Leaf wettability and leaf angle affect air-moisture deposition in wheat for self-irrigation.

BACKGROUND: Climate change and depleting water sources demand scarce natural water supplies like air moisture to be used as an irrigation water source. Wheat production is threatened by the climate variability and extremes climate events especially heat waves and drought. The present study focused to develop the wheat plant for self-irrigation through optimizing leaf architecture and surface properties for precise irrigation. METHODS: Thirty-four genotypes were selected from 1796 genotypes with all combinations of leaf angle and leaf rolling. These genotypes were characterized for morpho-physiological traits and soil moisture content at stem-elongation and booting stages. Further, a core set of ten genotypes was evaluated for stem flow efficiency and leaf wettability. RESULTS: Biplot, heat map, and correlation analysis indicated wide diversity and traits association. The environmental parameters indicated substantial amount of air moisture (> 60% relative humidity) at the critical wheat growth stages. Leaf angle showed negative association with leaf rolling, physiological and yield traits, adaxial and abaxial contact angle while leaf angle showed positive association with the stem flow water. The wettability and air moisture harvesting indicated that the genotypes (coded as 1, 7, and 18) having semi-erect to erect leaf angle, spiral rolling, and hydrophilic leaf surface (<90o) with contact angle hysteresis less than 10o had higher soil moisture content (6-8%) and moisture harvesting efficiency (3.5 ml). CONCLUSIONS: These findings can provide the basis to develop self-irrigating, drought-tolerant wheat cultivars as an adaptation to climate change.

Leaf prickle hairs and longitudinal grooves help wheat plants capture air moisture as a water-smart strategy for a changing climate.

MAIN CONCLUSION: The leaf features like trichome density, gradient grooves, and leaf wettability determine the efficiency to capture air moisture for self-irrigation in the wheat plant. Plants in water-scarce environments evolved to capture air moisture for their water needs either directly or indirectly. Structural features like cones, hairs, and grooves assist water capture. The morphology of crops such as wheat can promote self-irrigation under drought. To examine this further, 34 wheat genotypes were characterized for leaf traits in near optimal conditions in the field using a randomized complete block design with 3 replications. An association was found between morphological and physiological traits and yield using simple correlation plots. A core set of nine genotypes was subsequently evaluated for moisture harvesting ability and leaf wettability. Results showed that variation among genotypes exists for fog harvesting ability attributed to structural leaf features. Physiological traits, especially photosynthesis and water use efficiency, were positively associated with yield, negatively correlated with soil moisture at booting, and positively correlated with soil moisture at anthesis. The genotypes with deep to medium leaf grooves and dense hairs on the edges and adaxial surfaces (genotypes 7 and 18) captured the most moisture. This was a function of higher water drop rolling efficiency resulting from lower contact angle hysteresis. These results can be exploited to develop more heat and drought-tolerant crops.

Selenium Alleviates the Adverse Effect of Drought in Oilseed Crops Camelina (Camelina sativa L.) and Canola (Brassica napus L.).

Drought poses a serious threat to oilseed crops by lowering yield and crop failures under prolonged spells. A multi-year field investigation was conducted to enhance the drought tolerance in four genotypes of Camelina and canola by selenium (Se) application. The principal aim of the research was to optimize the crop yield by eliciting the physio-biochemical attributes by alleviating the adverse effects of drought stress. Both crops were cultivated under control (normal irrigation) and drought stress (skipping irrigation at stages i.e., vegetative and reproductive) conditions. Four different treatments of Se viz., seed priming with Se (75 µM), foliar application of Se (7.06 µM), foliar application of Se + Seed priming with Se (7.06 µM and 75 µM, respectively) and control (without Se), were implemented at the vegetative and reproductive stages of both crops. Sodium selenite (Na2SeO3), an inorganic compound was used as Se sources for both seed priming and foliar application. Data regarding physiochemical, antioxidants, and yield components were recorded as response variables at crop maturity. Results indicated that WP, OP, TP, proline, TSS, TFAA, TPr, TS, total chlorophyll contents, osmoprotectant (GB, anthocyanin, TPC, and flavonoids), antioxidants (APX, SOD, POD, and CAT), and yield components (number of branches per plant, thousand seed weight, seed, and biological yields were significantly improved by foliar Se + priming Se in both crops under drought stress. Moreover, this treatment was also helpful in boosting yield attributes under irrigated (non-stress) conditions. Camelina genotypes responded better to Se application as seed priming and foliar spray than canola for both years. It has concluded that Se application (either foliar or priming) can potentially alleviate adverse effects of drought stress in camelina and canola by eliciting various physio-biochemicals attributes under drought stress. Furthermore, Se application was also helpful for crop health under irrigated condition.

