Variation In Fertility Research Articles

Cultivation of Cassava (Manihot Esculentus C.) With Selected Legumes for Growth, Yield and Economic Advantages as Climate Change Mitigations

Cassava (Manihot esculentus Crantz.) is a monoecious perennial shrub that is extensively cultivated as an annual crop in tropical and subtr++=opical regions for its edible, starchy, tuberous roots. It is ideal for intercropping with short-duration crops, which are often harvested before the cassava canopy closes. Thus, intercropping cassava, especially with legumes, is an important way for poor farmers to provide additional crop yield during the early growth stage. Moreover, the incorporation of legumes into cassava-based cropping systems may offer one of the most feasible ways of enhancing protein intake and nutritional security of farming households. Accordingly, a 1-year field study on cassava intercropped with three legumes (haricot bean, mung bean, and soybean) in southern Ethiopia was conducted to determine the effect of intercropping on the growth, yield, and economic advantage of the cassava. The experiment was laid out in a randomized complete block design (RCBD) with three replications. The results revealed that there were significant (P<0.05) differences for cassava plant height, leaf number, stem width, number of storage roots per plant, storage root weight, dry matter, and root yield due to cassava legume intercropping. Cassava- haricot bean intercropping increased root yield by 28% as compared to cassava-mung bean (21%), and cassava-soybean (18 %), respectively. And it can improve land-use efficiency by 31% as compared to cassava-soybean and cassava-mung bean intercropping. The partial budget analysis also revealed that cassava planted with haricot bean gave the highest economic benefit of 199,250 Birr ha-1. Further researches on relative planting time of legumes with cassava and soil fertility variation under sole cassava and intercropping systems are important for improving productivity of growers under the study area.

Assessing Spatial Variation and Driving Factors of Available Phosphorus in a Hilly Area (Gaozhou, South China) Using Modeling Approaches and Digital Soil Mapping

Soil fertility plays a crucial role in crop growth, so it is important to study the spatial distribution and variation of soil fertility for agricultural management and decision-making. However, traditional methods for assessing soil fertility are time-consuming and economically burdensome. Moreover, it is hard to capture the spatial variation of soil properties across continuous geographic space using the conventional methods. As key techniques of digital soil mapping (DSM), spatial interpolation techniques have been widely applied in soil surveys and analysis in recent years, since they can predict soil properties at unknown points in continuous space based on limited sample points. However, further research is needed on spatial interpolation models for DSM in regions with variable climates and complex terrains, which are characterized by strong spatial variation in both environmental variables and soil fertility. In this study, taking a typical hilly area in a subtropical monsoon climate, i.e., Gaozhou, Guangdong Province, China, as an example, the performances of four popular spatial interpolation models (Random Forest (RF), Ordinary Kriging, Inverse Distance Weighting, and Radial Basis Function) for digital soil mapping on available phosphorus (AP) are compared. Based on RF, the spatial variation and its driving factors of the AP of Gaozhou are then analyzed. Furthermore, by selecting three typical truncation lines from different directions, the correlations between environmental variables and AP in different spatial positions are demonstrated. The root mean square error (RMSE) results of the above four models are 32.01, 32.08, 32.74, and 33.08, respectively, which indicate that the RF has a higher interpolation accuracy. Based on the mapping results of RF, the minimum, maximum, and mean values of AP in the study area are 38.90, 95.24, and 64.96 mg/kg, respectively. The high-value areas of AP are mainly distributed in forested and orchard areas, while the low-value areas are primarily found in urban and cultivated areas in the eastern and western regions. Vegetation and topography are identified as the key factors shaping the spatial variations of AP in the study area. Furthermore, the spatial heterogeneity of the influence strength of altitude and EVI is revealed, providing a new direction for further research on DSM in the future, i.e., spatial interpolation models considering the spatial heterogeneity of the influence of environmental variables.

