Total Yield Variation Research Articles

Genotype-environment interaction for grain yield in maize (Zea mays L.) using the additive main effects and multiplicative interaction (AMMI) model

Genotype-environment interaction consists of the different response of individual genotypes resulting from changing environmental conditions. Its significance is a phenomenon that makes the breeding process very difficult. On the one hand, the breeder expects stable genotypes, i.e., yielding similarly regardless of environmental conditions. On the other hand, selecting the best genotypes for each region is one of the key challenges for breeders and farmers. The aim of this study was to evaluate genotype-by-environment interaction for grain yield in new maize hybrids developed by Plant Breeding Smolice Co. Ltd., utilizing the additive main effects and multiplicative interaction (AMMI) model. The investigation involved 69 maize (Zea mays L.) hybrids, tested across five locations in a randomized complete block design with three replications. Grain yield varied from 8.76 t ha–1 (SMH_16417 in Smolice) to 16.89 t ha–1 (SMH_16043 in Płaczkowo), with a mean yield of 13.16 t ha–1. AMMI analysis identified significant effects of genotype, environment, and their interaction on grain yield. Analysis of variance indicated that 25.12% of the total variation in grain yield was due to environment factor, 35.20% to genotypic differences, and 21.18% to genotype by environmental interactions. Hybrids SMH_1706 and SMH_1707 are recommended for further breeding programs due to their high stability and superior average grain yield.

Effects of Surface Area and Water Level Variability on Fisheries Production in Lake Naivasha, Kenya

Lake Naivasha is a freshwater, a Ramsar site and an Important Bird Area. It provides multiple services to the surrounding communities such as Fishing, Tourism and Agriculture. Lake Naivasha has been experiencing a water level variation cycle over the years as a result of it being shallow and experiencing high evaporation. Variation in water levels leads to flooding, and receding which disrupts the Lake ecosystem thus causing direct and indirect effects on fishing. The study was conducted to establish the relationship between Surface area and water level variability and fish yield and revenue in Lake Naivasha. Primary data was collected using a semi-structured questionnaire, and Key informant interviews. Secondary data was collected using Landsat images that provided the temporal and spatial water level variability and documentary analysis between 1989 to 2022. Both descriptive statistics and inferential statistics were used for data analysis. The results show a positive correlation between Surface area Variability and fish yield (r= 0.6261, R2= 0.3920) and fish revenue (r= 0.5219, R2= 0.2724). Surface area variability accounts for 39% of the variation in total fish yield, and 27% of the fish revenue. The study recommends continuous monitoring and surveillance of the lake level, and water quality by the relevant government agencies, as well as watershed management and conservation measures for the sustainability of the Lake’s fishery.

AMMI GGE biplot analysis of wheat genotypes under heat stress and heat drought environment

Wheat is the third most important cereal crop of Nepal. Climatic changes have been a major threat on overall production and productivity of wheat in Nepal. With the aim of evaluating twenty elite wheat genotypes under heat stress and heat drought environments, a field experiment was conducted using alpha lattice design at Bhairahawa, Rupandehi, Nepal. The analysis of variance (ANOVA) revealed significant differences in the yield across wheat growing environments (p<0.001). Environment explained 75.11% of the total variation in grain yield. NL 1404 was the most stable followed by NL 1368, and NL 1413. NL 1376, NL 1369. NL 1386 was the best adapted genotypes under heat stress environments whereas NL 1384, Gautam, and BL 4949 were best adapted to heat drought environments. NL 1346 was the best genotype. WWW model explained NL 1346 won under heat drought environment and NL 1384 under heat stress environment. Mean vs. stability model showed NL 1346 was the above yielder and stable genotype. In ranking, NL1179 was concluded to be the ideal genotype. From the study, NL 1368 was found to be the winning genotype under heat drought and heat stress environments. These genotypes should further be evaluated to release as a variety.