Ornamental Plant Efficiency for Heavy Metals Phytoextraction from Contaminated Soils Amended with Organic Materials.

Accumulation of heavy metals (HMs) by ornamental plants (OPs) from contaminated agriculture soils is a unique technique that can efficiently reduce the metal load in the food chain. Amaranthus tricolor L. has attractive characteristics acquiring a higher growth rate and large biomass when grown at heavy metal contaminated soils. Site-specific detailed information is not available on the use of A. tricolor plant in metal phytoremediation from the polluted sites. The study aimed to enhance the uptake of HMs (Pb, Zn, and Cu) via amending poultry litter extract (PLE), vinasse sugarcane (VSC), and humic acid (HA) as natural mobilized organic materials compared to ethylene diamine tetraacetic acid (EDTA), as a common mobilized chemical agent by A. tricolor plant. The studied soils collected from Helwan, El-Gabal El-Asfar (Cairo Governorate), Arab El-Madabeg (Assiut Governorate), Egypt, and study have been conducted under pot condition. Our results revealed all organic materials in all studied soils, except EDTA in EL-Gabal El-Asfar soil, significantly increased the dry weight of the A. tricolor plant compared to the control treatment. The uptake of Pb and Zn significantly (p > 0.05) increased due to applying all organic materials to the studied soils. HA application caused the highest uptake as shown in Pb concentration by more than 5 times in Helwan soil and EDTA by 65% in El-Gabal El-Asfar soil while VSC increased it by 110% in El-Madabeg soil. Also, an increase in Zn concentration due to EDTA application was 58, 42, and 56% for Helwan, El-Gabal El-Asfar, and El-Madabeg soil, respectively. In all studied soils, the application of organic materials increased the remediation factor (RF) than the control. El-Madabeg soil treated with vinasse sugarcane gave the highest RF values; 6.40, 3.26, and 4.02% for Pb, Zn, and Cu, respectively, than the control. Thus, we identified A. tricolor as a successful ornamental candidate that, along with organic mobilization amendments, most efficiently develop soil health, reduce metal toxicity, and recommend remediation of heavy metal-contaminated soils. Additionally, long-term application of organic mobilization amendments and continued growth of A. tricolor under field conditions could be recommended for future directions to confirm the results.

Physiological insights into sulfate and selenium interaction to improve drought tolerance in mung bean.

The present study involved two pot experiments to investigate the response of mung bean to the individual or combined SO4 2- and selenate application under drought stress. A marked increment in biomass and NPK accumulation was recorded in mung bean seedlings fertilized with various SO4 2- sources, except for CuSO4. Compared to other SO4 2- fertilizers, ZnSO4 application resulted in the highest increase in growth attributes and shoot nutrient content. Further, the combined S and Se application (S + Se) significantly enhanced relative water content (16%), SPAD value (72%), photosynthetic rate (80%) and activities of catalase (79%), guaiacol peroxidase (53%) and superoxide dismutase (58%) in the leaves of water-stressed mung bean plants. Consequently, the grain yield of mung bean was markedly increased by 105% under water stress conditions. Furthermore, S + Se application considerably increased the concentrations of P (47%), K (75%), S (80%), Zn (160%), and Fe (15%) in mung bean seeds under drought stress conditions. These findings indicate that S + Se application potentially increases the nutritional quality of grain legumes by stimulating photosynthetic apparatus and antioxidative machinery under water deficit conditions. Our results could provide the basis for further experiments on cross-talk between S and Se regulatory pathways to improve the nutritional quality of food crops. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-00992-6.

High arsenic contamination and presence of other trace metals in drinking water of Kushtia district, Bangladesh.