Crop tillage, soil depth, and their influence on extracellular enzyme activities

Agricultural practices can alter both physicochemical properties and soil microbial parameters, modifying the dynamics of soil biochemical functioning and, consequently, nutrient cycling. This study evaluated the effect of land use on chemical and biochemical attributes, and relationships between environmental variables. We used a sampling design to collect soil samples at different depths in different agroecosystems. Soil samples from natural ecosystems (native Cerrado) and agroecosystems (cotton and sugarcane cultivation) were collected at 0–0.1 m, 0.1–0.2 m, 0.2–0.5 m, and 0.5–1.0 m from 12 areas in the State of Goiás, Brazil. Twelve chemical properties and two biochemical attributes (enzyme activity and microbial biomass carbon) were evaluated using a generalized linear model of variance and Tukey’s test with three factors: correlation between all soil attributes, multiple regression between soil attributes, and biochemical variables. Soil chemical and biochemical attributes were significantly affected by variable depth (p<0.05). Most of the metabolic activity in the soil occurred at 0 to 0.2 m, independent of land use class. Seasonality also affected enzyme activity in the soil, with higher activity during the rainy season. In contrast, microbial biomass carbon, an attribute generally related to organic matter and carbon mineralization, did not vary significantly with different soil depths and seasons. Thus, enzyme activity is an important indicator of soil fertility variations and is more sensitive than chemical and microbial parameters

Impact of soil fertility characteristics on artificial fertility gradient approach developed using sorghum (Sorghum bicolor) in Alfisols

In the advent of precision agriculture, applying fertilizer based on soil testing is a crucial tool to prescribe nutrient levels for crops, to increase nutrient use efficiency and production. A field experiment was conducted in a farmer's field in the Dindigul district, Southern agro-climatic zone of Tamil Nadu to ascertain the effect of artificial soil fertility gradient method on soil fertility, green fodder production of sorghum (Sorghum bicolor (L.) Moench) (var. CO 30) and nutrient absorption. A fertility gradient technique has been investigated to produce fertilizer recommendations for location-specific in red soils (Alfisols, Typic Rhodustalf). The experimental field was separated into three equal strips: strip I, II, and III, which received applications of the three graded levels of ertilizer N0P0K0, N1P1K1, and N2P2K2, respectively. Urea, single super phosphate, and muriate of potash fertilizers, respectively, were used to apply NPK. As a gradient crop, S. bicolor was raised. The N1 level was set based on the general fertilizer recommendation of feed sorghum, while the P1 and K1 values were set based on the soil’s ability to fix 100 kg ha-1 of phosphorus and 100 kg ha-1 of potassium, respectively. Plant samples were taken at harvest time, and their NPK content and nutrient uptake were determined. With addition of graded doses of nitrogen, phosphorus and potassium fertilizer in Strip I, II & III increased the soil's available N, P & K status substantially in the order of Strip I<II<III and minimize the heterogeneity in the soil population , management strategies employed, and prevailing climate conditions to induce fertility variations in the same field. The outcomes showed that sorghum crop yields for fodder (Strip III – 25.01 t ha-1) and NPK uptake were significantly impacted by the application of graded amounts of NPK fertilizers.

Impact of Crown Closure on Cone Production and Effective Number of Parents in Natural Stands of Taurus Cedar (Cedrus libani A. Rich.)

This study was carried out to estimate the effect of crown closure classes (degraded forest, low crown coverage, medium crown coverage, and full crown coverage) and growth characteristics (three heights, diameter at base, diameter at breast height, and crown diameter) on cone production and to estimate fertility variation and its allied parameters in 130-year-old natural populations of Taurus cedar, also called cedar of Lebanon (Cedrus libani A. Rich.). The effect of biotic (e.g., growth characteristics, crown closure) and abiotic (e.g., light penetration, temperature, humidity, and soil characteristics) factors on cone production, fertility variation, and gene diversity was evaluated in two consecutive years of Taurus cedar. The factors, viz., altitude, temperature, aspect, and rainfall, varied, while some of them could be managed by cultural operations such as management of the crown and stand density. The impact of crown closure on cone production, fertility variation, and related parameters were observed in Taurus cedar’s natural populations sampled from southern Turkey. Maximum cone productions of 29 and 40/tree were recorded with full crown closure in two consecutive years, due to significant differences among individuals within crown closure class. For instance, cone productions were between 10 and 67 in the full crown closure of the first year. The sibling coefficient, which is a measure of the fertility variation in a stand, was the highest (1.16) for the full crown closure in the first (meaning 86% fertile trees) and the second years (1.55, 65%), while it was the lowest for the medium crown closure (1.09, 92%) in both years. Gene diversity decreased from a degraded patch (0.987) to that with full crown closure (0.984). Results of variance analysis showed a significant (p ≤ 0.05) difference between crown closure classes for cone production within the second year and between years. Significant positive (p ≤ 0.05) correlations were noted between years for cone production (r = 0.22) and between cone production and crown closure in the first and second years (r = 0.29). However, growth characteristics had no effect on cone productions in individual crown closure classes, while there were significant (p ≤ 0.05) correlations between the diameter at breast height and cone production for both years (r = 0.15 and 0.17) in pooled populations.