The influence of planting window on yield stability of maize genotypes in semi-arid areas

Maize is one of the most important field crops for feed, food, and raw material in South Africa. It is the main staple food for the majority of the people impoverished households in South Africa. Maize is susceptible to drought, and erratic rainfall and extreme climate variation are major maize production constraints in South Africa. This study aimed to determine the influence of planting dates on the grain yield stability of six maize genotypes in five environments for three (2019/20 to 2021/22) consecutive seasons. The additive main effect and multiplicative interaction (AMMI) model indicated that the environment contributed 59.20 % and 47.76 % of the total variation in grain yield at planting dates one (PD1) and two (PD2), respectively. The magnitudes of the genotype x environment interaction sum of squares were 5.20 for PD1 and 12.30 for PD2 times that of the genotype (genotype) sum of squares for the grain yield (GEI). The first principal component accounted for 53.14 % (PD1) and 47.76 % (PD2) of the total variation in the dataset. The AMMI genotype superiority measure (Pi), genotype and genotype by environment interaction (GGE), yield stability index, and AMMI stability value analyses identified genotypes DKC75–65BR and DKC78–45BRGEN as stable and high yielding across environments and planting dates. Genotype DKC71–44B was the least stable at both planting dates. Bothaville (E7) for PD1 and Coligny 2021/22(E13) for PD2 had high yield potential and were favorable environments, whereas Potchefstroom 2019/20 and 2021/22 were the least favorable environments for PD1 and PD2, respectively.

Agronomic performance and yield stability of extra-early maturing maize hybrids in multiple environments in the Sahel

Frequent occurrence of drought, heat, low soil fertility and Striga infestation are the main stress factors reducing maize yield in the Sahel. Adoption of stable multiple stress tolerant maize cultivars in the region is crucial for achieving food security. However, selection of a stable high yielding cultivar is complicated by genotype × environment interaction (GEI) due to differential responses to growing conditions. Eleven extra-early maturing multiple-stress tolerant maize hybrids and two checks arranged in a randomized complete block design was evaluated across nine locations for two years in Mali and Niger. The objectives of this study were to identify (i) stable and high-yielding maize hybrids, and (ii) suitable test locations for selecting promising extra-early maize hybrids. GGE biplot was used for graphical analysis. Significant genotype, location and GEI effects were detected for grain yield and number of ears per plant. EEWQH-13 produced the highest grain yield (3860 kg ha−1) while EEYQH-1 had the poorest yield (2663 kg ha−1) with trial mean of 3395 kg ha−1 for all hybrids. GGE biplot explained 69.6 % of the total variation in grain yield among the hybrids. The polygon view identified EEWQH-13 as the best hybrid across six of the nine test locations. EEPVAH-58 was identified as the most stable high yielding hybrid across the nine test locations followed by EEWQH-16 and EEWQH-13. The nine locations were clustered under two mega-environments (ME1, ME2). Among the nine test locations, Tara and Aderaoua clustered in ME1 were the most suitable ones for selecting promising extra-early maize hybrids for wider adaptation. The three hybrids, EEPVAH-58, EEWQH-16, and EEWQH-13, identified in this study could be recommended for on-farm evaluation to confirm the consistency of their yield performance for possible release and commercialization in Mali and Niger.