Drinking water with excessive concentration levels of arsenic (As) is a great threat to human health. A hydrochemical approach was employed in 50 drinking water samples (collected from Kushtia district, Bangladesh) to examine the occurrence of geogenic As and the presence of trace metals (TMs), as well as the factors controlling As release in aquifers. The results reveal that the drinking water of shallow aquifers is highly contaminated by As (6.05-590.7 µg/L); 82% of samples were found to exceed the WHO recommended limit (10 µg/L) for potable water, but the concentrations of Si, B, Mn, Sr, Se, Ba, Fe, Cd, Pb, F, U, Ni, Li, and Cr were within safe limits. The Ca-HCO3-type drinking water was identified as having high contents of As, pH and HCO3-, a medium-high content EC, and low concentrations of NO3-, SO42-, K+, and Cl-. The significant correlation between As and NO3- indicates that NO3- might be attributed to the use of phosphate fertilizers and a factor responsible for enhancing As in aquifers. The study also reports that the occurrence of high As and the presence of TMs in drinking water may be a result of local anthropogenic activities, such as irrigation, intensive land use and the application of agrochemicals. The insignificant correlation between As and SO42- demonstrated that As is released from SO42- minerals under reducing conditions. An elevated pH value along with decoupling of As and HCO3- plays a vital role in mobilizing As to aquifer systems. Moreover, the positive relationship between As and Si indicated that As is transported in the biogeochemical environment. The reductive suspension of Mn(IV)-oxyhydroxides also accelerated the As mobilization process. Over exploitation of tube-well water and the competitive ion exchange process are also responsible for the release of As in aquifers.

Study of land cover/land use changes using RS and GIS: a case study of Multan district, Pakistan.

Water and land both are limited resources. Current management strategies are facing multiple challenges to meet food security of an increasing population in numerous South Asian countries, including Pakistan. The study of land cover/land use changes (LCLUC) and land surface temperature (LST) is important as both provide critical information for policymaking of natural resources. We spatially examined LCLU and LST changes in district Multan, Pakistan, and its impacts on vegetation cover and water during 1988 to 2017. The LCLUC indicate that rice and sugarcane had less volatility of change in comparison with both cotton and wheat. Producer's accuracy (PA) is the map accuracy (the producer of map), but user's accuracy (UA) is the accuracy from the point of view of a map user, not the map maker. Average overall producer's and user's accuracy for the region was 85.7% and 87.7% for Rabi (winter) and Kharif (summer) seasons, respectively. The results of this study showed that 'built-up area' increased with 7.2% of all the classes during 1988 to 2017 in the Multan district. Anthropogenic activities decreased the vegetation, leading to an increase in LST in study area. Changes on LCLU and LST during the last 30 years have shown that vegetation pattern has changed and temperature has increased in the Multan district.

Current status and future possibilities of molecular genetics techniques in Brassica napus.

As PCR methods have improved over the last 15 years, there has been an upsurge in the number of new DNA marker tools, which has allowed the generation of high-density molecular maps for all the key Brassica crop types. Biotechnology and molecular plant breeding have emerged as a significant tool for molecular understanding that led to a significant crop improvement in the Brassica napus species. Brassica napus possess a very complicated polyploidy-based genomics. The quantitative trait locus (QTL) is not sufficient to develop effective markers for trait introgression. In the coming years, the molecular marker techniques will be more effective to determine the whole genome impairing desired traits. Available genetic markers using the single-nucleotide sequence (SNP) technique and high-throughput sequencing are effective in determining the maps and genome polymorphisms amongst candidate genes and allele interactions. High-throughput sequencing and gene mapping techniques are involved in discovering new alleles and gene pairs, serving as a bridge between the gene map and genome evaluation. The decreasing cost for DNA sequencing will help in discovering full genome sequences with less resources and time. This review describes (1) the current use of integrated approaches, such as molecular marker technologies, to determine genome arrangements and interspecific outcomes combined with cost-effective genomes to increase the efficiency in prognostic breeding efforts. (2) It also focused on functional genomics, proteomics and field-based breeding practices to achieve insight into the genetics underlying both simple and complex traits in canola.

Upregulation of TaHSP90A transcripts enhances heat tolerance and increases grain yield in wheat under changing climate conditions.