Comprehensive assessment and information database on saline and waterlogged soils in Kazakhstan: Insights from Remote Sensing Technology

Soil salinity and waterlogging are significant challenges in agricultural regions worldwide, including Kazakhstan. Understanding the characteristics and distribution of saline and waterlogged soils is crucial for developing effective strategies to mitigate their negative impact on crop productivity and environmental sustainability. This study aims to provide a comprehensive assessment of saline and waterlogged soils in various zones of the Republic of Kazakhstan, including the desert, foothill semi-desert (vertical), semi-desert (latitudinal), and dry-steppe areas. By examining the genetic horizons, chemical composition, ionic composition, salt content, and granulometric composition of these soils, this research contributes to the knowledge base necessary for implementing targeted soil management practices and restoration techniques. Fieldwork was conducted at 66 designated base points, where detailed descriptions of the genetic horizons of these soils were made. The data collected from these surveys were utilized to create an extensive information database, encompassing various indicators such as nomenclature, profile structure morphology, chemical composition, ionic composition of water extracts, salt content, absorbed cations, and granulometric composition. The findings reveal that saline soils cover a significant area of 16.7% (35,817.4 thousand hectares) of the agricultural land, while waterlogged soils occupy 0.5% (1,083.4 thousand hectares). The study highlights the poor fertility of saline soils due to high concentrations of water-soluble salts, predominantly sodium chlorides and sulfates, throughout the soil profile. Conversely, waterlogged soils exhibit distinct features such as gleyed horizons and a greenish-grayish color, with variations in fertility. The information presented in this study contributes to the understanding of the characteristics and distribution of saline and waterlogged soils in Kazakhstan, facilitating the development of strategies to restore soil fertility and implement appropriate management practices.

Perspective: Can early embryonic losses be reduced in lactating dairy cows?

Perspective: Can early embryonic losses be reduced in lactating dairy cows?

An automated system of soil sensor-based site-specific seeding for silage maize: A proof of concept

Despite recent studies of map-based site-specific seeding (SSS) revealing improved agronomic and economic outcomes over uniform rate seeding (URS), to our best knowledge no visible and near infrared spectroscopy (vis-NIRS) sensor-based SSS studies exist to date. This study aimed to develop and evaluate an automated sensor-based SSS technology for silage maize (Zea mays L.) production. An on-line visible and near-infrared reflectance spectroscopy (vis-NIRS) sensor was installed in front of a tractor to provide real-time input data to control the seed rate using a precision seeding machine mounted at the back of the tractor. A LabVIEW-based software was developed and used to predict soil fertility index using on-line vis-NIR spectra, which was then used to calculate the seed rate and transfer it to the controller of the seeding machine. The agronomic and economic benefits of SSS were compared with URS under a one-site-year experiment. Results showed that the proposed sensor-based SSS technology was 87.5% efficient in controlling the desired seed rates, according to the soil fertility status. In parallel with the observed spatial similarity between predicted soil fertility index and actual seed rates, a strong linear association (R2 = 0.80) was also achieved. As a result, SSS improved silage yield by 1.4 t ha−1 (4.4%), while sowing a lower seed rate (86.4 kSeeds ha−1) than the URS (90 kSeeds ha−1). This improved gross margin by 91 € ha−1, of which only 7 € ha−1 was attributed to savings on seed cost. The proposed sensor-based SSS technology was technically sound and thus transforms within-field fertility variations into agro-economic benefits effectively.

Natural genetic variation in a dopamine receptor is associated with variation in female fertility in Drosophila melanogaster.

