Comparative Metabolic Profiling in Pulp and Peel of Green and Red Pitayas (Hylocereus polyrhizus and Hylocereus undatus) Reveals Potential Valorization in the Pharmaceutical and Food Industries

Pitaya (Hylocereus genus) is a popular plant with exotic and nutritious fruit, which has widespread uses as a source of nutrients and raw materials in the pharmaceutical industry. However, the potential of pitaya peel as a natural source of bioactive compounds has not yet fully been explored. Recent advances in metabolomics have paved the way for understanding and evaluating the presence of diverse sets of metabolites in different plant parts. This study is aimed at exploring the diversity of primary and secondary metabolites in two commercial varieties of pitaya, i.e., green pitaya (Hylocereus undatus) and red pitaya (Hylocereus polyrhizus). A total of 433 metabolites were identified using a widely targeted metabolomic approach and classified into nine known diverse classes of metabolites, including flavonoids, amino acids and its derivatives, alkaloids, tannins, phenolic acids, organic acids, nucleotides and derivatives, lipids, and lignans. Red pitaya peel and pulp showed relatively high accumulation of metabolites viz. alkaloids, amino acids and its derivatives, and lipids. Differential metabolite landscape of pitaya fruit indicated the presence of key bioactive compounds, i.e., L-tyrosine, L-valine, DL-norvaline, tryptophan, γ-linolenic acid, and isorhamnetin 3-O-neohesperidoside. The findings in this study provide new insight into the broad spectrum of bioactive compounds of red and green pitaya, emphasizing the valorization of the biowaste pitaya peel as raw material for the pharmaceutical and food industries

Assessment of Genetic Diversity and Discovery of Molecular Markers in Durian (Durio zibethinus L.) in China

Durian (Durio zibethinus L.) is a crop of economic and health importance globally. Efforts are being made to revamp China’s only successful commercial-scale durian plantations in Hainan; however, their genetic base is unknown. Therefore, the present study was undertaken to assess the genetic base and population structure of 32 genotypes in durian plantation sites in Hainan, China, and develop simple sequence repeat (SSR) markers by whole genome sequencing through restriction site-associated DNA sequencing technology to facilitate germplasm conservation and breeding. The results from identity by state (IBS), phylogenetic tree, population structure, and principal component analysis grouped the 32 genotypes into two clusters/sub-populations. Based on IBS, genotypes in Cluster I are largely duplicated genotypes; however, results from the model-based population structure demonstrated that most of the genotypes in Sub-population II shared a common genetic background with those in Sub-population I/Cluster I. The results revealed that the core durian collection in the plantation sites in Hainan include D24, D101, MSW, JH, D163, HFH, and NLX-5. In addition, we developed a total of 79,178 SSR markers with varied lengths and amplicon sizes. The genetic diversity and population structure reported in this study will be useful for durian conservation and utilization. In addition, the discovered and developed SSR markers will lay the foundation for molecular breeding via marker-assisted selection, quantitative trait loci mapping, and candidate gene discovery and validation

Multi-Indicator and Geospatial Based Approaches for Assessing Variation of Land Quality in Arid Agroecosystems

Novel spatial models for appraising arable land resources using data processing techniques can increase insight into agroecosystem services. Hence, the principal component analysis (PCA), hierarchal cluster analysis (HCA), analytical hierarchy process (AHP), fuzzy logic, and geographic information system (GIS) were integrated to zone and map agricultural land quality in an arid desert area (Matrouh Governorate, Egypt). Satellite imageries, field surveys, and soil analyses were employed to define eighteen indicators for terrain, soil, and vegetation qualities, which were then reduced through PCA to a minimum data set (MDS). The original and MDS were weighted by AHP through experts’ opinions. Within GIS, the raster layers were generated, standardized using fuzzy membership functions (linear and non-linear), and assembled using arithmetic mean and weighted sum algorithms to produce eight land quality index maps. The soil properties (pH, salinity, organic matter, and sand), slope, surface roughness, and vegetation could adequately express the land quality. Accordingly, the HCA could classify the area into eight spatial zones with significant heterogeneity. Selecting salt-tolerant crops, applying leaching fraction, adopting sulfur and organic applications, performing land leveling, and using micro-irrigation are the most recommended practices. Highly significant (p < 0.01) positive correlations occurred among all the developed indices. Nevertheless, the coefficient of variation (CV) and sensitivity index (SI) confirmed the better performance of the index developed from the non-linearly scored MDS and weighted sum model. It could achieve the highest discrimination in land qualities (CV > 35%) and was the most sensitive (SI = 3.88) to potential changes. The MDS within this index could sufficiently represent TDS (R2 = 0.88 and Kappa statistics = 0.62), reducing time, effort, and cost for estimating the land performance. The proposed approach would provide guidelines for sustainable land-use planning in the studied area and similar regions