Plants have certain adaptation mechanisms to combat temperature extremes and fluctuations. The heat shock protein (HSP90A) plays a crucial role in plant defence mechanisms under heat stress. In silico analysis of the eight TaHSP90A transcripts showed diverse structural patterns in terms of intron/exons, domains, motifs and cis elements in the promoter region in wheat. These regions contained cis elements related to hormones, biotic and abiotic stress and development. To validate these findings, two contrasting wheat genotypes E-01 (thermo-tolerant) and SHP-52 (thermo-sensitive) were used to evaluate the expression pattern of three transcripts TraesCS2A02G033700.1, TraesCS5B02G258900.3 and TraesCS5D02G268000.2 in five different tissues at five different temperature regimes. Expression of TraesCS2A02G033700.1 was upregulated (2-fold) in flag leaf tissue after 1 and 4h of heat treatment in E-01. In contrast, SHP-52 showed downregulated expression after 1h of heat treatment. Additionally, it was shown that under heat stress, the increased expression of TaHSP90A led to an increase in grain production. As the molecular mechanism of genes involved in heat tolerance at the reproductive stage is mostly unknown, these results provide new insights into the role of TaHSP90A transcripts in developing phenotypic plasticity in wheat to develop heat-tolerant cultivars under the current changing climate scenario.

Dissecting wheat above-ground architecture for enhanced water use efficiency and grain yield in the subtropics.

BACKGROUND: Growing wheat under climate change scenarios challenges, scientists to develop drought and heat-tolerant genotypes. The adaptive traits should therefore be explored and engineered for this purpose. Thus, this study aimed to dissect surface traits and optimizing the leaf architecture to enhance water use efficiency (WUE) and grain yield. Twenty-six wheat genotypes were assessed for five novel leaf traits (NLTs: leaf prickle hairs, groove type, rolling, angle and wettability) under normal, drought and heat conditions following triplicated factorial randomized complete block design (RCBD). The data for NLTs, physiological traits (stomatal conductance, WUE, transpiration, and photosynthesis), and standard morphological and yield traits were recorded. Leaves were sampled at the stem elongation stage (Zadoks 34) to measure the leaf water content (%), contact angle, and to obtain pictures through scanning electron microscopy (SEM). The air moisture harvesting efficiency was evaluated for five selected genotypes. The ideotype concept was applied to evaluate the best-performing genotypes. RESULTS: The correlation analysis indicated that long leaf prickle hairs (> 100 µm), short stomatal aperture and density (40-60 mm- 2), inward to spiral leaf rolling, medium leaf indentation, low contact angle hysteresis (< 10°), and cuticular wax were positively associated with WUE. This, in turn, was significantly correlated to grain yield. Thus, the genotypes (E-1) with these traits and alternate leaf wettability had maximum grain yield (502 g m- 2) and WUE supported with high photosynthesis rate, and relative water content (94 and 75% under normal and stress conditions, respectively). However, the genotype (1-hooded) with dense leaf hairs on edges but droopy leaves, spiral leaf rolling, and lighter groove, also performed better in terms of grain yield (450 g m- 2) under heat stress conditions by maintaining high photosynthesis and WUE with low stomatal conductance and transpiration rate. CONCLUSION: The SEM analysis verified that the density of hairs on the leaf surface and epicuticular wax contributes towards alternate wettability patterns thereby increasing the water-use efficiency and yield of the wheat plant. This study paves a way towards screening and and developing heat and drought-tolerant cultivars that are water-saving and climate-resilient.

Prioritizing strategies for wheat biofortification: Inspiration from underutilized species.

The relationship between malnutrition and climate change is still poorly understood but a comprehensive knowledge of their interactions is needed to address the global public health agenda. Limited studies have been conducted to propose robust and economic-friendly strategies to augment the food basket with underutilized species and biofortify the staples for nutritional security. Sea-buckthorn is a known "superfood" rich in vitamin C and iron content. It is found naturally in northern hemispherical temperate Eurasia and can be utilized as a model species for genetic biofortification in cash crops like wheat. This review focuses on the impacts of climate change on inorganic (iron, zinc) and organic (vitamin C) micronutrient malnutrition employing wheat as highly domesticated crop and processed food commodity. As iron and zinc are particularly stored in the outer aleurone and endosperm layers, they are prone to processing losses. Moreover, only 5% Fe and 25% Zn are bioavailable once consumed calling to enhance the bioavailability of these micronutrients. Vitamin C converts non-available iron (Fe3+) to available form (Fe2+) and helps in the synthesis of ferritin while protecting it from degradation at the same time. Similarly, reduced phytic acid content also enhances its bioavailability. This relation urges scientists to look for a common mechanism and genes underlying biosynthesis of vitamin C and uptake of Fe/Zn to biofortify these micronutrients concurrently. The study proposes to scale up the biofortification breeding strategies by focusing on all dimensions i.e., increasing micronutrient content and boosters (vitamin C) and simultaneously reducing anti-nutritional compounds (phytic acid). Mutually, this review identified that genes from the Aldo-keto reductase family are involved both in Fe/Zn uptake and vitamin C biosynthesis and can potentially be targeted for genetic biofortification in crop plants.