Fertility is a major component of fitness but its genetic architecture remains poorly understood. Using a full diallel cross of 50 Drosophila Genetic Reference Panel inbred lines with whole genome sequences, we found substantial genetic variation in fertility largely attributable to females. We mapped genes associated with variation in female fertility by genome-wide association analysis of common variants in the fly genome. Validation of candidate genes by RNAi knockdown confirmed the role of the dopamine 2-like receptor (Dop2R) in promoting egg laying. We replicated the Dop2R effect in an independently collected productivity dataset and showed that the effect of the Dop2R variant was mediated in part by regulatory gene expression variation. This study demonstrates the strong potential of genome-wide association analysis in this diverse panel of inbred strains and subsequent functional analyses for understanding the genetic architecture of fitness traits.

Soil fertility thresholds driven by sand content indicate drylands degradation phases on the Tibetan Plateau

AbstractUnderstanding the process of dryland degradation is crucial to combating desertification and maintaining land sustainability. To identify important indicators of dryland degradation, we conducted a field survey of 46 drylands spanning an aridity gradient across the Tibetan Plateau. Our random forest model suggested that soil sand content was the most important predictor of variation in soil fertility (carbon, nitrogen, and phosphorus). Most soil fertility showed a nonlinear and abrupt decline with increasing soil sand content, and displayed three sequential thresholds. First, soil organic carbon sharply decreased beyond a soil sand content threshold of 47%. Second, exceeding a subsequent threshold of 70%, the total nitrogen and light fraction carbon declined dramatically with increasing soil sand content. Finally, soil heavy fraction carbon, inorganic carbon, and total carbon were drastically reduced when the soil sand content exceeded 80%. The three soil fertility thresholds along the gradient of the soil sand content indicated a sequence of dryland degradation phases. Our findings provide an approach for detecting the severity of dryland degradation and suggest vulnerable areas of degradation on the Tibetan Plateau.

Assessing spatial variability of soil and drawing location-specific management zones for coastal saline soils in Ramanathapuram District, Tamil Nadu

The production of crops in saline and alkali-degraded areas is difficult due to the heterogeneous and spatial variation of soil fertility. First, their spatial variability was analyzed and maps of the spatial distribution were created using Geostatistical techniques. The fuzzy k-mean clustering analysis was then used to define Management zones in the coastal saline soils of Ramanathapuram district in Tamil Nadu. One hundred and fifty geo-referenced soil samples (30 cm depth) were taken and analyzed for pH, electrical conductivity (ECe) in the saturated paste extract (USSL method), organic carbon (OC) (Walkley-Black chromic acid wet oxidation method), calcium carbonate (CaCO3) (Rapid titration method) and available phosphorus and extractable micronutrients (Multinutrients extraction method), revealing significant variation in soil characteristics throughout the coastal saline soils of Ramanathapuram district. The most significant factors, which together accounted for four principal components and 69% of the overall variability, were pH, electrical conductivity (ECe), calcium Carbonate and available zinc. According to Geostatistical analysis, the Exponential (pH, OC (organic carbon), P, Fe, Mn and Zn) and Stable (ECe) was the best fit semivariogram ordinary kriging model with weak to moderate spatial dependence. Fuzzy k-mean clustering was also used to identify zone 1, zone 2 and zone 3. For every soil property, there was a significant difference between MZ1(zone 1), MZ2(zone 2) and MZ3(zone 3). These results also showed that cluster analysis gave farmers a chance to use location-specific nutrient management strategies by minimizing variability within the zone. The management zones can decrease agricultural inputs and environmental pollutants while increasing crop productivity.

Reproductive Performance of Tunisian Arabian Stallions: A Study on the Variance and Estimation of Heritability.

