,"identity":"71f6ca86-b1ab-450e-98f5-b15187fd6bfc","order_by":4,"name":"Yahaya Bukari","email":"","orcid":"","institution":"Cocoa Research Institute of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Yahaya","middleName":"","lastName":"Bukari","suffix":""},{"id":613211904,"identity":"4f287035-945d-42fc-9750-69b4d82e88ab","order_by":5,"name":"Priscilla Amissah","email":"","orcid":"","institution":"Cocoa Research Institute of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Priscilla","middleName":"","lastName":"Amissah","suffix":""},{"id":613211908,"identity":"20cba27c-9660-4cb9-8772-7790b53cff10","order_by":6,"name":"Seth Osei -Akoto","email":"","orcid":"","institution":"Ministry of Food and Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Seth","middleName":"Osei","lastName":"-Akoto","suffix":""}],"badges":[],"createdAt":"2026-03-24 10:26:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9210569/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9210569/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105715604,"identity":"1618a69d-2098-4514-a2c2-bcee28e59003","added_by":"auto","created_at":"2026-03-30 08:44:21","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":374910,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical coordinates of the experimental sites at Bole and Wenchi in the Guinea Savannah and Forest Transitional zone of Ghana, West Africa used for the study.\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9210569/v1/1bc804a425b2ba7155f26b21.jpg"},{"id":105715695,"identity":"6cb6bd06-6473-436c-b3b3-155c3da4481c","added_by":"auto","created_at":"2026-03-30 08:44:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":316857,"visible":true,"origin":"","legend":"\u003cp\u003ePattern of average yield across years of 20 cashew clones evaluated under Bole (sub-optimal) and Wenchi (Near optimal) in the Guinea savannah and Forest Transitional savannah agroecological zone of Ghana.\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9210569/v1/0efa1bb603a1baa72110f012.jpg"},{"id":105715669,"identity":"b8495d42-71c2-4895-85d4-0eff1cae0e12","added_by":"auto","created_at":"2026-03-30 08:44:33","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":343926,"visible":true,"origin":"","legend":"\u003cp\u003ePattern of 2-year average yield performance of highest and least-yielding cashew clones at Bole (sub-optimal). Grouping was based on overall 7-year yield average. Highest-yielding clones (n = 5) were not significantly (P \u0026gt; 0.05) different from each other; least yielding clones (n = 5) were not significantly (P \u0026gt; 0.05) different from each other.\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9210569/v1/b44c81b2ec606decc0e82b81.jpg"},{"id":105715694,"identity":"33276a77-93b1-468b-8b96-eecad760ad90","added_by":"auto","created_at":"2026-03-30 08:44:37","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":316895,"visible":true,"origin":"","legend":"\u003cp\u003ePattern of 2-year average yield performance of highest and least-yielding cashew clones at Wenchi (Near-optimal). Grouping was based on overall 7-year yield average. Highest-yielding clones (n = 5) were not significantly (P \u0026gt; 0.05) different from each other; least yielding clones (n = 5) were not significantly (P \u0026gt; 0.05) different from each other.\u003c/p\u003e","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9210569/v1/268a10f75fcb3a8f685adfc5.jpg"},{"id":105715705,"identity":"6e316c3f-46d8-4078-b747-e08ca8a835d6","added_by":"auto","created_at":"2026-03-30 08:44:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2555111,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9210569/v1/940ba5a4-21e0-4333-a3e0-0f34f6806f09.pdf"},{"id":105715605,"identity":"f4c5049d-e471-4847-8eae-67d22501535a","added_by":"auto","created_at":"2026-03-30 08:44:21","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":150016,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytables.doc","url":"https://assets-eu.researchsquare.com/files/rs-9210569/v1/ebc3ff59fc850ffe35d0d2fa.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multi-trait selection index for high clonal cashew (Anacardium occidentally. L.) yield performance","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCashew (\u003cem\u003eAnacardium occidentale\u003c/em\u003e L.) is perennial nut tree crop belonging to the family \u003cem\u003eAnacardiaceae\u003c/em\u003e (mangoes and pistachios family). It originated from North-Eastern Brazil (Mitchell and Mori 1987), and was introduced into West Africa by the early Portuguese settlers in the 16th and 19th century. Currently, over 50% of the raw cashew nut (RCN) produced globally is dominated by West African producing countries and Ivory coast is the leading producer with substantial productions from Nigeria, Ghana, Benin, Burkina Faso, Tanzania, and Guinea-Bissau (ACA \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Awuah \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The crop is highly valued for their nuts and the global consumption of these nuts has doubled over a period of ten years and this has been attributed to both their health benefits in preventing heart diseases and the shift in preference of vegan diet over non-vegan diet (Sushma et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The value of cashew in reducing poverty, boosting rural development and as a major foreign exchange earner for most developing producing countries has been emphasize d(Eze et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hinnou et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yin et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eCashew adapts well to different ecological zones (Dedzoe et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), however, it requires an annual rainfall of 800\u0026ndash;2000 mm (Sys et al. 1993) coupled with a well-drained deep light to medium textured soils (Dedzoe et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) with a pH range of 4.5\u0026ndash;6.5 (Dendena and Corsi \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and a temperature range of 25\u0026ndash;28 ᵒC (Dendena and Corsi \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) with a pronounced dry period of 5\u0026ndash;6 months (Dedzoe et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) for optimum productivity. Nevertheless, long breeding cycles, weak juvenile - mature correlations, changes in climate, market demands and emerging pest and disease pressures, pose, however, daunting challenges.\u003c/p\u003e \u003cp\u003eThe breeding of a perennial crop like cashew is an expensive and time-consuming due to their large tree size and lengthy juvenile phase (Migicovsky and Myles \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). A typically grafted cashew clone will start bearing in the 3rd year after planting, reach full bearing in the 10th year and continue to give remunerative yields for 20 years (Agrifarming \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, tree crops like avocado (\u003cem\u003ePersea americana\u003c/em\u003e) took up to 15 years to mature before flowering (Janick and Moore \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) while the breeding of some commercial apple (\u003cem\u003eMalus domestica\u003c/em\u003e) cultivars took about 26 years (Peil et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It is therefore common for a limited number of elite cashew varieties to be propagated widely by farmers over long periods of time. The propagation of the same cashew cultivars over time, could lead to increasing susceptibility to drought and diseases, since these crops remain genetically frozen while environmental conditions continue change and pathogen continue to evolve.\u003c/p\u003e \u003cp\u003eA common strategy employed by plant breeders to maximize genetic gains per unit time and reduce the long breeding cycles in many tree crop breeding programs has been the development of a selection index that could identify the most productive clones early in the breeding program than relying of data in the later years of production. This strategy has been successfully applied to tree crops like Cocoa (\u003cem\u003eTheobroma cacao L.)