Corrigendum: Sub-surface drip fertigation improves seed cotton yield and monetary returns.

[This corrects the article DOI: 10.3389/fpls.2022.1038163.].

Modelling, mapping and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote sensing data.

The present study is designed to monitor the spatio-temporal changes in forest cover using Remote Sensing (RS) and Geographic Information system (GIS) techniques from 1990 to 2017. Landsat data from 1990 (Thematic mapper [TM]), 2000 and 2010 (Enhanced Thematic Mapper [ETM+]), and 2013 to 2017 (Operational Land Imager/Thermal Infrared Sensor [OLI/TIRS]) were classified into the classes termed snow, water, barren land, built-up area, forest, and vegetation. The method was built using multitemporal Landsat images and the machine learning techniques Support Vector Machine (SVM), Naive Bayes Tree (NBT) and Kernel Logistic Regression (KLR). According to the results, forest area was decreased from 19,360 km2 (26.0%) to 18,784 km2 (25.2%) from 1990 to 2010, while forest area was increased from 18,640 km2 (25.0%) to 26,765 km2 (35.9%) area from 2013 to 2017 due to "One billion tree Project". According to our findings, SVM performed better than KLR and NBT on all three accuracy metrics (recall, precision, and accuracy) and the F1 score was >0.89. The study demonstrated that concurrent reforestation in barren land areas improved methods of sustaining the forest and RS and GIS into everyday forestry organization practices in Khyber Pakhtun Khwa (KPK), Pakistan. The study results were beneficial, especially at the decision-making level for the local or provincial government of KPK and for understanding the global scenario for regional planning.

Morpho-physiological and biochemical response of wheat to various treatments of silicon nano-particles under drought stress conditions.

Silicon nanoparticles (Si-NPs) have shown their potential for use in farming under water-deficient conditions. Thus, the experiment was accomplished to explore the impacts of seed priming of Si-NPs on wheat (Triticum aestivum L.) growth and yield under different drought levels. The plants were grown in pots under natural ecological environmental conditions and were harvested on 25th of April, 2020. The results revealed that seed priming of Si-NPs (0, 300, 600, and 900 mg/L) suggestively improved, the spike length, grains per spike, 1000 grains weight, plant height, grain yield, and biological yield by 12-42%, 14-54%, 5-49%, 5-41%, 17-62%, and 21-64%, respectively, relative to the control. The Si-NPs improved the leaf gas trade ascribes and chlorophyll a and b concentrations, though decreased the oxidative pressure in leaves which was demonstrated by the diminished electrolyte leakage and upgrade in superoxide dismutase and peroxidase activities in leaf under Si-NPs remedies over the control. The outcomes proposed that Si-NPs could improve the yield of wheat under a dry spell. In this manner, the utilization of Si-NPs by seed priming technique is a practical methodology for controlling the drought stress in wheat. These findings will provide the basis for future research and helpful to improve the food security under drought and heat related challenges.

Impact analysis of moisture stress on growth and yield of cotton using DSSAT-CROPGRO-cotton model under semi-arid climate.