Effect of Banana Stalk Organic Fertilizer on the Growth of Chinese Cabbage

In order to solve the problem of waste disposal after banana harvest, we use banana stalk to produce banana stalk organic fertilizer, through a plot experiment. We compare the influence of normal organic fertilizer (Wanlubao) and banana stalk organic fertilizer as base fertilizers on Chinese cabbage growth, and evaluate the economic benefits of banana stalk organic fertilizer. The results show that organic fertilizer has little effect on water content and nutrient content of Chinese cabbage, but has significant effect on plant height and leaf width. Using organic fertilizer can increase the production of Chinese cabbage by 22.50%-43.10%. With 6750 kg/ha normal organic fertilizer, Chinese cabbage gets the highest yield, which reaches 30135 kg/ha, followed by the treatment of 6750 kg/ha stalk organic fertilizer. At farmers’ conventional fertilization level (4500 kg/ha), stalk organic fertilizer can increase the yield by more than 3.50% in comparison with the normal organic fertilizer, and the economic benefit increases by 1800 yuan/ha. As a kind of banana waste cycling product, banana stalk organic fertilizer is of low cost and good effect, and can be used instead of normal organic fertilizer

Effect of Two Urea Forms and Organic Fertilizer Derived from Expired Milk Products on Dynamic of NH3 Emissions and Growth of Williams Banana

Sustainable agricultural development depends mainly on the recycling of organic wastes to reduce environmental pollution, as well as to reduce the use of mineral fertilizers. Expired milk products are rich in organic carbon and nitrogen, so they are good raw materials for making organic fertilizers. In this study, expired milk products were converted to organic fertilizer (EDPF) by gravity and thermal treatments. The extracted EDPF was used in the nutrition of Williams banana plants under field conditions for two growing seasons. The field experiment consisted of four treatments including: C = control without N fertilization, U = traditional urea, SRU = slow-release urea, and EDPF. EDPF significantly (p < 0.05) improved the growth and yield of Williams banana in comparison to U and SRU. EDPF significantly minimized the soil pH and increased the soil organic-C and cation exchange capacity compared to the other treatments. EDPF increased the total yield of bunches by 20% and 17% in the first and second years, respectively, above U and SRU. EDPF surpassed the traditional and slow-release urea in its ability to supply the banana plants with nitrogen. NH3-N loss from U, SRU, and EDPF reached 172, 132, and 100 kg N ha−1, respectively, which accounted for 34%, 26%, and 20% of the total added nitrogen. Nitrogen loss from the investigated treatments was in the order: U > SRU > EDPF > C. EDPF significantly reduced the ammonia volatilization compared to U and SRU by reducing the soil pH and increasing the soil organic matter. The dynamic of NH3 emissions not only depends on the nitrogen form but also on climatic conditions and concentrations of NH4+ in the soil solution. Protecting the ecosystem and maximizing the benefits of wastes utilization can be done through the recycling of expired dairy products to organic fertilizers

Integration of Geostatistical and Sentinal-2AMultispectral Satellite Image Analysis for Predicting Soil Fertility Condition in Drylands

For modelling and predicting soil indicators to be fully operational and facilitate decision-making at any spatial level, there is a requirement for precise spatially referenced soil information to be available as input data. This paper focuses on showing the capacity of Sentinal-2A(S2A) multispectral imaging to predict soil properties and provide geostatistical analysis (ordinary kriging) for mapping dry land soil fertility conditions (SOCs). Conditioned Latin hypercube sampling was used to select the representative sampling sites within the study area. To achieve the objectives of this work, 48 surface soil samples were collected from the western part of Matrouh Governorate, Egypt, and pH, soil organic matter (SOM), available nitrogen (N), phosphorus (P), and potassium (K) levels were analyzed. Multilinear regression (MLR) was used to model the relationship between image reflectance and laboratory analysis (of pH, SOM, N, P, and K in the soil), followed by mapping the predicted outputs using ordinary kriging. Model fitting was achieved by removing variables according to the confidence level (95%).Around 30% of the samples were randomly selected to verify the validity of the results. The randomly selected samples helped express the variety of the soil characteristics from the investigated area. The predicted values of pH, SOM, N, P, and K performed well, with R2 values of 0.6, 0.7, 0.55, 0.6, and 0.92 achieved for pH, SOM, N, P, and K, respectively. The results from the ArcGIS model builder indicated a descending fertility order within the study area of: 70% low fertility, 22% moderate fertility, 3% very low fertility, and 5% reference terms. This work evidence that which can be predicted from S2A images and provides a reference for soil fertility monitoring in drylands. Additionally, this model can be easily applied to environmental conditions similar to those of the studied area