\u003c/em\u003e (Padi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and Kola (\u003cem\u003eCola nitida\u003c/em\u003e (Vent) (Akpertey et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In cashew, selection indices for the development of superior varieties have mostly relied on several traits over several years of data collection, until final varietal recommendations are made (Nkumbula et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Piria and Manivannan \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Others have also relied on vegetative traits correlations with early yield traits to select the most productive clones. (Adu-Gyamfi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Adeigbe et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) has therefore emphasized that by combining these different traits into a comprehensive index, cashew breeders can more effectively identify elite varieties that maximize economic benefits for farmers and processors early in the breeding program than relying on yield data in later years of production.\u003c/p\u003e \u003cp\u003eMost tree crop breeding programs aim to improve multiple valuable traits, however, they tend to overlook firstly, the value of each trait in a particular environment, secondly the genotypic correlation among traits and thirdly the varying heritability\u0026rsquo;s estimates which often leads to sub-optimal selection response (Grattapaglia et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). While selecting for traits with conflicting response can be misleading, as progress in one might harm the other, selecting for traits with synergistic correlations between two or more traits can bias the selection against the remaining traits (Grattapaglia et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, the development of a robust selection index that relies on juvenile traits, heritability estimates, together with a favorable genotypic association with yield in later years of production could constitute a viable strategy to reduce the lengthy cashew breeding programs and subsequently save financial resources.\u003c/p\u003e \u003cp\u003eThe Ghana Cashew Breeding Research Program has planted cashew field gene banks with over 2000 accessions of both local and exotic origin at the Bole Research stations in the Guinea savannah ecological zone and Wenchi Agricultural research station in the Forest transitional zone (Adu-Gyamfi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Dadzie et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Here, we report on a selection criterion that relies on the use of a set of juvenile traits that could be effective as selecting for high yield performing clonal cashew varieties in later years of production.\u003c/p\u003e"},{"header":"1. Materials and Experimental design","content":"\u003cp\u003eGermplasm materials from Benin: BE 203, BE 204, BE 575, BE 627 and BE 739 and from farmers fields in Ghana : AKD, AKC, BAMBOI 7, BAME 7, IDDM 29, KT 1, KT 2, KT 4, KT 5 and SB 9 (Adu-Gyamfi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Adu-Gyamfi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) together with superior clones; SG 266, SG 278, SG 273, SG 014, SG 004 and SG 224 identified in the Ghana cashew breeding program (Adu-Gyamfi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) were used for the study (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The trial was established in 2009 at Bole (N 07ᵒ 45.171' W002\u0026deg;05.803') and Wenchi (N 09ᵒ 00.561', W002\u0026deg; 32.237\u0026rsquo;) research stations in the Guinea savannah and Forest transitional ecologies respectively (Fig.\u0026nbsp;1). The Guinea savannah zone is characterized by a Unimodal rainfall whereas the Forest Transitional zone is characterized by a bimodal rainfall pattern (Yamba et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The trial was laid out at a spacing of 10m \u0026times; 10m and arranged in a randomized complete block design with four replications and eight trees (per clone) per plot. The husbandry practices for this trial followed the recommended agronomic practices for cashew production in Ghana.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Agro - climatic information\u003c/h2\u003e \u003cp\u003eThe rainfall, temperature and relative humidity information during the period of study were obtained from the weather stations at Bole (Sub-station of the Cocoa Research Institute of Ghana) and Wenchi (Agricultural Research Station of the Ministry of Food and Agriculture) research stations respectively. In order to assess the soil nutrient levels at the experimental site, ten (10) soil core samples were randomly collected from each of the site at a depth of 0\u0026ndash;5 and 5\u0026ndash;10 cm respectively. These samples from each site were bulked and mixed thoroughly and four sub - samples were collected from each bulk mix and using standard laboratory procedures, the soil levels of C - carbon, N - Nitrogen, P - Phosphorus, Mg - Magnesium, Ca - Calcium and K - Potassium were assessed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Agronomic information\u003c/h2\u003e \u003cp\u003eThe agronomic information collected were on growth and yield components. Survival was defined as the number of plants per plot (expressed as a percentage) for each clone living after the first annual drought season\u0026thinsp;\u0026minus;\u0026thinsp;2009. Canopy volume was estimated as 1/2 x 4/3 x crown area \u0026times; crown diameter in June, 2011. Where crown diameter is 2 times the mean of the four crown radii and canopy area is 3.142 \u0026times; (crown diameter )\u003csup\u003e2\u003c/sup\u003e. Nut yield (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was estimated as the weight of raw cashew nut (RCN) collected annually from each clone throughout the fruiting season from 2012\u0026ndash;2018, whereas nut weight (g) was measured from 2014\u0026ndash;2015 as the weight of 1 kg of RCN divided by the number of nuts for each clone. Shelling was estimated from 2014\u0026ndash;2015 as the proportion of good kernels recovered from I kg of raw nuts for each clone.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Analysis\u003c/h2\u003e \u003cp\u003eAnalysis of variance based on Best Linear Unbiased Predictions (BLUPS) was used to test the significance of the genotype, environment and genotype \u0026times;environment interaction effects for the various agronomic traits measured using Genstat statistical package, version 12 (VSN International Ltd, Hemel Hempstead, UK) with environment considered a random effect and clones as a fixed effect respectively. Analysis was performed using the following model.\u003c/p\u003e \u003cp\u003eYijk\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;\u003cem\u003eREP\u003c/em\u003ek\u0026thinsp;+\u0026thinsp;Gi\u0026thinsp;+\u0026thinsp;Ej\u0026thinsp;+\u0026thinsp;GEij+ Ɛijk\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eY\u003csub\u003eijk =\u003c/sub\u003e observed value; \u0026micro; - grand mean, \u003cem\u003eREP\u003c/em\u003ek - is the replicate effect (k\u0026thinsp;=\u0026thinsp;1; 2; :::; r), G\u003csub\u003ej\u003c/sub\u003e - effect of genotype, Ej - Environmental effect, GEij - the interaction effect of genotype i with Environment j and Ɛ\u003csub\u003eijk\u003c/sub\u003e - residual effect. The differences among genotype and environmental means were tested by LSD at the 5% probability level. Heritability and genetic correlations among traits across environments were estimated using META-R (Alvarado et al. 2018). The heritability was classified as low (0\u0026ndash;30%), moderate (30\u0026ndash;60%), or high (\u0026gt;\u0026thinsp;60%) as suggested by (Wickham \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn order to assess the effect of retrospective selection for high yields performance based on survival rate in the early years of production, we employed a t-test to assess differences in yield of two sets of clones with contrasting survival rates. For this analysis, the first set (high survivors) consisted of the clone with the highest survival rate and those with survival rate not significantly (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) different from this clone and the second set (low survivors) consisted of the clone with the lowest survival rate and all clones with survival rate not significantly (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) different from this clone. Similar analysis were carried out for canopy volume, shelling and nut weight Further, we used a t-test to assess differences in yield of two sets of clones (high and low yielding) with contrasting yield performance based on first 2 - years, first 3 - years, first 4 - years, first 5 - years and first 6 - years average yields to assess the effects of possible retrospective selection for yield based on early production year yields. For this analysis the first set (high early yields) included the clones with the highest average yield and all the clones that were not significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) from this clones whereas the second set (low early yields) consisted of the clone with the least average yield and other clones that were not significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) from this clone.