A consistently high level of stallion fertility plays an economically important role in modern horse breeding. To better understand the factors affecting variation in stallion fertility, we have performed a statistical analysis study on some breeding factors: year of breeding, stud farm, age of the stallion, number of covered mares per stallion, reproduction methods, and age of the mare. This work was conducted on 94 purebred Arabian stallions in four different regions of Tunisia. The results showed an increase in the number of stallions during the study period, ranging from 11.33% in 2011 to 13.29% in 2018. Sidi Thabet's stud farm contained the highest number of purebred Arabian stallions. The majority of stallions were between 15 and 21 years old and had covered 1 to 20 mares; 95.19% of stallions were used in natural mating (Nat); 50.36% had low fertility, 17.69% had medium fertility, and 32.3% had excellent fertility according to fertility standards. Depending on the year and stud, there was a variation in fertility per cycle (FERPCE) and end-of-season fertility (FERPSE) of the stallions. The highest average FERPCE and FERPSE values were obtained using artificial insemination with fresh semen (AIF). Analysis of FERPCE and FERPSE showed that the model used in our study explained 40.21% of total variability observations for FERPCE and 42.1% for FERPSE. The used statistical model showed that the breeding year, the stud, the age of the stallion, the number of covered mares by stallions and the method of reproduction significantly affected both FERPCE and FERPSE (with p = 0.001). Low to moderate heritability estimations for FERPCE (hs2 = 0.08) and FERPSE (hes2 = 0.36) were obtained.

Biological Factors and Multiple Regression Analysis for Human Fertility among Four Different Endogamous Populations of Coastal Andhra Pradesh

Multiple regression analysis was done to examine the impact of the biological factors on fertility. This paper focuses on the biological factors on human fertility. Here fertility is used as the number of children ever born for a woman. This variable is easily measurable. The entire set of variables related to fertility are classified into the important biological factors influencing the fertility are age at marriage, age at menarche, age at first conception and age at last conception. To examine the impact of the factors on fertility by multiple regression analysis and the effect of each group on fertility is discussed separately and collectively. The resultant zero order correlation coefficients indicate that there is no serious problem of multicollinearity in estimated regression model. In all the four population groups, the R2 values are statistically significant which indicates that all the explanatory variables considered in the model together explain 63% of the variation in fertility among Kapu population, 55% among Settibalijas, 50% among Paki’s and 67% among Yerukala population.

Appraising co-composting efficiency of biodegradable plastic bags and food wastes: Assessment microplastics morphology, greenhouse gas emissions, and changes in microbial community

Biodegradable plastic bags (BPBs) to collect food waste and microplastics (MPs) produced from their biodegradation have received considerable scientific attention recently. Therefore, the current study was carried out to assess the co-composting efficiency of biodegradable plastic bags (polylactic acid (PLA) + polybutylene terephthalate (PBAT) + ST20 and PLA + PBAT+MD25) and food waste. The variations in greenhouse gas (GHG) emissions, microbial community and compost fertility were likewise assessed. Compared with the control, PLA + PBAT+ST20 and PLA + PBAT+MD25 both accelerated organic matter degradation and increased temperature. Moreover, PLA + PBAT+ST20 aggravated CH4 and CO2 emissions by 12.10 % and 11.01 %, respectively. PLA + PBAT+MD25 decreased CH4 and CO2 emissions by 5.50 % and 9.12 %, respectively. Meanwhile, compared with PLA + PBAT+ST20, the combined effect of plasticizer and inorganic additive in PLA + PBAT+MD25, reduced the NO3−-N contents, seed germination index (GI) and compost maturity. Furthermore, adding BPBs changed the richness and diversity of the bacterial community (Firmicutes, Proteobacteria and Bacteroidetes). Likewise, redundancy analysis (RDA) showed that the co-compost system of BPBs and food waste accelerated significantly bacterial community succession from Firmicutes and Bacteroidetes at the initial stage to Proteobacteria and Actinobacteria at the mature stage, increased co-compost temperature to over 64 °C and extended thermophilic composting phase, and promoted the degradation of MPs. Additionally, according to structural equation model quantification results, the inorganic additive of PLA + PBAT+MD25 had more serious toxicity to microorganisms and had significantly adverse effects on GI through CO2-C (λ = −0.415, p < 0.05) and NO3−-N (λ = −0.558, p < 0.001), thus reduced compost fertility and quality. The results also indicated that the BPBs with ST20 as an additive could be more suitable for industrial composting than the BPBs with MD25 as an additive. This study provided a vital basis for understanding the potential environmental and human health risks of the MPs' generated by the degradation of BPBs in compost.

