Journal of the Saudi Society of Agricultural Sciences最新文献

Adenostemma madurense is one of the Asteraceae with many medical properties but has not been widely cultivated. This study aims to determine the different fertilizer doses that can produce the best growth, phenolic, flavonoid, terpenoid, and the 11α-OH KA (a diterpenoid found in A. madurense productivity), resulting in the high antioxidant capacity of A. madurense. A one-factor randomized block design was employed in five fertilizer doses, control/without fertilizer, 100 % cow manure (20 tons/ha), 100 % NPK (in the form of urea, SP-36, and KCl:135, 100, 135 kg/ha, respectively), a combination of 50 % cow manure + 50 % NPK, and a combination of 100 % cow manure + 100 % NPK. Fertilizers increase plant growth. Applying the combination of 100 % cow manure + 100 % NPK was the best fertilizer composition, which produced the highest plant height, leaf, and branch number. This fertilizer combination produced total phenolic, flavonoid productivity of 739.50 μmol Gallic Acid Equivalent/plant, 97.37 μmol Quercetin Equivalent/plant, not significantly different from applying 100 % NPK and the combination of 50 % cow manure + 50 % NPK, and terpenoid productivity of 77.51 mmol Nerol Equivalent/plant. The 11α-OH KA productivity and antioxidant capacity of this fertilizer is 18.00 mM 11α-OH KA/plant and 601.76 μmol Ascorbic Acid Equivalent/g dry sample, not significantly different from applying 100 % NPK. Applying 100 % cow manure + 100 % NPK may enhance the medicinal plant A. madurense’s efficacy, especially for antioxidants.

Water stress in plants due to the effects of climate change resulted in reduced growth and yield of coffee in the tropics. Efficient use of water through the use of SMART irrigation systems available provides a promising solution to address such a problem. Thus, a study utilizing a combined climate- based and soil moisture SMART irrigation system has been conducted to assess its effects on the growth of Robusta coffee seedlings compared to practiced manual irrigation. The experimental design utilized a Complete Block Design (CBD) approach. Additionally, water consumption was measured to determine any significant differences. Over the course of the two-month experiment, 20 replications per treatment, it was observed that coffee seedlings subjected to the automated irrigation system (T1) exhibited significant improvements in both plant height and number of leaves, with growth rates of 72.56% and 65.29%, respectively, compared to manually irrigated plants (T0). Although the water savings achieved under the automated system were not statistically significant, there was an 18.95% reduction in water consumption. These findings highlight the potential benefits of automating irrigation systems using an IoT approach, specifically in terms of enhancing coffee seedling productivity. By utilizing real-time data from sensors, the SMART irrigation system effectively optimized water usage and resulted in improved growth and yield. This research underscores the importance of implementing such technological advancements to mitigate the adverse effects of climate change on coffee cultivation in tropical regions.

The cotton leafworm, Spodoptera littoralis, is a polyphagous pest that attacks various economic crops. Integrated Pest Management (IPM) uses different techniques to combat this pest unfortunately chemical control is the predominant. However, it does not target the pupal stage of the insect. Therefore, a safe and cost-effective technique must be developed to address this issue.

This technique integrates using plant-based agents; M. oleifera and R. angustifolia seed oils as pupaicids. Various concentrations (1%, 2%, and 4%) of both oils were employed by means of the dipping method of pre-pupae. The study delved into the biological, and biochemical aspects of pupal development to adult emergence. Analysis of the fatty acids along with the hydrocarbons and sterols was conducted through GLC analysis for oils composition.

Our research has shown that Moringa oleifera and Ruta angustifolia oils at a concentration of 4 % have a significant impact on pre-pupal mortality (42.57& 61.9 %) and pupation of survival pre-pupa (57.42&38.09 %) However, emerged adults were reduced to 83.33 % and 60 %, respectively. Chitinase recording significantly disturbance after 1 day for Ruta (6.21 µg/min/g) and Moringa oil (2.12 µg/min/g). Also, Phosphatase enzyme showed a significant disturbance after 4 and 7 days of treatments. GLC data of fatty acids showed that oleic acid (74.42 %) was the major fatty acid in M. oleifera oil, while linolenic, linoleic, and oleic acids represented 31.39 %, 22.70 %, and 21.95 %, respectively, in R. angustifolia oil. Sterols in M. oleifera oil were β-sitosterol and stigmasterol, while Ruta oil contained additional amounts of cholesterol and campesterol,

Briefly, the suggested technique was effective in disturbing pupal development and reducing emerged adults. Ruta was more effective than Moringa oil due to its contents of sterols and hydrocarbons that may affect ecdysis.