\u003c/p\u003e \u003c/div\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Environmental conditions\u003c/h2\u003e \u003cp\u003eThe rainfall amount, temperature and humidity values during the drought period of October - March varied for the vegetative and reproductive phases at Bole and Wenchi research stations respectively (Table S2). Over the period, Bole recorded a mean rainfall of 41.6 mm in the range 27.3\u0026ndash;52.4 mm whereas in Wenchi, a mean rainfall of 62.1 mm in the range of 41\u0026ndash;82 mm was recorded. For, temperature, Bole recorded a mean value of 35.4 ᵒC in a range of 32.7\u0026ndash;40.9 ᵒC whereas Wenchi recorded a mean of 32.5 in the range of 31\u0026ndash;38 ᵒC. Interestingly, Bole and Wenchi recorded a remarkably high (40.9 and 38.1 ᵒC ) rise in temperature in 2015 compared to the other years. Relative humidity at 0900 hr and at 1500 hrs recorded a mean value of 79.1% and 22.3% at Bole whilst in Wenchi, mean values 79.6 and 56.4% were recorded respectively. Comparatively, Bole consistently recorded low rainfall amounts, high temperatures, low humidity (0900hrs) and low humidity (1500hrs) values by 33.1%, 8.2% ,10% and 60.4% than Wenchi respectively.\u003c/p\u003e \u003cp\u003eThe soil characteristics both experimental sites at has been reported (Adu-Gyamfi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The soils at both sites were of acidic reaction and Bole was predominantly Ferric Luvisol while Wenchi was mainly Lithosol. Against the standard developed by Dedzoe et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), the organic carbon contents, phosphorus, exchangeable potassium levels were relatively lower at Bole. However, for total nitrogen, the levels were comparable to the critical value at both sites. Overall, the Bole site appear to be sub-optimal whereas Wenchi appeared to near-optimal based on the consistently low rainfall amount, low humidity and high temperatures recorded at Bole coupled with the low soil fertility compared to Wenchi. Hence, our report will utilize the terms sub-optimal and near-optimal field conditions to denote the Bole and Wenchi environments respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Overall agronomic trait performance\u003c/h2\u003e \u003cp\u003eThe combined variance analysis of agronomic data of the 20 cashew clones of divers origin evaluated in sub-optimal and near optimal environments showed that genotype, environment and genotype \u0026times; environment interaction effects were highly significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) for survival, height, nut weight, shelling, first 3 - year average yield, first 4 - year average yield, first 5 - year average yield, first 6-year average yield and overall 7-year average yield (Table S3). However, for canopy volume and the first 2 - year average yields, only the effects of genotype and environment were significant. Survival rate among the clones were in the range of 49% in clone SG 273 to 76% in clone BE 575 and BE 739 with average rate of 64.3% in the sub-optimal environment whereas in the near optimal environment, it was 44.3% in clone AKD to 84.1% in BE 203, BE 204, BE 627, KT 4, SB 9, SG 224 with average rate of 67.8% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Fluctuations among the clones for the tested environments were evident, with clones BE 575, BE 739, KT 5 being top three best clones in the sub - optimal environment whereas BE 203, BE 204, BE 627, KT 4, SB 9, SG 224 were among the top three best clones in the near - optimal environment. A comparative reduction of 12.8% in survival rate was observed in the sub-optimal environment compared to the near-optimal environment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean survival (%), height (cm), canopy volume (m\u003csup\u003e3\u003c/sup\u003e) of 20 cashew germplasm clones evaluated under sub-optimal (Bole) and near - optimal (Wenchi) environment.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSurvival\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eCanopy volume\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.2 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.8 (44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.1 (34.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.2 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAMBOI 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.5 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.0 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAME 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.5 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.2 (35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.2 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e102.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.2 (64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e120.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.0 (90.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.5 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e107.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.2 (41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.0 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.2 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDDM 29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.5 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.5 (69.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e115.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.2 (41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.2 (64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e114.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.5 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.5 (69.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.2 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.0 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.2 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSB 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.0 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.0 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.2 (64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e119.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.8 (45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.0 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e120.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.8 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e120.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.5 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.0 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.8 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.5 (69.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.9 (60.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84.1(67.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSED (Clone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSED (Location)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSED (Clone \u0026times; Location)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the sub-optimal environment, plant height increments ranged from 0.49 in BE 627 to 1.07 m in SG 266 with an average increment of 0.74mm whereas in the near optimal environment, a range of 0.77 in AKD to 1.58 m in SG 014 with average increment of 1.1mm was recorded (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The top three best clones in the sub-optimal environment with the highest height increments were SG 266, BE 203 and KT 4 whereas those whereas in the near optimal environment, clones SG 014, BE 204 and SG 266 were outstanding. A comparative reduction of 52.7% in plant height was observed in the sub - optimal environment compared to the near - optimal environment\u003c/p\u003e \u003cp\u003eFor canopy volume, a range of 3.6 m\u003csup\u003e3\u003c/sup\u003e in KT 1 and KT 4 to 4.37 m\u003csup\u003e3\u003c/sup\u003e in SG 014 with average volume of 3.91 m\u003csup\u003e3\u003c/sup\u003e was recorded in the sub-optimal environment whereas a range of 78.8 m\u003csup\u003e3\u003c/sup\u003e in KT 2 to 120.9 m\u003csup\u003e3\u003c/sup\u003e in BE 204 with an average volume of 100.7 m\u003csup\u003e3\u003c/sup\u003e in the sub-optimal environment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Across the two environments, canopy volume values were 26 fold lower in the sub - optimal environment than the near - optimal environment.