Site-Specific Seed Yield Prediction of Red Fescue (Festuca rubra L.) Based on Drone Imaging and Local Regression Models

Yield maps give farmers information about growth conditions and can be a tool for site-specific crop management. Combine harvesters may provide farmers with detailed yield maps if there is a constant flow of a certain amount of biomass through the yield sensor. This is unachievable for grass seeds because the weight of the intake is generally too small to record the variation. Therefore, there is a need to find another way to make grass seed yield maps. We studied seed yield variation in two red fescue (Festuca rubra) fields with variation in management and soil fertility, respectively. We estimated five vegetation indices (VI) based on RGB images taken from a drone to describe yield variation, and trained prediction models based on relatively few harvested plots. Only results from the VI showing the strongest correlation between the index and the yield are presented (Normalized Excess Green Index (ExG) and Normalized Green/Red Difference Index (NGRDI)). The study indicates that it is possible to predict the yield variation in a grass field based on relatively few harvested plots, provided the plots represent contrasting yield levels. The prediction errors in yield (RMSE) ranged from 171 kg ha−1 to 231 kg ha−1, with no clear influence of the size of the training data set. Using random selection of plots instead of selecting plots representing contrasting yield levels resulted in slightly better predictions when evaluated on an average of ten random selections. However, using random selection of plots came with a risk of poor predictions due to the occasional lack of correlation between yield and VI. The exact timing of unmanned aerial vehicles (UAVs) image capture showed to be unimportant in the weeks before harvest.

The tempo-spatial changes of soil fertility in farmland of China from the 1980s to the 2010s

The grain yield level is closely related to soil fertility. To clarify the status and variations of soil fertility in Chinese farmland, soil sample profile data from the Soil Species of China in the 1980s and the Soil Series of China in the 2010s were collected. And surface soil data of fertility indexes (pH, soil organic matter, total nitrogen, total phosphorus, and total potassium) were calculated. The tempo-spatial variations characteristics of both soil fertility indexes and soil comprehensive fertility of Chinese farmland were analyzed with descriptive statistics, comparative analysis of paired sample points, and Integrated Fertility Index method. The results showed that: 1) The farmland soils in southern China were acidic and those in northern were alkaline. From the 1980s to the 2010s, the pH mean decreased by 0.34, and the acidification of soils in the southern region was more significant; 2) SOM and TN contents showed similar spatial patterns, with higher contents in southern and northeastern regions. Compared with the 1980s, the SOM mean and TN mean in the 2010s increased by 2.72 g/kg and 0.06 g/kg, respectively, with a decreasing trend in some areas; 3) The spatial distribution of TP and TK contents showed significant variability, with change range of the mean values was 0.15 g/kg and −1.51 g/kg during the three decades, respectively; 4) In general, the soil fertility in Chinese farmland was poor, with the most sample points at Grade IV (Mid-low) in the 2010s (22.38 %). During the three decades, the IFI mean increased by 0.01. The number of sample points with increasing IFI in eastern China was more than that in western China. And the soil fertility in eastern China showed a trend of ameliorating. This study would have great scientific significance for guiding agricultural fertilizer application and improving fertility in farmland soils.

The effects of fertility and synchronization variation on seed production in two Chinese fir clonal seed orchards

Variations in fertility and synchronization information is fundamental to seed orchard management. Our objective was to determine clonal variation and stability in strobili production, phenology, synchronization, and seed production in two generation clonal seed orchards (CSO) of Chinese fir. The number of female and male strobili and the phenology of 42 clones in both the 2.0- and 2.5-generation clonal seed orchards were investigated and recorded to calculate the variation and stability of fertility and synchronization. In both seed orchards, an obvious variation in gamete contribution was found among clones, indicating deviation from random mating. Female receptivity was in the pollen shedding stage, which is favorable to pollination. However, low synchronization (mean POij = 0.283) between clones indicated low overlap between female receptivity and pollen shedding. A higher POij value within clones than within outcrossing combinations indicated a high risk of selfing in two seed orchards, particularly for early- and late-flowering clones. The number of female strobili and POij (as female) significantly influence seed production. Overall, fertility and synchronization variation had notable consequences for seed production. Scientific genetic management is indispensable for promoting fertility uniformity and synchronization to obtain maximal genetic gain.