Corn cultivation is relevant to the province of Tayacaja, a region with the greatest biodiversity in the Huancavelica State, although to date there are no published studies. Phenotypic characterization pursues measuring the genetic diversity of a group of genotypes, using appropriate morphological descriptors. The main objective of this work was to study the agro-morphological characteristics and productive potential of 25 starchy corn varieties, evaluated in four contrasting environments of the province of Tayacaja, Perú, during the crop cycle 2019–2020. For this purpose, 25 plant and ear characteristics were chosen, using principal components (PC) and cluster analysis. The experiments were established in an alpha-lattice design, with three replications, in experimental units of two rows, with 0.20 m between plants and 0.80 m between furrows, 4 m long. The agro-morphological characterization grouped the 25 varieties within 6 well-defined clusters, giving an overview of the existing phenotypic variability among the evaluated starchy corn varieties. The varieties G₆, G₁₄, G₂₀, G_T3, and G₁₈ were the genotypes with the most outstanding characteristics, which facilitated their separation from the rest of the materials studied. The multivariate analysis brought together representative varieties of certain races, with typical plant and ear characteristics. The study revealed the existence of a good productive and agronomic potential for the development of genetic materials for cancha (toasted kernel grains), choclo (fresh corn), and mote corn production; as well as the presence of anthocyanin in the grain, information that, together with the agro-morphological characterization, could be very useful to enhance gains in the selection process in future genetic improvement work.

The Brown planthopper, Nilapavarta lugens (Stål) (BPH) is a major pest of rice after the adoption of the Green Revolution. Its outbreaks are frequently linked to climate variability and change, posing almost all rice varieties in Indonesia at risk, resulting in economic losses due to reduced production. The amount of information available about its current and future potential distribution as well as the influencing factors are still limited. The objective of this study is to examine the impact of climate variability on BPH and to assess the projection of the BPH potential distribution under different climate scenarios. Maximum entropy (MaxEnt) was applied to predict the current and future potential distribution of BPH over Indonesia. This study used data on BPH-affected areas, rainfall and temperature, and the Ocean Nino Index (ONI) on a monthly interval to examine the linkage between climate and BPH affected areas. The global-climate models from phase 6 of coupled model intercomparison project (CMIP6) for period 2041–2060 were used to examine the variations in 19 bioclimatic variables for two shared socioeconomic pathways (SSPs) compared to baseline period (1971–2000). The findings concluded that the dynamics of BPH damaged areas were strongly influenced by higher temperature and rainfall in dry season associated with La Niña events. Precipitation of driest month, precipitation seasonality, mean temperature of driest quarter and temperature seasonality were the most affected factors in the distribution of BPH. Our results highlight BPH distribution was expected to increase to 2.4% and 3.02% (moderately suitable), 1.88% and 1.95% (suitable), 2.59% and 2.76% (highly suitable) respectively under SSP2-4.5 and SSP5–8.5. These findings could serve as early warnings to adjust agricultural practices and implement tailored pest management methods to effectively address the shifting pattern of BPH in the future.

Agricultural development in many arid countries including Oman is limited due to water scarcity which is currently exacerbated with increasing demand due to rapid population growth, economic development, and mismanagement of water resources. Impact of climate change is expected to adversely impact the water resources. Therefore, finding new efficient, environmentally friendly, and affordable water-saving techniques in agronomy is a necessity for achieving agricultural sustainability. Irrigation water can be saved by creating capillary barriers (CB) to unsaturated moisture flow. In this study, a “nature-inspired capillary barrier design” called hereafter as Smart Capillary Barrier (SCB) (mosaic of fine textured blocks, made of silt loam, and sandy sheath surrounding the blocks) was tested in series of field experiments with soil columns and pots. We investigated the effect of the percentage of sand of the sheath on water storage capacity of the SCB blocks and growth of okra (Abelmoschus esculentus L.) under deficit irrigation. Three proportions of sand to silt loam (sand%:silt loam%) in the sheaths were used in this study, SCB-25 (25:75%), SCB-50 (50:50%) and SCB-75 (75:25%). Our results show that increasing the percentage of sand in the designed and constructed SCB composite reduces evaporative and drainage water losses and therefore increases the water storage capacity of the blocks. Our SCB-75 attains 1.7–1.3 smaller drying rate than that for SCB-25 and SCB-50, respectively. Therefore, this composite had higher water saving capacity than a homogeneous soil (no capillary barrier) and a soil with a standard sand mulch (coarse soil overlies fine soil). The study found that using SCB composite did not consistently have a clear effect on the growth of okra plants at all stages of their development. However, during the development stage, using SCB-75 resulted in significantly higher dry biomass of the plants compared to using a homogeneous soil (the control). Additionally, during the initial stage of fruit yield, using SCB-75 also resulted in significantly higher fruit yield compared to using a homogeneous soil. Application of our SCB composite is a promising approach for saving water in desertic farming.