Adequate soil moisture around the root zone of the crops is essential for optimal plant growth and productivity throughout the crop season, whereas excessive as well as deficient moisture is usually detrimental. A field experiment was conducted on cotton (Gossipium hirsuttum) with three water regimes (viz. well-watered (control); rainfed after one post-sowing irrigation (1-POSI) and rainfed after two post-sowing irrigations (2-POSI)) in main plots and application of eight osmoprotectants in sub plots of Split plot design to quantify the loss of seed cotton yield (SCY) under high and mild moisture stress. The DSSAT-CROPGRO-cotton model was calibrated to validate the response of cotton crop to water stress. Results elucidated that in comparison of well watered (control) crop, 1-POSI and 2-POSI reduced plant height by 13.5-28.4% and lower leaf area index (LAI) by 21.6-37.6%. Pooled analysis revealed that SCY under control was higher by 1,127 kg ha-1 over 1-POSI and 597 kg ha-1 than 2-POSI. The DSSAT-CROPGRO-cotton model fairly simulated the cotton yield as evidenced by good accuracy (d-stat ≥ 0.92) along with lower root mean square error (RMSE) of ≤183.2 kg ha-1; mean absolute percent error (MAPE) ≤6.5% under different irrigation levels. Similarly, simulated and observed biomass also exhibited good agreement with ≥0.98 d-stat; ≤533.7 kg ha-1 RMSE; and ≤4.6% MAPE. The model accurately simulated the periodical LAI, biomass and soil water dynamics as affected by varying water regimes in conformity with periodical observations. Both the experimental and the simulated results confirmed the decline of SCY with any degree of water stress. Thus, a well calibrated DSSAT-CROPGRO-cotton model may be successfully used for estimating the crop performance under varying hydro-climatic conditions.

The use of Multispectral Radio-Meter (MSR5) data for wheat crop genotypes identification using machine learning models.

Satellite remote sensing is widely being used by the researchers and geospatial scientists due to its free data access for land observation and agricultural activities monitoring. The world is suffering from food shortages due to the dramatic increase in population and climate change. Various crop genotypes can survive in harsh climatic conditions and give more production with less disease infection. Remote sensing can play an essential role in crop genotype identification using computer vision. In many studies, different objects, crops, and land cover classification is done successfully, while crop genotypes classification is still a gray area. Despite the importance of genotype identification for production planning, a significant method has yet to be developed to detect the genotypes varieties of crop yield using multispectral radiometer data. In this study, three genotypes of wheat crop (Aas-'2011', 'Miraj-'08', and 'Punjnad-1) fields are prepared for the investigation of multispectral radio meter band properties. Temporal data (every 15 days from the height of 10 feet covering 5 feet in the circle in one scan) is collected using an efficient multispectral Radio Meter (MSR5 five bands). Two hundred yield samples of each wheat genotype are acquired and manually labeled accordingly for the training of supervised machine learning models. To find the strength of features (five bands), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Nonlinear Discernment Analysis (NDA) are performed besides the machine learning models of the Extra Tree Classifier (ETC), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), k Nearest Neighbor (KNN) and Artificial Neural Network (ANN) with detailed of configuration settings. ANN and random forest algorithm have achieved approximately maximum accuracy of 97% and 96% on the test dataset. It is recommended that digital policymakers from the agriculture department can use ANN and RF to identify the different genotypes at farmer's fields and research centers. These findings can be used for precision identification and management of the crop specific genotypes for optimized resource use efficiency.

Using the Taguchi experimental design for assessing within-field variability of surface run-off and soil erosion risk.

Water erosion is one of the soil degradation processes driven by environmental and field factors such as rainfall intensity, slope gradient, dynamics of vegetation cover, soil characteristics, and management practices. Most of the studies assess the separate contribution of these factors under controlled conditions. However, there is a lack of adequate knowledge regarding the complex interactions between prevailing factors and soil erosion processes under heterogeneous field conditions. This study investigated 16 combinations of 5 factors at 4 levels of each factor on the soil erosion process using Taguchi's fractional factorial experiment design, identifying the factor combinations resulting in maximum sediment yield, runoff, organic carbon, and nitrogen losses. We considered the factors: Soil organic matter and silt content (SiltOM), vegetation cover (VC), slope steepness (SS), rainfall intensity (RI), and depth to a loamy layer (DLL). The interactive effects of these factors and their combinations were visualized from the analysis of signal-to-noise (S/N) responses. Results indicated that interactions between the selected factors and soil erosion processes exist and multiple linear regression models were developed to predict sediment yields, runoff, carbon, and nitrogen losses at the sub-field scale. Results revealed that 1) RI with 40.6% showed the highest contribution to sediment yield followed by SS (23.8%), VC (17.74%), SiltOM (14.77%), and DLL (3.17%), indicating a strong rainfall-erosion relationship; 2) the combination of levels of factors generating highest sediment yield was determined; 3) A simple multiple linear regression model developed for predicting local sediment yield showed the highest agreement with field observations (R2 = 82.5%). The findings suggest that Taguchi design could be used reliably for modeling soil erosion at field and sub-field scales. Using local calibration data such models have great potential for soil erosion risk assessments at the field scale, especially in areas where contributing factors and factor levels change at small spatial scales.