\u003c/p\u003e \u003cp\u003eIn the sub-optimal environment, nut yields in the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year were in the range of 79.3\u0026ndash;220.1 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 76.2\u0026ndash;304.5 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 215.6\u0026ndash;380.3 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 230\u0026ndash;505 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 287.1\u0026ndash;589.6 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 306.9\u0026ndash;607.4 kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003ewith average yields of 122.1, 145.5 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 285.5 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 361.9 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 438.7 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 453.6 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). On the other hand, the near-optimal environment recorded a range of 184.4\u0026ndash;352.6, 244.2\u0026ndash;577, 342.9\u0026ndash;631.2, 387.6\u0026ndash;900.4, 456.1\u0026ndash;961.1, 447.4\u0026ndash;1143.6 nut yields in the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year with average nut yield of 251.1 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 386.3 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 468 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 637.9 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 726.3 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 811.9 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean year yields, nut weight (g) and shelling (%) of 20 cashew germplasm clones evaluated under (Sub-optimal) Bole and near near optimal (Wenchi) environment.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"18\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e2-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003e3-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eNut weight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c18\" namest=\"c15\"\u003e \u003cp\u003eShelling\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e79.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e192.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e79.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e244.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e29.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e86.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e197.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e81.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e244.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAMBOI 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e114.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e184.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e126.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e329.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAME 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e147.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e237.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e167.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e350.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e149.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e243.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e186.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e451.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e149.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e242.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e166.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e451.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e27.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e147.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e257.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e214.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e372.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e29.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e100.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e247.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e111.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e398.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE 739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e117.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e245.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e185.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e327.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDDM 29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e124.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e257.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e131.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e365.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e133.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e234.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e162.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e281.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e91.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e244.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e108.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e350.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e32.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e99.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e226.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e118.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e315.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e132.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e291.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e162.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e408.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSB 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e80.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e242.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e76.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e371.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e29.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e148.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e283.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e147.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e505.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e29.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e117.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e302.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e162.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e520.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e106.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e323.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e117.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e577.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e220.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e352.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e304.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e525.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e98.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e215.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e99.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e336.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e29.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e122.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e251.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e145.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e386.3\u0026thinsp;\u0026plusmn;\u0026thinsp;27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e28.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSED (clone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e40.