RESPONSIVENESS OF POTATO VARIETIES TO BALANCED MINERAL FERTILIZER APPLICATION RATES

The effectiveness of applying balanced rates of mineral fertilisers for potatoes was studied in the forest-steppe zone of the Southern Urals, taking into account potato varieties and agronomic practices. It was established that the crucial factor affecting the formation of planned tuber yields is the level of mineral nutrition, which accounted for 67% of the yield variation in 2019, 40% in 2020, 45% in 2021, and 39% under the conditions of 2022. For comparison, the planting density determined the variation by 8.4%, 41.5%, 37.2%, and 23.2%, respectively, and the genotype accounted for 15.2%, 10.9%, 14.3%, and 13.2% of the total tuber yield variation. In 2022, single irrigation of potatoes determined 20.4% of this parameter's variance. The fertiliser rate calculated to achieve the planned yield of 40 t/ha led to an average increase in tuber yield for the Zakhar variety by 8.16 t/ha, Kashtak by 9.08 t/ha, Amulet by 7.76 t/ha, and Cavalier by 9.75 t/ha. The fertiliser rate calculated for a 60 t/ha yield increased by 13.56, 12.92, 14.71, and 18.33 t/ha, respectively. The target tuber yield of 40 t/ha was achieved by the Zakhar (39.8 t/ha) and Kashtak (41.8 t/ha) varieties in 2019 (correlation coefficient 0.91), Amulet (39.1 t/ha) in 2020 (correlation coefficient 0.85) with a planting scheme of 75 x 19 cm, Cavalier (38.7 t/ha) in 2021 (correlation coefficient 0.39), and Amulet (41.8 t/ha) in 2022 with a planting scheme of 75 x 14 cm. The planned yield of 60 t/ha was achieved by the studied varieties only in 2022 with single irrigation (300 m3/ha) and a dense planting scheme (75 x 14 cm) for Amulet (60.9 t/ha) and Cavalier (58.4 t/ha), also with a planting scheme of 75 x 19 cm. The formation of planned potato yields in the forest steppe of the Chelyabinsk region can be ensured by cultivating adaptive varieties of local selection (Zakhar, Kashtak, Amulet, and Cavalier) and regulating the water regime through critical irrigation. In 2022, potato irrigation increased the average yield by 11.1 t/ha for Cavalier, 10.7 t/ha for Kashtak, 10.6 t/ ha for Zakhar, and 10.1 t/ha for Amulet compared to the rain-fed variant, thereby increasing the profitability of mineral fertilisers with an additional tuber yield by 1.5 to 2 times.

Stability analysis for fodder yield of oat (Avena sativa L.) genotypes using univariate statistical models under diverse environmental conditions in Ethiopia

Oat (Avena sativa L.) is one of the most important dual-purpose cereal crops cultivated under diverse environmental conditions in Ethiopia. The fodder dry matter yield stability analysis was conducted using twenty-four oat genotypes across nine environments in a randomized complete block design with three replications. The study aimed to evaluate the magnitude of genotype by environment interaction and determine the stability of oat genotypes for fodder yield using 14 univariate stability parameters. The pooled analysis of variance revealed that the genotype, environment, and their interaction effects had variation (p < 0.001) for fodder yield. The contribution of environment for the total fodder yield variation was the highest (67.45%) followed by the interaction (22.73%) and genotypic (9.82%) effects. The results of stability analysis showed that high fodder yield-producing genotypes had stable performance using the stability parameters of genotypic superiority index (Pi), yield stability index (YSI), coefficient of determination (R2), and coefficient of variability (CVi), demonstrating that selection of oat genotypes using these stability parameters would be effective for fodder yield improvement. Moreover, Spearman's rank correlation coefficients indicated that the stability parameters of Pi, YSI, R2, and CVi had a significant positive association with fodder dry matter yield (FDMY). On the contrary, the FDMY had non-significant inverse relations with the remaining stability parameters except Bi, suggesting that the selection of oat genotypes using these stability parameters would not be effective for fodder yield improvement. Therefore, G6, G7, G9, G10, and G23 were desirable genotypes for fodder yield improvement programs in Ethiopia.

Estimating grain and biomass yield of bread wheat genotypes by optical sensors

Use of optical sensors in wheat breeding programs can provide convenience in predicting the grain and biomass yield. In this study, optical sensors were used to estimate the grain and biomass yield of different wheat genotypes. Field trials were conducted with 49 wheat genotypes in three different WST (full irrigation (FI), supplementary irrigation (SI), and rainfed) in Central Anatolia (Eskisehir Province) in the 2011 and 2012 growing seasons. The genotypes were significantly different in grain yield, biomass weight (BM), LAI, and NDVI, SPAD ZD 55 (SPAD measured on ZD 55) was the most critical variable to predict grain yield, it was significantly correlated with grain yield in all three water supply conditions. Similarly to SPAD ZD 55, NDVI ZD 31, and LAI ZD 41 were the most significant attributes to predict BM in all three water supply cases. Multiple linear regression equation developed using independent variables of SPAD ZD 55, NDVI ZD 60, NDVI ZD 31, and NDVI ZD 24 described 52 % of the total variation in grain yield of 49 genotypes. The genotypes were highly consistent in the relationship between grain yield and SPAD ZD 55 and the relationship between BM and LAI ZD 41 in all three water supply cases. The results were promising to predict grain yield of highly different wheat genotypes under different water supply regimes. However, more research is needed to conceptualize relationships between yield and sensor measured variables in wheat genotypes across different environments and soil settings.