Integration of Geostatistical and Sentinal-2AMultispectral Satellite Image Analysis for Predicting Soil Fertility Condition in Drylands

For modelling and predicting soil indicators to be fully operational and facilitate decision-making at any spatial level, there is a requirement for precise spatially referenced soil information to be available as input data. This paper focuses on showing the capacity of Sentinal-2A(S2A) multispectral imaging to predict soil properties and provide geostatistical analysis (ordinary kriging) for mapping dry land soil fertility conditions (SOCs). Conditioned Latin hypercube sampling was used to select the representative sampling sites within the study area. To achieve the objectives of this work, 48 surface soil samples were collected from the western part of Matrouh Governorate, Egypt, and pH, soil organic matter (SOM), available nitrogen (N), phosphorus (P), and potassium (K) levels were analyzed. Multilinear regression (MLR) was used to model the relationship between image reflectance and laboratory analysis (of pH, SOM, N, P, and K in the soil), followed by mapping the predicted outputs using ordinary kriging. Model fitting was achieved by removing variables according to the confidence level (95%).Around 30% of the samples were randomly selected to verify the validity of the results. The randomly selected samples helped express the variety of the soil characteristics from the investigated area. The predicted values of pH, SOM, N, P, and K performed well, with R2 values of 0.6, 0.7, 0.55, 0.6, and 0.92 achieved for pH, SOM, N, P, and K, respectively. The results from the ArcGIS model builder indicated a descending fertility order within the study area of: 70% low fertility, 22% moderate fertility, 3% very low fertility, and 5% reference terms. This work evidence that which can be predicted from S2A images and provides a reference for soil fertility monitoring in drylands. Additionally, this model can be easily applied to environmental conditions similar to those of the studied area

Potassium Source and Biofertilizer Influence K Release and Fruit Yield of Mango (<i>Mangifera indica</i> L.): A Three-Year Field Study in Sandy Soils

Arid degraded soils have a coarse texture and poor organic matter content, which reduces the activity of microorganisms and soil enzymes, and thus the soil quality, plant yield and quality decrease. Potassium solubilizing bacteria (KSB) have been suggested to increase the activity of soil enzymes and increase the release of potassium from natural K-feldspar in the arid degraded soil, and thus potentially reduce the rates of the application of chemical fertilizers. Field studies were conducted for three successive growing seasons in an organic farming system to investigate the effects of K-feldspar and KSB (Bacillus cereus) on K release, soil fertility, and fruit yield of mango plants (Mangifera indica L.). The maximum growth of mango plants was found in the treatments inoculated with KSB. KSB increased soil available N, P, K, and the activity of dehydrogenase and alkaline phosphatase enzymes by 10, 7, 18, 54, and 52%, respectively. KSB increased the fruit yield of mango by 23, 27, and 23% in the first, second, and third growing seasons, respectively. The partial (up to 50%) substitution of chemical K-fertilizer with K-feldspar gave fruit yield and quality very close to that fertilized with the full chemical K-fertilizer. The release rate of K (over all the treatments) varied between 0.18 and 0.64 mg kg−1 of soil per day. KSB significantly increased the K release rate. The application of chemical K-fertilizer gave the highest K release, while substitution with K-feldspar reduced the release of K. Natural K-feldspar contains 8.2% K but is poorly soluble when applied alone. KSB increased the soil quality parameters and enhanced the growth and quality of mango fruit. The fruit yield of mango, under KSB inoculation and fertilization with different K sources, ranged between 9.14 to 17.14 t ha−1. The replacement of 50% of chemical K-fertilizer with natural K-feldspar caused a decrease in the fruit yield by 17, 8, and 2.7% in the first, second, and third years, respectively. The substitution of chemical K-fertilizer with K-feldspar up to 50% with KSB is a good strategy to reduce the excessive use of chemical K-fertilizer. B. cereus and natural K-feldspar have the potential to improve soil health and mango plant productivity in low fertile arid soils

