Journal of the Saudi Society of Agricultural Sciences最新文献

The use of assisted reproductive technologies to improve productivity in livestock industry is becoming popular. The study aimed to determine the utilisation of artificial insemination (AI) and to find out the factors associated with adoption of AI by beef farmers in selected areas of Southern and Ghanzi districts. The data were collected through a survey where a questionnaire was administered to beef farmers. Random sampling was used to interview 54 beef farmers in Southern district and 40 beef farmers in Ghanzi district. The data were analysed using Frequency procedure in Statistical Package for Social Sciences (SPSS). The association between the nominal variables was tested using Pearson Chi-square in SPSS. There is significant (P < 0.05) association between AI utilization by beef farmers and these socio-economic factors; district where farming is done, age of the farmer, education level, occupation of the farmer, purpose of rearing cattle (commercial or subsistence) and land (communal or ranches). Gender of the farmer is not associated with AI utilization.

Ganoderma boninense, the causative agent behind basal stem rot (BSR) disease in oil palm, instigated a pressing need for innovative and ecologically sustainable strategies to counter its impact. Biological control strategies, particularly employing bio-fungicides, have emerged as environmentally friendly alternatives for managing oil palm plant diseases. This study delved into harnessing the biocontrol potential of Indigenous bacterial isolate by investigating and evaluating its bioactive compounds of ethyl acetate extract with the capacity to suppress G. boninense growth in oil palm plants. Molecular identification was utilized to identify of bacterial isolate using 16S rRNA primers (5′- AGA GTT TGA TCC TGG CTC AG– 3′) and (5′- GGA TAC CTT GTT ACG ACT T– 3′). The agar well diffusion technique and scanning electron microscopy (SEM) were utilized to assess the inhibitory effects of bacterial ethyl acetate extract against G. boninense. A comprehensive analysis of the bacterial ethyl acetate extracts was conducted by gas chromatography - mass spectrometry (GC–MS). Molecular identification confirmed that the bacterial isolate was Bacterium strain BS1727. By employing SEM, the ethyl acetate extracts had influenced on G. boninense mycelial architecture. The exposure to the bacterial ethyl acetate extracts induced degradation and morphological distortion of the mycelial structure, serving as an indicator of its impact on the mycelium's structural modulation. Noteworthy, the spectrum of bioactive compounds was a subset of aromatic hydrocarbons, encompassing volatile organic compounds (VOCs). Based on GC–MS analysis, among the VOCs, acetic acid butyl ester and toluene showed the highest relative peak areas, 46.34 % for acetic acid butyl ester and 31.82 % for toluene, respectively. Ethylbenzene had a relative peak area of 5.4 %, 1,1,2-trichloroethane 4.41 %, and allyldimethyl (prop-1-ynyl) silane 3.17 %. The remaining compounds were 6-undecyl-5,6-dihydro-2H-pyran-2-one, 3-decen-5-one, 2-methyl-, and o-cymene, with the relative peak areas were below 1 %. These findings explained the inherent capacity of antifungal compounds as a viable strategy in inhibiting the growth of G. boninense.