Performance and Yield Stability of Quality Protein Maize (Zea mays L.) Hybrids under Rainfed Condition

Abstract Quality protein maize (QPM) commercialization can combat the food and nutritional insecurity that is common in some developing nations of the world. Evaluation of QPM hybrids under varying rainfed environments provide valuable evidence for the selection of the most productive genotypes for the target environment. The present study was conducted at three locations to assess the agronomic performance and the grain yield stability of 11 QPM and 2 commercial hybrids (checks) over two years. There were significant (p ≥ 0.01) differences among the environments in the expression of all measured traits while genotype as well as genotype × environment interaction also differed significantly for all the traits except for husk cover and Anthesis-silking interval. The tested QPM hybrids outperformed the local and reference checks by 17.28% and 29.47% respectively. The biplot explained 85.3% of the total variation in yield, with 65.4% attributed to principal component 1 and 19.9% to principal component 2. Three vertex hybrids, EWQH-25, EWQH-21 and Local Check, were identified as the most responsive in the environments within which they fall. Hybrid EWQH-21 produced the highest yield across all environments but was unstable. Therefore, hybrids EWQH-22, EWQH-9, and EWQH-13, with similar yield values and more stable performances were recognized as ideal across environments. Lapai 2017 (E2) proves to be both representative and discriminative, making it the ideal test environment for selecting hybrids with broad adaptability. The study concludes that EWQH-9, EWQH-13, and EWQH-22 be recommended for cultivation across the environments while EWQH-21 be recommended for the specific area of adaptation.

Selection of High-Yielding and Stable Genotypes of Barley for the Cold Climate in Iran.

The interaction between genotypes and environments plays an important role in selecting superior genotypes for target locations. The main objectives of the present study were to analyze the effect of the genotype-by-environment interaction (GEI) and identify superior, newly developed, and promising barley genotypes for cold regions in Iran. For these purposes, a set of genotypes obtained from breeding programs for cold climates in Iran, along with two reference genotypes, were investigated at eight research stations (Tabriz, Ardabil, Arak, Miandoab, Mashhad, Jolge Rokh, Karaj, and Hamadan) during two consecutive growing seasons (2019-2020 and 2020-2021). The results of the freezing test (LT50) showed that most of the tested genotypes had significant cold tolerance at the seedling stage. Based on the additive main effect and multiplicative interaction (AMMI) analysis, environment (E) and GEI effects explained 49.44% and 16.55% of the total variation in grain yield, respectively. Using AMMI1 and AMMI2 models, G2 and G20 were found to be superior genotypes in terms of grain yield and stability. Moreover, AMMI-based stability parameters considered the G20 genotype to be the ideal genotype. A two-plot analysis of the genotype-by-environment interaction (GGE) biplot showed that the 16 experimental environments were grouped into 2 mega-environments. Of the test environments, ARK1 and KAJ2 had the highest discriminating power and representativeness ability, and these were identified as ideal environments for testing advanced genotypes for yield and stability performance during early barley breeding practices in cold areas in Iran. In conclusion, both AMMI and GGE biplot models identified several superior genotypes, among which G20, with a high average yield relative to the overall average yield and the lowest IPC1 score, was found to have high yield stability and is recommended for inclusion in breeding programs for cold climates in Iran.