Analysis of Land Use Change and Associated Implications on Soil Ecosystem Functions in South Eastern Nigeria

Land use change affects soil functions and its capacity to provide ecosystem services. Though much of the tropics are experiencing accelerated increases in land use change, associated impacts of such changes are poorly understood and studied. This study assessed the extent to which land use changes affect the soil ecosystem functions in a rainforest zone of south eastern Nigeria. Soil samples were collected from 24 sample locations in selected natural forest, cashew and palm plantations. Samples were analyzed in triplicate in the laboratory for geochemical analysis, after which the result was subjected to statistical analysis—ANOVA, correlation and regression. Forest carbon had higher % mean carbon content; though there was no significant difference (F (2, 21) = .246, p = .784) in carbon level across land uses. R value of .301 showed low correlation between % carbon, organic matter and % loss in ignition. Furthermore, R2 value of 9.1% total variation in the dependent variable could only be explained by the independent variables. CEC, Nitrogen, Potassium and Phosphorus content of the land uses did not differ significantly: CEC (F (2, 21) = .844, p (.44); Nitrogen (.243), p (.79), Potassium (.140), p (.87), Phosphorus (.783), p (.47). This showed that there was no significant variation in soil fertility of the land uses, although natural forest had higher concentrations for these variables. Across the land uses, soil texture equally had no significant variations: % sand (F (2, 21) = .320, p (.729) % clay (.430), p (.656), % silt (.043), p (.958). Soil carbon was seen to be more enhanced in natural forest ecosystems than other land uses. Though plantations had reduced capacities to provide ecosystem functions, establishing such in modified landscapes is still advocated as they can coexist with such and yet ensure ecosystem functions.

Clonal fertility and heritability in strobilus production, and gene diversity of seed crops in a second-generation seed orchard of Pinus thunbergii

Abstract Variation of female and male strobilus production among clones over 4 consecutive years was estimated, and genetic variance, heritability, and genetic correlation in strobilus production were investigated in the second-generation seed orchard of Pinus thunbergii. This seed orchard was created with grafts selected according to the volume growth of their offspring. The production of female strobili continued to increase, whereas the production of male strobili fluctuated throughout the investigated period. The number of female strobili was highest in rich cone years, but the production of male strobili was not the same in rich or poor years. The maleness index showed a balance between female and male parents that occurred when male strobilus production was in rich or poor years. The parental balance curve for female strobilus production was closer to the expectation (i.e., more equal contribution) than that for male strobilus production in all years. The analysis of variance revealed significant differences among clones in female and male strobilus production over the four-year period. The narrow-sense heritability was higher in male strobilus production than female strobilus, implying that male strobilus production was under genetic control. The Pearson’s correlation was positive and mostly significant, indicating that female strobilus production was reflected in male strobilus production. The effective parent number was lowest in moderate and good years for cone production. The loss of gene diversity in seed crops was lower than expected based on clonal fertility variation.

Genome-Wide Association Screening Determines Peripheral Players in Male Fertility Maintenance

Deciphering the functional relationships of genes resulting from genome-wide screens for polymorphisms that are associated with phenotypic variations can be challenging. However, given the common association with certain phenotypes, a functional link should exist. We have tested this prediction in newly sequenced exomes of altogether 100 men representing different states of fertility. Fertile subjects presented with normal semen parameters and had naturally fathered offspring. In contrast, infertile probands were involuntarily childless and had reduced sperm quantity and quality. Genome-wide association study (GWAS) linked twelve non-synonymous single-nucleotide polymorphisms (SNPs) to fertility variation between both cohorts. The SNPs localized to nine genes for which previous evidence is in line with a role in male fertility maintenance: ANAPC1, CES1, FAM131C, HLA-DRB1, KMT2C, NOMO1, SAA1, SRGAP2, and SUSD2. Most of the SNPs residing in these genes imply amino acid exchanges that should only moderately affect protein functionality. In addition, proteins encoded by genes from present GWAS occupied peripheral positions in a protein-protein interaction network, the backbone of which consisted of genes listed in the Online Mendelian Inheritance in Man (OMIM) database for their implication in male infertility. Suggestive of an indirect impact on male fertility, the genes focused were indeed linked to each other, albeit mediated by other interactants. Thus, the chances of identifying a central player in male infertility by GWAS could be limited in general. Furthermore, the SNPs determined and the genes containing these might prove to have potential as biomarkers in the diagnosis of male fertility.