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSED (location)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSED (clone \u0026times; location)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e_-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean year yields of 20 cashew germplasm clones evaluated under sub-optimal (Bole) and near optimal (Wenchi) environment.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e4-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e5-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e6-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e7-years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e364.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230.0\u003c/p\u003e \u003c/td\u003e \u003ctd 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\u003cp\u003e659.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e440.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e691.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e352.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e480.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e452.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e624.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e479.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e706.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e472.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e754.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSB 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e471.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e268.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e673.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e337.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e813.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e357.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e922.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e243.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e574.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e348.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e789.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e480.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e878.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e517.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1004.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e290.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e610.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e360.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e900.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e477.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e961.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e489.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1143.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e218.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e631.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e285.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e861.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e351.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e958.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e365.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1097.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e372.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e552.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e505.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e724.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e589.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e841.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e607.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e934.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e431.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e584.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e308.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e657.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e328.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e773.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e285.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e467.9\u0026thinsp;\u0026plusmn;\u0026thinsp;28.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e361.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e637.9\u0026thinsp;\u0026plusmn;\u0026thinsp;43.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e438.7\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e726.2\u0026thinsp;\u0026plusmn;\u0026thinsp;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e453.6\u0026thinsp;\u0026plusmn;\u0026thinsp;18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e811.8\u0026thinsp;\u0026plusmn;\u0026thinsp;57.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSED(Clone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSED(Location)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSED(Clone x Location)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e86.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the sub-optimal environment, clones SG 266, BE 575 and BE 203 consistently stood high among the top five clones for the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year (overall) average yields whereas in the near optimal environment clones SG 266, SG, 224, SG 014, SG 004 stood high (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). On the other hand, for the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year average yields, clones KT 2, SG 224, SB 9, SG 273 and AKC consistently stood low among the 5 worst clones whereas in the near-optimal environment near optimal environment, it was clones AKC, AKD, KT 1, KT 4, IDDM 29 and BE 739.. In comparing the two environments for average nut yields, the sub-optimal environment consistently recorded a low yield by 35%, 45.2%, 24.2%, 28%, 25%, and 28.3% for the first 2-year, 3-year, 4-year, 5-year, 6-year and 7-year average yields respectively (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the sub-optimal environment, an average nut weight of 4.8 g was recorded and the top five clones with the largest nut weight (\u0026ge;\u0026thinsp;5.1g) included BE 739, KT 5, SG 273, BAME 7 and BE 575 whereas in the near-optimal environment an average nut weight of 5.8g was recorded and BAMBOI 7, BE 739, KT 4, KT 5 and IDDM 29 were outstanding (nut weight\u0026thinsp;\u0026ge;\u0026thinsp;6.3g) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In comparing the two environments, the sub-optimal environment recorded a lower nut weight reduction of 21% than the near optimal environment.\u003c/p\u003e \u003cp\u003eFor shelling, the sub-optimal environment gave an average value of 28.6% and the top five clones with the highest shelling (\u0026ge;\u0026thinsp;28%) were IDDM 29, SG 224, SB 9, BE 203 and BAMBOI 7 whereas in the near-optimal environment an average of 30.1% was recorded with clones KT 2, BAMBOI 7, BAME 7, SG 014, and BE 203 being outstanding (shelling\u0026thinsp;\u0026ge;\u0026thinsp;30%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Comparatively, a shelling reduction of 6.4% was observed in the sub-optimal environment compared to the near - optimal environment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Nut yield patterns and response to selection based on early growth and yield traits\u003c/h2\u003e \u003cp\u003eFor this study, the first 2 - year, 3 - year, 4 - year, 5 - year, 6 - year and 7 -year(overall) average yields of the 20 cashew clones displayed a moderate biennial yield increase pattern under both sub-optimal and near optimal environment (Fig.