An initial investigation on the physical traits of the cumin (Cuminum cyminum L.) schizocarps was examined in order to select the best genotypes of cumin grown in three regions of Morocco (Drâa-Tafilalet, Marrackech-Safi, and Oriental). This operation was conducted on 34 cumin accessions from six origins (local, India, Syria, Egypt, Turkey, and Saudi Arabia). To evaluate differences between the physical properties among accessions, length, width, thickness, and both the volumetric mass and the thousand-schizocarp mass were measured. Geometric properties (geometric mean diameter, sphericity index, specific mass and surface area) and gravitational parameters (bulk density, true density, and porosity) were calculated for each accession. Heritability (broad sense), phenotypic and genetic variabilities are also assessed. The average values of the evaluated parameters were found to be significantly different (p < 0.01) between accessions. The physical characteristics of schizocarps were significantly influenced by their origin, cultivated provinces and irrigation methods. Length, width, thickness and length of style range on average from 5.7 to 6.8 mm, 1.5 to 2.5 mm, 1.2 to 1.8 mm and 0.6 to 0.9 mm, respectively. Local and Egyptian accessions were the best-sized accessions. Regarding the weight, the Indian accession C11 registered the best volumetric mass 52.9 g, while the thousand-mass was found to be higher in the local accession from Zagora C19 with 7.3 g. The results showed that the phenotypic coefficient of variation (PCV) was higher than the genotypic coefficient of variation (GCV). The highest PCV and GCV were length of style (30.0%) and true density (24.4%), respectively. Volumetric mass had the highest value of heritability (99%). PCA analysis of seed origin showed clearly the ordination of cumin schizocarps into three groups. The big-sized schizocarps group is composed of local and Egyptian accessions, while the Saudi Arabia accession was individualized in a single group. Regarding the cultivated zone in Morocco, the ordination of schizocarps according to the province revealed four distinct groups. Finally, this study showed that irrigation mode may also affect the physical properties of cumin schizocarps.

Mining exploration programmes are being expensive and risky due to the limitations of conventional prospecting methods in identifying desired mineralisation. Worldwide, mining exploration programmes have a success rate of approximately 0.7%. Bio-geochemical methods, a sub-branch of geochemical prospecting, are used to identify potential mineralisation areas by studying the distribution of plants containing certain metals. Turkey's leading position in the world in terms of boron reserves increases the strategic importance of boron. On the other hand, metagenome analysis is an important tool in scientific research for detecting microorganisms. Our study aims to develop a cost-effective and efficient biological alternative method for detecting boron mines. Metagenome analysis output showed correlation with the presence of Calothrix sp. NIES-3974, Snodgrassella alvi, Xanthomonas citri, X. citri pv. Fuscans, Pseudomonas viciae, and Aphanothecaceae bacteria and detecting of the potential boron traces in soil. Modelling studies were also conducted on aquaporin z protein, related to the boron uptake, that can be used for utilising from boron detection.

Soil carbohydrates play a vital role in maintaining the health of soil and ensuring that ecosystems function properly. The method used in this study for measuring carbohydrate content in soil is quick, effective and easy. The investigation involved using three techniques to extract 45 soil samples of different soil texture; hot water, cool water and classical methods. The extracted samples were then analyzed for carbohydrates using two techniques; the widely accepted Phenol Sulfuric Acid method and the newly developed Sulfuric Acid UV method. The results revealed that the hot water extraction method consistently yielded higher levels of carbohydrates compared to the other methods. Interestingly the newly developed Sulfuric Acid UV method consistently produced similar results to those obtained from the well established Phenol Sulfuric Acid method. These results suggest that the novel Sulfuric Acid UV method, which relies on absorption in the ultraviolet region to analyze soil carbohydrate content is indeed a viable approach. This has allowed scientists and researchers to have an alternative means of determining soil carbohydrate levels.

In crop growing, biostimulants are currently used to improve the advance and yield of crops. These biostimulants showed successful effects in various crops against severe stress factors. Therefore, integrative studies are required to define the usage of such products in agriculture. This study investigated the valuable impacts of biostimulants on the growth parameters of green beans (Phaseolus vulgaris) in Morocco known for its harsh climatic conditions. Equally, we studied the effect on the soil characteristics. The growth parameters were the number, length, and weight of leaves and pods, and were measured after, 21, 29, 35, 42, and 49 days of cultivation. The soil parameters were organic matter, macro-elements, and microelements. The obtained results exposed that the number of leaves was enhanced by 52.95 % in plants treated with biostimulants, while the improvement of foliar weight was estimated at 83.45 %. The treatment improved the weight of pods by 50 % after 75 days and by 63.65 % after 90 days. Similarly, the treatment improved the length of pods by 48 % after 75 days and by 78 % after 90 days. The improvement of growth parameters was in a time-dependent manner. These results are the first to clarify the faculty of biostimulants to enhance the growth performance of green beans under North African climatic and soil circumstances. However, more experiments are desired to evaluate the optimum quantities of biostimulants needed to get the maximum yield. Equally, future research is required to assess the influence of biostimulants on the nutritive quality of fruits.