Stability and Performance Evaluation of Advanced Bread Wheat (Triticum aestivum L.) Genotypes in Low to Mid Altitude Areas of Ethiopia

Twenty three advanced bread wheat genotypes have been evaluated against two released bread wheat varieties in 2018−19 and 2019−20 in nine diverse environments of Ethiopia. The experiment was laid out using alpha lattice design with three replications. Ten stability models were employed in order to assess stability and performance of 23 advanced bread wheat genotypes. Combined analysis of variance for grain yield has revealed that the environments, the genotypes and GEI effects were significantly different (p&lt;0.001). In the present study, Environments, GEI and Genotypic effects accounted for 88.6%, 8.3% and 3.1% of the total grain yield variation, respectively. Twelve bread wheat genotypes, ETBW 9136, ETBW 9139, ETBW 9065, ETBW 9080, ETBW 9172, ETBW 9396, ETBW 9452, ETBW 9641, ETBW 9642, ETBW 9646, ETBW 9647 and ETBW 9648 produced grain yield that raged from 5.4 to 5.8 t ha-1, indicating their superior yielding potential. ETBW 9136, ETBW 9139, ETBW 9172, ETBW 9396, ETBW 9452, ETBW 9641, ETBW 9642 and ETBW 9646 were the most stable bread wheat genotypes as confirmed by five to ten stability models. However, ETBW 9452, ETBW 9641, ETBW 9642, ETBW 9646, ETBW 9647 and ETBW 9648 were susceptible to either stem rust or yellow rust or both. Providentially, ETBW 9136, ETBW 9139, ETBW 9172 and ETBW 9396 were superior yielding, stable, resistant and moderately resistant to wheat rusts. Thus, these four genotypes were the most promising advanced bread wheat genotypes to be verified and released in low to mid altitude areas of Ethiopia.

Character Association Analysis on Morpho-physiological and Yield Parameters of Rice (Oryza sativa L.) under Water Stress

The present character association study aims to understand the correlation between morphological, physiological and yield traits of rice genotypes under water stress and non-stress conditions, so as to identify the differentially expressing traits under both the conditions. Such differentially expressed traits with positive influence on yield can serve as selection criteria for selection of stress tolerant plants. The experiment was carried out using randomized complete block design with three replications at the department of plant breeding and genetics, college of agriculture, Kerala Agricultural University between December 2021 and March 2022. Sixteen characters pertaining to morphological, physiological and yield of three rice genotypes were recorded under reproductive stage water stress and non-stress conditions. The intensity of trait correlations varied significantly under drought and non-drought conditions. The results of correlation studies indicate positive and significant correlation of grain yield with number of tillers, 1000 grain weight, photosynthetic rate, inter cellular CO2 content and water use efficiency under well-watered condition and of these, 1000 grain weight, and inter cellular CO2 content had significant positive influence on grain yield under drought stress. Principal component analysis results indicated two principal components i.e., PC1 and PC2 accounted for 70.5% and 29.5% of the total variation in grain yield under drought and 89% and 11% respectively under non drought conditions. Correlation and principal component analysis concluded that plants with higher grain weight along with improved high internal carbon dioxide content in leaves can be selected for attaining high yield potential under drought and non-drought conditions and will serve as climate adaptive crops under varying soil moisture levels.

Foliar fungicides help maize farmers reduce yield gaps in late sown crops in a temperate region

Foliar diseases produce significant maize (Zea maize L.) yield reductions, increasing yield gaps and threatening food security. In the central temperate region of Argentina 50 % of maize cropped is grown under late sowing dates (December), where meteorological conditions are favorable to disease development, such as higher temperatures during initial stages and higher relative humidity. However, no major testing was reported to fully understand yield responses to foliar fungicides. Our objectives were to quantify the impact of foliar fungicide application on grain yield in late sown crops, and to identify genotype, management, and environmental interactions modulating the yield response. We conducted 21 on-farm trials during 6 growing seasons (2014/15 and from 2016/17 to 2020/21) with and without a fungicide, each trial having 8–20 commercial hybrids. Fungicide application was done between V8 and V12 stages (eight and twelve fully expanded leaves, respectively), using a commercial fungicide mix of azoxystrobin and cyproconazole. Average yield variation across sites ranged from 4359 to 12,101 kg ha−1, and fungicide use produced an average positive yield increase of 472 kg ha−1 (or 5.8 %). The yield increase varied from no response to 1282 kg ha−1 across sites, and was not correlated to the site yield. Fungicide application explained 1.9 % of the total yield variation, higher than its interaction with either site or genotype (1.1 and 0.1 % of total yield variance, respectively). Mean temperature from sowing to V14 (fourteen fully expanded leaves) helped explain the crop yield response variation to fungicide application across sites, increasing by 138 kg ha−1 °C−1 in response to higher mean temperature (explored temperatures from 21.9 to 26.4 °C). Our results illustrate the relevance of fungicide applications to reduce yield gaps, where described predictors can help farmer optimize this decision.