\u0026nbsp;2). Average year yield increments in the sub - optimal environment were in the rates of 16%, 49.1%, 21,1%, 17.5% and 3.3% whereas in the near optimal the rates of 35%, 17.4%, 26.6%, 12.2% and 11% for the first 2 - year, 3 - year, 4 - year, 5 - year, 6 - year and 7 -year(overall) respectively (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eIn the sub - optimal environments, there was a significant response to selection for yield (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) based on survival rates, where the set of clones with the highest survival rates out yielded those with low survival (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However, in near - optimal environments, there was no significant difference in yield between the set of clones producing high survival rates and those producing low survival rates respectively. On the other hand, for height increments, there was a significant difference in yield selection between the set of clones producing taller trees than those producing shorter ones under both the sub-optimal (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and near - optimal environments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For canopy volume, there was a significant difference in yield between the set of clones producing canopies with high volumes than those producing low canopy volumes and selection response was significant under both near optimal (p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.047) and sub-optimal environment (p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eYield performance of cashew clones based on retrospective selection for agronomic traits trait under sub-optimal (Bole) and near optimal (Wenchi) environment.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEnvironment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYield (kg/ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eProbability\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvival\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e502.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e533.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e396.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanopy Volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e549.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e394.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNut weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e531.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e447.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e485.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e457.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.753\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e548.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e355.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 3 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e542.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e355.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e496.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e356.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e523.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e347.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 6 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-optimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e553.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e347.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvival\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e684.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e989.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e596.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanopy Volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e928.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e656.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNut weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e880.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e898.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e660.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e986.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e646.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 3 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e989.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e580.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1062.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e568.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1062.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e580.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage yield for first 6 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1074.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e568.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe retrospective effect of selection for high yields in the later years based on yields averaged over the first 2 - years, 3 - years, 4 - years, 5 - years and 6 - years of yield data recording years were also assessed with a t-test. There was a significant response to selection based on early average yields in first 2 - years ( p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001; p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.005 ), 3 - years( p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001; p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 4 - years ( p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.009; p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 5 - years ( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001; p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 6 - years ( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001; p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001), for later years\u0026rsquo; under sub-optimal and near optimal environments where the set of clones with high (n\u0026thinsp;=\u0026thinsp;5) early year average yields consistently out-yielded the set of clones with low (n\u0026thinsp;=\u0026thinsp;5) early year average yields respectively (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Figs.\u0026nbsp;3 \u0026amp; 4). Among these clones, although the response was significant during the overall average yield period (7 -years of production), the response in the relatively early production years (first 2 years average production) under both sub-optimal and near optimal environment were equally pronounced respectively (Figs.\u0026nbsp;3 and 4). Retrospectively, we also assessed the effects of selecting for higher yields based on nut weight and shelling values obtained in the early years of production. Interestingly, the were no significant selection response for nut weight under both sub-optimal and near optimal environments but there was significant selection response for shelling under near - optimal environment respectively. Overall, the response to selecting yields in later years based on survival, height, canopy volume and first\u0026thinsp;\u0026minus;\u0026thinsp;2 year average early yield were more pronounced in sub-optimal environments, whereas under near optimal environments, height, canopy volume and shelling were more pronounced.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Genotypic correlations among traits\u003c/h2\u003e \u003cp\u003eSurvival showed a strong and positive genotypic correlation coefficients (r\u0026thinsp;=\u0026thinsp;0.80) with the overall average yield data recording in the sub - optimal environment, whereas a moderate (r\u0026thinsp;=\u0026thinsp;0.47) correlation coefficient was recorded in the near- optimal environment respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). However, for plant height increments, a strong positive genotypic correlation coefficients with the overall yield data recording period was observed in both the sub - optimal environment (r\u0026thinsp;=\u0026thinsp;0.98) and near - optimal environment ( 0.80) respectively. Canopy volume also showed strong positive genotypic correlation coefficient with overall average yield recording in both the sub - optimal environment (r\u0026thinsp;=\u0026thinsp;0.80) and in the near-optimal environment (r\u0026thinsp;=\u0026thinsp;0.84) respectively. The first average yields at two-years (r\u0026thinsp;=\u0026thinsp;0.97), three-years (r\u0026thinsp;=\u0026thinsp;0.94), four-years (r\u0026thinsp;=\u0026thinsp;0.87), five-years (r\u0026thinsp;=\u0026thinsp;0.96) and six-years (r\u0026thinsp;=\u0026thinsp;0.98) of production showed strong significant genotypic correlation coefficients with overall yield period (seven - years) in the sub - optimal environment. Similarly, in the near optimal environment, average yields for the first two - years (r\u0026thinsp;=\u0026thinsp;0.75), three-years (r\u0026thinsp;=\u0026thinsp;0.88), four-years (r\u0026thinsp;=\u0026thinsp;0.95), five-years (r\u0026thinsp;=\u0026thinsp;0.98) and six-years (r\u0026thinsp;=\u0026thinsp;0.98) of production also showed strong genotypic correlation coefficients with overall average yield recording period. On the other hand, while nut weight showed a strong negative correlation with overall yield under sub-optimal environment, shelling showed a strong positive genotypic correlation coefficient with overall yield data recording (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGenotypic correlation coefficient estimates between survival, height, crown volume, nut weight, shelling, 2-year, 3-year, 4-year, 5-year, 6-year and overall average yield among 20 cashew clones evualueted at Bole (sub-optimal) and Wenchi (near optimal).