In the pursuit of advancing food quality assessment, this study employs sophisticated data-driven techniques to delve into the complex realm of honey analysis. With the aim of unraveling the multifaceted nature of honey quality, Self-Organizing Maps (SOMs) and Principal Component Analysis (PCA) were employed to scrutinize the interplay of physicochemical, biochemical, and melissopalynological attributes in honey samples collected from the diverse drylands of Algeria. The dataset comprised 62 honey samples and eight crucial parameters. These parameters span climate zones (arid vs. desertic), honeybee breeds (Tellian, Saharan, and hybrid), honey extraction methods (manual pressing vs. electric centrifugation), and beekeeping systems (modern vs. traditional). Using SOMs, honey samples were categorized into distinct clusters that reflect variations across these four honey-related variables. Additionally, SOM heatmaps offer granular insights into individual parameters' distribution across the SOM map. Our analysis revealed nuanced distinctions in honey quality across North African regions, with specific parameters playing a pivotal role in defining honey quality. On average, the honey samples exhibited the following characteristics: a water content of 15.14 %, an electrical conductivity of 0.5 µS/cm, a pH of 4.20, a total sugar content of 83 %, a reducing sugar content of 63.83 %, a proline concentration of 382.7 mg/kg of honey, an hydroxymethylfurfural level of 77.4 mg/kg, and an average pollen grain density of 4.56 × 10⁵ grains per 10 g of honey. Notably, the study identified clear demarcations in honey quality linked to beekeeping systems and revealed characteristics associated with bee breeds and extraction techniques. The results underscored the significance of selected honey parameters as key indicators of quality. This analytical approach not only offered a comprehensive assessment of honey quality but also holds potential for broader applications within the food industry. The findings invite further exploration into the ecological and genetic dimensions of beekeeping practices in North Africa to deepen our understanding of honey's multifaceted attributes. This study showcased the efficacy of SOMs and PCA in unraveling the complex fabric of honey quality assessment. These data-driven techniques, complemented by the structured dataset and analytical approach used, provided valuable insights that contributed to enhancing the scientific understanding of honey quality. By elucidating the complex relationships between physicochemical, biochemical, and melissopalynological parameters and honey quality, this research paves the way for future studies in this field and holds promise for broader applications in food quality assessment and monitoring.

Rigidoporus microporus is a soil-borne pathogen that causes significant losses in rubber plantations worldwide. As an alternative technique, the development of bacteria as biological control agents capable of producing hydrolytic enzymes and antibiotics has emerged. The in vitro activity of bacterial isolates against R. microporus was assessed using hydrolytic enzyme production and antibiotic inhibition. The research included enzyme activity analyses and antagonism assays against R. microporus, followed by selection of the top ten isolates using the Analytical Hierarchy Process. The 16S rRNA gene sequencing was used to determine compatibility and identification. Twenty-two bacterial isolates produced one or more enzymes, including chitinase, glucanase, and cellulase. These isolates inhibited the growth of R. microporus through diffusible, volatile, and colonized soil, resulting to abnormal mycelial formation. Hierarchical analysis has selected 10 isolates with the highest potency and compatibility. Four isolates (S085, S108, SK909, and SK018) belonged to Serratia surfactantfaciens, while others were identified as Brucella intermedia (basonym: Ochrobactrum intermedium) (S018, T2, and BE60), Bacillus albus (NJ57), Bacillus amyloliquefaciens (P7), and Burkholderia cepacia (SS19.7). The present study demonstrated the ability of bacterial isolates to secrete hydrolytic enzymes and antibiotic metabolites causing permanent abnormalities in R. microporus mycelia, representing the first report of such metabolite activity of rhizosphere and endophytic bacteria as biological control agents against R. microporus. However, further study is needed to assess their performance under field conditions.