Photothermal Quotient-An Effective Thermal Index for Evaluation of Lentil (Lens culinaris L.) Phenology and Yield in the Lower Gangetic Plains

Background: Sowing time and variety-specific genetics influence the phenological development of lentil (Lens culinaris L.), affecting its heat and solar energy utilization for attaining satisfactory yield. The present study was conducted to assess how the different thermal indices behaved in explaining variation in phenology and yield components with corresponding effects on yield of lentil varieties grown under varying sowing dates. Methods: The experiment comprised of four sowing dates in the main plots and five lentil varieties in the sub-plots, laid out in a split-plot design replicated thrice. The phenology, yield components and yield were recorded. The computed thermal indices and correlation and regression analyses were used to assess their effects on yield traits and yield. Result: Sowing after 7th November reduced lentil yield by 13.6-22.5 kg ha-1 day-1 and 0.9-2.1% ha-1 day-1 on absolute and relative basis, respectively. The varieties WBL 77 and HUL 57 were less sensitive to temperature fluctuations resulting in stable yield performance under varying thermal regimes. Despite significant influence of temperature on yield traits, growing degree days explained 82.0-89.0%, while photothermal quotient (PTQ) explained 92.0-96.0% of the total variation in yield. PTQ emerged as a reliable yield predicting thermal index and might be used for breeding climate-smart lentil varieties.

Multi-location evaluation of mungbean (Vigna radiata L.) in Indian climates: Ecophenological dynamics, yield relation, and characterization of locations.

Crop yield varies considerably within agroecology depending on the genetic potential of crop cultivars and various edaphic and climatic variables. Understanding site-specific changes in crop yield and genotype × environment interaction are crucial and needs exceptional consideration in strategic breeding programs. Further, genotypic response to diverse agro-ecologies offers identification of strategic locations for evaluating traits of interest to strengthen and accelerate the national variety release program. In this study, multi-location field trial data have been used to investigate the impact of environmental conditions on crop phenological dynamics and their influence on the yield of mungbean in different agroecological regions of the Indian subcontinent. The present attempt is also intended to identify the strategic location(s) favoring higher yield and distinctiveness within mungbean genotypes. In the field trial, a total of 34 different mungbean genotypes were grown in 39 locations covering the north hill zone (n = 4), northeastern plain zone (n = 6), northwestern plain zone (n = 7), central zone (n = 11) and south zone (n = 11). The results revealed that the effect of the environment was prominent on both the phenological dynamics and productivity of the mungbean. Noticeable variations (expressed as coefficient of variation) were observed for the parameters of days to 50% flowering (13%), days to maturity (12%), reproductive period (21%), grain yield (33%), and 1000-grain weight (14%) across the environments. The genotype, environment, and genotype × environment accounted for 3.0, 54.2, and 29.7% of the total variation in mungbean yield, respectively (p < 0.001), suggesting an oversized significance of site-specific responses of the genotypes. Results demonstrated that a lower ambient temperature extended both flowering time and the crop period. Linear mixed model results revealed that the changes in phenological events (days to 50 % flowering, days to maturity, and reproductive period) with response to contrasting environments had no direct influence on crop yields (p > 0.05) for all the genotypes except PM 14-11. Results revealed that the south zone environment initiated early flowering and an extended reproductive period, thus sustaining yield with good seed size. While in low rainfall areas viz., Sriganganagar, New Delhi, Durgapura, and Sagar, the yield was comparatively low irrespective of genotypes. Correlation results and PCA indicated that rainfall during the crop season and relative humidity significantly and positively influenced grain yield. Hence, the present study suggests that the yield potential of mungbean is independent of crop phenological dynamics; rather, climatic variables like rainfall and relative humidity have considerable influence on yield. Further, HA-GGE biplot analysis identified Sagar, New Delhi, Sriganganagar, Durgapura, Warangal, Srinagar, Kanpur, and Mohanpur as the ideal testing environments, which demonstrated high efficiency in the selection of new genotypes with wider adaptability.