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWenchi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvival (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanopy volume (m3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2-years average yield (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-years average yield (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4-years average yield (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.87***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-years average yield (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-years average yield (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNut weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.72**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Variance and Heritability of traits\u003c/h2\u003e \u003cp\u003eThe high genotype \u0026times; environment interaction variance recorded in this study accounted for the variable heritability values observed for the traits studied (Table S4). Heritability estimates generally decreased for average year yields. The highest heritability estimate was observed for the first 2-years (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.74) and first 3-years (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.60) average yield, whereas moderate estimates were obtained for shelling (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.52), height (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.51), first 4-years average yield (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.50), first 6-years average yield (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.42) and first 7-years average yield (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.47). However, low heritability estimates were obtained for survival (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.12), canopy volume (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.10), nut weight (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.11) and first 5 - years average yield (\u003cem\u003eh\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003ebs\u0026thinsp;=\u0026thinsp;0.20) (Table S4).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eTo develop a robust selection index which focuses on using juvenile traits that would be effective as selecting for yield in later years, we utilized cashew germplasm clones of varied origin and evaluated them in sub - optimal and near optimal field ecologies over a period of nine years. In our study, retrospective selection for high yields in later years of production based on survival, height, canopy volume and first 2 - years average yield in sub-optimal environment were effective whereas in the near - optimal environment height, canopy volume, shelling and first 2 - years average yields were effective. These observations imply that the set of juvenile traits optimal for selecting high cashew yield performers could vary with ecological conditions and this could be attributed to the significant clone, environment and clone \u0026times; environment interaction effects recorded in the current study. Our results in this study are therefore consistent with the findings of Kumar et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) who emphasized that in a sub - optimal ecologies, traits related to drought tolerance would receive higher weighting as an effective selection index compared to a near - optimal or irrigated environment, where the index might prioritize traits that maximize yield potential under favorable conditions.\u003c/p\u003e \u003cp\u003eThe effectiveness of selection indices that rely on a combination of juvenile traits in both the vegetative and early reproductive phases has been highly emphasized in many tree crop improvement programs (Akpertey et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Akpertey et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Padi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In the present study, juvenile traits like high survival rate, faster tree height gain with rapidly expanding canopies volumes and shelling together with the first 2 - year average yields were effective. These observations are consistent with the findings Akpertey et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) who emphasized that selection for stable high yields in later years for Kola (\u003cem\u003eCola nitida M.\u003c/em\u003e) may effectively rely on a combination of fast vegetative growth and the first 2-year average yields. Similarly, in Cocoa, early season vigour ratings in combination with early year yields were found to be effective as varieties with poor juvenile growth rate and low early yields were found to have poor yields (Padi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In coffee, the use of fruit set, span and the first three-year yields were over 70% as efficient as using overall seven-year yields in selecting superior varieties (Akpertey et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequentially, the huge financial resource investment that could accrue from relying on early years\u0026rsquo; performance to select for stable high cashew yields in later years compared to recording yield data over many years before final varietal recommendations is emphasized.\u003c/p\u003e \u003cp\u003eInterestingly, over the 9 - year duration of study, the biennial/ alternate bearing nature where a year of heavy yield (on-year) is followed by a year of low or light yield (off-year) was evident in the average year yield pattern in both the sub-optimal and near optimal environment. This phenomenon has been attributed to both heavy fruit load, which suppresses flower bud formation for the next season and depleting tree resources, which are influenced by hormones like gibberellins (GAs) and auxins (Krasniqi et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Salari \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). While this biennial bearing habit could vary with crop species, genetics play a significant role as some cultivars of other crops inherently favor this cycle. Nevertheless as the alternate bearing phenomenon affects both high and low yielding varieties, selection of clones like SG 266, BE 203, BE 204, SG 004, BE 575 for sub-optimal environment and SG 266, SG 224, SG 014, KT 5, SG 004 for near optimal environment in the early production years and advancing them in the breeding cycle would allow the cultivation of only targeted clones that can be planted in larger orchards to increase production.\u003c/p\u003e \u003cp\u003eWhile a typical cashew orchard will reach full bearing in the 10th year after planting (Agrifarming \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), in our present study, average yields continue to increase exponentially even at the 9th year of production. Such yield increases are expected and could vary with the environment until canopies close interlock/overcrowd before yields decline will set in. This phenomenon has been expressed in other tree crops where a yield decline from interlocking canopies and has been attributed to reduced light interception and utilization by the photosynthetic surface (Akpertey et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Further, in many tree crops breeding trials, varietal selections are made when the trees had attained maturity, because the high environmental effect (error) decrease with age (Jones et al., 1957; Padi et al., 2016). Contrastingly, our study which relied on average year yields build up to maturity reported moderate to high heritability values in the early year yields and decreased towards maturity. Our result are consistent with other findings, as moderate heritability estimates for early year average yields in cashew have been reported (Das \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our reports therefore re-emphasize the higher weights attached to the use of higher early year yield traits as an effective selection index for superior clonal cashew varieties. On the other hand, low heritability estimates were recorded for survival, nut weight and canopy volume in our study and our results are in concurrence with similar values reported for these traits in other studies (Adu-Gyamfi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Dadzie \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Daouda et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Das \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Nevertheless, their high correlation with the overall yield performance in later years at the genotypic level suggest that selection for high yielding cashew clones based on these traits in the early years of the breeding program would be as good as selection in later years. In a Kola selection breeding program, Akpertey et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) similarly found low heritability values for vegetative traits, yet they were effective in selecting high yield performing genotypes in later years of production.