Currently, nanotechnology is widely used in agriculture and horticulture. Nanofertilizers are essential for encouraging vegetative growth and flowering, as well as enhancing productivity and fruit quality. These nanoparticles are viewed as growth promoters as well. The current study was therefore carried out during the two successive seasons of 2021 and 2022 on 14-year-old trees grown in clay soil in a field experiment at the Pomology Department Research orchard, Faculty of Agriculture, Assiut University, Egypt. The effects of conventional vs. nano-micronutrients as foliar fertilizers on the fruit yield, quality, and mineral nutrition status of pomegranate trees were studied. The foliar application of all treatments on pomegranate trees remarkably increased yield and physical properties of fruits as well as improved the levels of total soluble solids percentage, anthocyanin pigment, flavonol, total phenols, antioxidant activity and nutrients status compared with the controls during the 2021 and 2022 seasons. The lowest fruit cracking percentages were obtained by the spraying of nano-micronutrients (4.33–5.70 %) compared with the other treatments and the control, which gave the highest percentages (10.45–11.43 %). The highest increments in yield, physical properties of fruits and levels of total soluble solids percentage, anthocyanin pigment, flavonol, total phenols, and antioxidant activity were noticed by the spraying of nano-micronutrients especially at 1000 and/or 1500 µg mL⁻¹. It could be concluded that the use of nanofoliar fertilization in pomegranate cultivation may improve the yield, quality, and nutritional status of pomegranate fruits.

Collecting and analyzing data on surface water across extensive areas is a challenging, time-consuming and expensive. Developing predictive models that offer high accuracy, reliability and require minimal parameters can potentially reduce the time and expense associated with water quality monitoring and management. While most existing studies have focused on estimating point prediction of water quality without approximating the predictive interval (PI) of the estimation, this study aimed to develop a prediction tool to estimate the PI of water quality indexes (WQIs) in the lower Mun river basin. This was achieved by employing principal component analysis (PCA), artificial neural networks (ANN), and bootstrap methods to enhance accuracy, robustness, and reliability with the minimum number of water quality parameters. PCA was initially used to select 4 parameters for the WQI. Subsequently, ANN regression was employed to develop a new WQI to enhance data evaluation efficiency. The testing results of the proposed model revealed its excellent performance compared to other models in terms of accuracy (root mean square error (RMSE) = 0.86, correlation coefficient (R) = 0.993, scatter index (SI) = 0.019, mean absolute error (MAE) = 0.709, and mean bias error (MBE) = −0.003). Additionally, the proposed model incorporated the bootstrap method to quantify uncertainty and create a PI, resulting in a high coverage rate exceeding 95%. By integrating statistical techniques with artificial intelligence and quantifying uncertainty, it is possible to effectively evaluate water quality, provide more accurate and reliable indexes. This study can be an effective tool for decision makers and planners seeking precise data on water quality to develop water resource management strategies.

Oil pollution is one of the most dangerous pollutant due to the huge quantities that are spillage from crude oil that contains toxic compounds. To treat contaminated soil with oil, bioremediation is an important methods which involve use microorganisms and plants to degraded pollutants and clean up the soils. A biological pot factorial experiment was carried out in a (CRD) design to study the ability of Rhizobia species, a mixture of Bacillus and Grasspea leguminous plant for removal diesel oil from contaminated soil. The results showed that the different species of bacteria led to a significant increase in the amount of diesel oil absorbed by roots and shoots of plant for all treatments compared to the control treatment. And the Vigna radiata (R4) species gave a highest value (13.70 mLpot⁻¹) absorbed by shoots compared to lowest value of control treatment (4.15 mLpot⁻¹), with a significant increase about (230.12%). The diesel oil amounts remaining in soil were decreased significantly with the addition of different isolates of Rhizobium bacteria or Bacillus compared to the control treatment. Moreover, there were significant differences in the amount of diesel oil degraded in soil treated with different isolates of microbial treatments planted compared to control treatment. The adding Rhizobia isolated from Vicia faba (R2) recorded the highest amount decomposed (504.33) mLpot⁻¹ compared to the control treatment (318.52) mLpot⁻¹ with a significant increase (58.33%). Therefore, we concluded that the Grasspea plant with Rhizobia species or Bacillus can be used for phytoremediation contaminated soil with diesel oil.