Limited impacts of climatic conditions on commercial oil palm yields in Malaysian plantations

BackgroundOil palm is a key driver of deforestation, but increasing yields in existing plantations could help meet rising global demands, while avoiding further conversion of natural habitat. Current oil palm plantations present substantial opportunities for sustainable intensification, but the potential for local yield improvements depends partly on the role of climate in determining yield.MethodsWe determine the importance of local climatic conditions for oil palm yields in 12 commercial plantations in Peninsular and East Malaysia (Borneo), during 2006–2017. We quantify relationships between climatic conditions (raw and anomalised monthly temperature and rainfall data) and yield for lag times up to 36 months prior to harvest, corresponding to key stages in oil palm fruit development.ResultsOverall, climatic conditions explained < 1% of the total variation in yield. In contrast, variation in yield among plantations accounted for > 50% of the explained variation in yield (of total R2 = 0.38; median annual fresh fruit bunch yield 16.4–31.6 t/ha). The main climatic driver of yield was a positive effect of maximum monthly temperature during inflorescence development (Spearman’s Rho = 0.30), suggesting that insufficient solar radiation is the main climatic constraint to yield in our study sites. We also found positive impacts of rainfall during key stages of fruit development (infloresence abortion and sex determination: Spearman’s Rho 0.06 and 0.08 respectively, for rainfall anomalies), suggesting minor effects of water-limitation on yield; and a negative impact of maximum temperature during the month of harvest (Spearman’s Rho – 0.14 for temperature anomalies), suggesting possible heat stress impacts on plantation workers.ConclusionsOur findings imply a relatively minor role of climate in determining yield, and potentially substantial yield gaps in some commercial plantations in Malaysia (possibly up to ~ 50%). Thus, there appear to be substantial opportunities for improving oil palm yield in existing plantations in Malaysia, with further research needed to identify the drivers of such yield gaps.

The Effects of Vetiver Grass (Vetiver Zizanodes L.) on Soil Fertility Enhancement, Soil Water Conservation, Carbon Sequestration and Essential oil Productions A: Review

Genotype x environment (GxE) interaction and yield-stability analysis is an imperative in measur­ing varietal stability and suitability for cultivation over seasons and ecological zones. Developing high performing and stable genotypes across different locations is of most importance to plant breeders. This study was conducted using 84 hybrid lines to identify the most stable and high yielding genotypes. To gain these objective, multiple-environmental trials (MET) was undertaken annually across locations. AMMI model has shown that the largest proportion of the total variation in grain yield was attributed to environments and somehow to genotypes. GGE bi-plot analysis also visualized the winner genotype at each area and to identify high yielding and stable genotypes. The genotype with the high yield in SR is G66, and in KB G27, G10, G79, in SH G25, G78, G86 and G68 while, in SR the best genotypes is G66. The other vertex genotypes (G1, G32, G51, 71 and G26 are poorest in all environments. Environments, AM and SH exerted strong interaction forces while the rest two did less. On the other hand, the genotypes near the origin are not sensitive to environmental interaction and those distant from the origins are sensitive and have large interaction. Hence, G1, G5, G66, G71, G18, G10 and G25 had more responsive since they were far away from the origin whereas the genotypes G54, G29, G23, G4, G9, G5, G43, G13 and G7 were close to the origin and hence they were less sensitive to environmental interactive forces while genotypes G38, G11, G45 and G76 were the most closest to the origin and hence had almost no interaction forces. Generally, G74 can be recommended for specific adaptation whereas G2 and G16 relatively for broader adaptation. Keywords: AMMI; GEI; genotype; environment; model; stability , GGE biplot DOI: 10.7176/JNSR/13-5-04 Publication date: March 31 st 2021

Variability of Siberian stone pine seed yield in introduction plantations in the Vologda region