Mechanisms of Chitosan Nanoparticles in the Regulation of Cold Stress Resistance in Banana Plants

Exposure of banana plants, one of the most important tropical and subtropical plants, to low temperatures causes a severe drop in productivity, as they are sensitive to cold and do not have a strong defense system against chilling. Therefore, this study aimed to improve the growth and resistance to cold stress of banana plants using foliar treatments of chitosan nanoparticles (CH-NPs). CH-NPs produced by nanotechnology have been used to enhance tolerance and plant growth under different abiotic stresses, e.g., salinity and drought; however, there is little information available about their effects on banana plants under cold stress. In this study, banana plants were sprayed with four concentrations of CH-NPs—i.e., 0, 100, 200, and 400 mg L−1 of deionized water—and a group that had not been cold stressed or undergone CH-NP treatment was used as control. Banana plants (Musa acuminata var. Baxi) were grown in a growth chamber and exposed to cold stress (5 °C for 72 h). Foliar application of CH-NPs caused significant increases (p &lt; 0.05) in most of the growth parameters and in the nutrient content of the banana plants. Spraying banana plants with CH-NPs (400 mg L−1) increased the fresh and dry weights by 14 and 41%, respectively, compared to the control. A positive correlation was found between the foliar application of CH-NPs, on the one hand, and photosynthesis pigments and antioxidant enzyme activities on the other. Spraying banana plants with CH-NPs decreased malondialdehyde (MDA) and reactive oxygen species (ROS), i.e., hydrogen peroxide (H2O2), hydroxyl radicals (•OH), and superoxide anions (O2•−). CH-NPs (400 mg L−1) decreased MDA, H2O2, •OH, and O2•− by 33, 33, 40, and 48%, respectively, compared to the unsprayed plants. We hypothesize that CH-NPs increase the efficiency of banana plants in the face of cold stress by reducing the accumulation of reactive oxygen species and, in consequence, the degree of oxidative stress. The accumulation of osmoprotectants (soluble carbohydrates, proline, and amino acids) contributed to enhancing the cold stress tolerance in the banana plants. Foliar application of CH-NPs can be used as a sustainable and economically feasible approach to achieving cold stress tolerance

Modeling of P-Loss Risk and Nutrition for Mango (Mangifera indica L.) in Sandy Calcareous Soils: A 4-Years Field Trial for Sustainable P Management

The continuous addition of phosphorus (P) fertilizers above plant requirements increases P loss risks, especially if such fertilization practices continue long-term. The current study aims to determine the threshold value of P in plants and soil, which achieves the maximum mango fruit yield without P loss risk. P fertilizer doses (0&ndash;240 g tree&minus;1) were added to 12-year-old mango (Mangifera indica L.) cv Hindy planted in sandy soil for four consecutive years. Soil and plant samples were collected each year to estimate the critical p values by linear&ndash;linear, quadratic, and exponential models. The relationships between fruit yield and available soil P were positive and significant in all the mathematical models. Mango fruit yield is expected to reach its maximum value if the sandy calcareous soil contains an available P amount ranging between 10&ndash;12 mg kg&minus;1 and increasing the soil available P above this level leads to negligible increases in the fruit yield. Increasing the available soil P above 20.3 mg kg&minus;1 increases P-loss risk. P concentrations in blades and petioles of mango leaves can be arranged as follows: beginning of the flowering stage &gt; the full blooming stage &gt; beginning of the fruiting stage. The analysis of petioles of mango leaves in the beginning of the flowering stage significantly corelated with mango fruit yield and can be used in predicting the response of mango to P fertilization. The findings of the present investigation revealed that the critical P in mango petioles ranged between 2.34 and 3.53 g kg&minus;1. The threshold of available soil P for maximum fruit yield is half of P loss risks. The combined analysis of soil and plants is a powerful diagnostic tool for P management in sandy degraded soil. The findings of the current study are a good tool in achieving the optimum utilization of P fertilizer resources in maximizing mango fruit yield and reducing the risks of environmental pollution that result from excessive fertilization doses