\u003c/p\u003e \u003cp\u003eThe value of genotypic correlations among agronomic traits in the development selection index in many studies have been overlooked even though conflicting correlations between multiple traits could result in sub-optimal selection response (Grattapaglia et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Interestingly, while genotypic correlations between shelling and yield in later years of production were not significant under both environment, their selection were effective under near - optimal environment. Similar observations have been made in other studies which suggest that as long as genetic variance is high selection can still be effective if traits are not genetically correlated (Ata-Ul-Karim et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Muir and Pease \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). On the other hand, nut weight although gave a significant negative genotypic correlations with yield in later years of production, their response to selection under both environments were not effective. This could be attributed to a combination of genetic, environment and selection methods as highlighted in many studies indicating that significant genotypic correlation between traits does not guarantee effective selection response.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe lengthy cashew breeding programs is costly and has led to a limited number of cultivated clonal varieties that have been propagated over a long period of time. This has lead to susceptibility to drought, disease and insect. Our trial focused on identifying a set of juvenile traits that would be effective as selecting for high yield performance in later years of production. Retrospective selection for survival, height, canopy volume and first 2 - year average yield resulted in gains in identifying cashew clones with higher yields early in the cashew breeding program under sub-optimal environment whereas in the near - optimal environment height, canopy volume, shelling and first 2 - year average yield were effective. Based average yields across years, a biennial yielding pattern was evident among the clones and their ranking were consistent across the years. Genotypic correlation coefficient estimates were significant between yield in later years of production and survival, height, canopy volume, nut weight and 2 - year average yield under sub-optimal environment whereas under near optimal environment, height, canopy volume, shelling and 2 - year average yield were significant respectively. While, selection response for most correlated traits gave positive response, selcting for high yield in later years using nut weight was not effective. Our results therefore suggest the identified traits would advantageous in selecting productive and efficient clones early in the cashew breeding program, that the set of juvenile traits effective for selection could vary with ecological conditions.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003eThe authors declare that there are no conflict of interest.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Archiving statement\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors acknowledge the support of the Deutsche Gesellschaft f\u0026uuml;r Internationale Zusammenarbeit GmbH (GIZ) with funding through Commcashew, the African Development Banak (AfDB) and the Cocoa Research Institute of Ghana (CRIG).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePKKAG conceived and designed the experiment. PKKAG, AA, GA, SA, YB, performed the experiment, collected and analyzed data and wrote the manuscript. PA and SOA all assisted with data collection and provided significant editorial and analytical advice.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eACA (2022) Cashew Market Analysis: Africas Share of the EU Market Production Increase African Cashew Alliance. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.africancashewalliance.com/en/news-and-info/blog/cashew-market-analysis-africas-share-eu-market-production-increase#:~:\u003c/span\u003e\u003cspan address=\"https://www.africancashewalliance.com/en/news-and-info/blog/cashew-market-analysis-africas-share-eu-market-production-increase#:~:\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003etext=Though%20Benin's%20official%20estimate%20for,production%2C%20according%20to%20Jim%20Fitzpatrick.\u0026amp;text=Cashew%20processing%20remained%20highly%20concentrated,the%20support%20of%20development%20partners. 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L, climate change, selection index, Biennial bearing","lastPublishedDoi":"10.21203/rs.3.rs-9210569/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9210569/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe breeding of cashew varieties is expensive and time-consuming and the identification of a selection criterion that could rely on juvenile traits to effectively select for superior clones in later years of production could constitute a viable strategy to sustain production. We evaluated 20 cashew clones of varied origins over a 9 - year period under sub-optimal and near-optimal environment for growth and yield traits respectively. The trial was laid out in a randomized complete block design with four replications. There were significant clone \u0026times; environment interaction effects for most traits. Under sub-optimal environment, high genotypic correlations were found between overall yield and survival, height, canopy volume, nut weight and the first 2-years, 3-years, 4-years, 5-years and 6-years of production whereas under near-optimal environment height, canopy volume, first 2-years, 3-years, 4-years, 5-years and 6 years of production years were high. Heritability ranged from 0.10\u0026ndash;0.51, 0.11\u0026ndash;0.52 and 0.20\u0026ndash;0.74 for vegetative traits, nut quality traits and yield across years of production respectively. Under sub-optimal environment, selection for survival, height with rapidly expanding canopies and yield during the first 2 years of production were effective whereas under near-optimal environment selection for height with rapidly expanding canopies, shelling and yield during the first 2 years of production were effective. Our study suggest that the set of traits optimal for selection of high yield performers could vary with ecology and the identified criterion has a large potential to identify the most productive clones early in the cashew breeding program.\u003c/p\u003e","manuscriptTitle":"Multi-trait selection index for high clonal cashew (Anacardium occidentally. L.) yield performance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-30 08:42:01","doi":"10.21203/rs.3.rs-9210569/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d154abfa-a93c-40b5-82fa-ab71f15d06b7","owner":[],"postedDate":"March 30th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"69209817362376373242686206538705659504","date":"2026-05-09T10:12:27+00:00","index":17,"fulltext":""},{"type":"reviewerAgreed","content":"225486156381211642649160481599737583202","date":"2026-05-09T08:44:20+00:00","index":16,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T20:30:47+00:00","index":14,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T08:42:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-30 08:42:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9210569","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9210569","identity":"rs-9210569","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}