Selection of high-yielding samples of Siberian stone pine in artificial plantations created outside its habitat potentially improves the quality of work on its introduction. The study represents an assessment of the level of individual variability of Siberian stone pine by seed yield in the context of introduction (taking into account its variation by years of crop generation). Studies were conducted in the annually seeding Chagrinsky cedar grove located in the Gryazovetsky District of the Vologda Region. Sample trees were selected to observe the dynamics of seed formation in the plantation. Observations allowed us to conclude about the irregularity of yields from year to year and high variability in the volume of yields among individual trees. A significantly pronounced effect on the seed yield of Siberian stone pine is recorded both in terms of the year of cone generation and individual variability of the trees. Individual characteristics account for 41% of the total variation in yield, while the year of observation accounts for only 21%. Dependence on individual variability slightly decreases with the increasing duration of observations, which may be due to chronographic variability in the reproductive capacity of the trees. It was concluded that the selection of maternal producers for the creation of high-yielding plantations is advisable. At the same time, the increased observation period for the reproductive capacity of individual trees makes it possible to increase the efficiency of selection. To reduce the duration of observations, it was recommended to use the ratio of crown width to crown length as a correlative feature. Nevertheless, in some non-yielding years, the relationship between the yield and this feature may not be evident. For this purpose, the trees with the lowest value of this indicator should be selected as high-yielding ones.

Stability and Performance Evaluation of Advanced Bread Wheat (Triticum aestivum L.) Genotypes in Optimum Areas of Ethiopia

Multi-environment trials were carried out at 11 locations in different wheat growing zones of Ethiopia during 2017–18 and 2018–19 to identify high yielding, stable, biotic and abiotic stresses resistant varieties with improved quality traits for commercial release. Twenty-eight advanced bread wheat genotypes have been evaluated against two released bread wheat varieties. The experiment was laid out using alpha lattice design with three replications. Nine stability models were employed in order to assess stability and performance of 28 advanced bread wheat genotypes across 18 diverse environments. Combined analysis of variance for grain yield has revealed that the environments, the genotypes and GEI effects were significantly different (p&lt;0.001). Environments, GEI and Genotypic effects accounted for 71.99%, 22.97% and 5.03% of the total grain yield variation, respectively. Significant GEI showed variable performance of genotypes across environments. Eight advanced bread wheat genotypes namely ETBW8595, ETBW8668, ETBW8751, ETBW8991, ETBW8996, ETBW9547, ETBW9553 and ETBW9554 produced grain yield of more than 5.0 t ha-1, indicating their superior yielding potential. ETBW8595, ETBW8668, ETBW8751, ETBW8991 and ETBW9554 were found the most stable bread wheat genotypes as confirmed by five to eight stability models. ETBW8751, ETBW8991 and ETBW9554 were highest yielding, stable, adaptable, resistant and moderately resistant to prevailing stem and yellow rust diseases. Thus, these three genotypes were the most promising advanced bread wheat genotypes to be verified and released in Ethiopia. These promising bread wheat genotypes can be included in multipurpose bread wheat crossing blocks in order to correct shortcomings of commercial varieties.

Zajednički i direktni efekti genotipa i uslova životne sredine na varijabilnost prinosa i komponenti prinosa linija kukuruza

This study aimed to evaluate the influence of environmental conditions and genotype on the yield of three maize lines and the morphological properties of ears and seeds. Three hybrid maize lines were used as material in the study conducted in two consecutive years (2018 and 2019) at one location (Zemun Polje, Belgrade, Serbia). The following parameters were monitored: seed weight (SW), seed volume (V), bulk density (BD), ear length (EL), ear thickness (ET), fraction content and seed yield (MSY). Calibration divided the seed into a small seed fraction of 6.5-8.4 mm (SF) and a large seed fraction of 8.5-11 mm (LF). Seeds smaller than 6.5 mm and larger than 11 mm are presented as seed waste fraction (FW). The average seed yield for all three lines in the first and the second year was 6.13 and 4.66 t ha-1 , respectively. A significant impact of the environment was noticed on seed weights in both years (2018 and 2019), i.e. 327.56 and 251.77 g, respectively. The total variation in yield determined by the morphological characteristics of the seed was R2 =0.514