Leaf rolling and leaf angle improve fog capturing and transport in wheat; adaptation for drought stress in an arid climate.

BACKGROUND: Plants use different mechanisms to transport the collected fog water. Leaf traits of wheat play an important role in directing fog water through leaf rolling and leaf angle into the root zone, where it can be stored for consumption. Wheat leaf traits can enhance fog capturing under drought stress. To examine this, 200 wheat genotypes were characterized for leaf rolling and leaf angle under optimal conditions in the field using a randomized complete block design. Seven different phenotypic combinations for leaf traits were observed. A core set of 44 genotypes was evaluated under drought stress. RESULTS: Results show that variability for leaf traits existed among genotypes. An association was found between leaf rolling and leaf angle, moisture capturing, physiological parameters, and yield contributing traits using correlation. Physiological parameters, especially water use efficiency, were positively correlated with grain yield and moisture capturing at both growth stages. The genotypes (G11 at tillering and G24 at booting phonological phases) with inward to twisting type rolling and erect to semi-erect leaf angle capture more water (12-20%) within the root zone. Twenty-one genotypes were selected based on moisture capturing efficiency and evaluated for leaf surface wettability. Association was found between fog capturing and wettability. This shows that it was due to the leaf repellency validated from static contact angle measurements. CONCLUSION: These results will give insights into fog capturing and the development of drought-tolerant crops in the semi-arid and arid regions.

Leaf rolling dynamics for atmospheric moisture harvesting in wheat plant as an adaptation to arid environments.

Plant species surviving in the arid regions have developed novel leaf features to harvest atmospheric water. Before the collected water evaporates, it is absorbed and transported for storage within the tissues and move toward the root zone through the unique chemistry of leaf structures. Deep insights into such features reveal that similarities can be found in the wheat plant. Therefore, this study aimed to evaluate the leaf rolling dynamics among wheat genotypes and their relationships with moisture harvesting and its movement on the leaf surface. For this purpose, genotypes were characterized for leaf rolling at three distinct growth stages (tillering, booting, and spike emergence). The contact angle of leaf surface dynamics (adaxial and abaxial), water budget, and morphophysiological traits of genotypes were measured. The results indicate that leaf rolling varies from inward to twisting type among genotypes and positively affected the water use efficiency and soil moisture difference at all growth stages under normal and drought conditions. Results of wetting property (hydrophilic < 90°) of the leaf surface were positively associated with the atmospheric water collection (4-7 ml). The lower values of contact angle hysteresis (12-19°) also support this mechanism. Thus, genotypes with leaf rolling dynamics (inward rolled and twisted) and surface wettability is an efficient fog harvesting system in wheat for interception and utilization of fog water in drought-prone areas. These results can be exploited to develop self-irrigated and drought-tolerant crops.

Growth and productivity assessments of peanut under different irrigation water management practices using CSM-CROPGRO-Peanut model in Eastern Mediterranean of Turkey.

Irrigation water scheduling is crucial to make the most efficient use of ever-decreasing water. As excessive irrigation decreases yield, while imprecise application also causes various environmental issues. Therefore, efficient management of irrigation frequency and irrigation level is necessary to sustain productivity under limited water conditions. The objective of the current study is to assess the water productivity at various irrigation regimes during peanut crop growing seasons (2014 and 2015) in Eastern Mediterranean, Turkey. The field experiments were conducted with treatments consisting of three irrigation frequencies (IF) (IF1: 25 mm; IF2: 50 mm; and IF3: 75 mm of cumulative pan evaporation (CPE)), and four irrigation water levels (WL1 = 0.50, WL2 = 0.75, WL3 = 1.0, and WL4 = 1.25). WL1, WL2, WL3, and WL4 treatments received 50, 75, 100, and 125 of cumulative pan evaporation. The CSM-CROPGRO-Peanut model was calibrated with experimental data in 2014 and evaluated with second-year experimental data (2015). The model simulated seed yield and final biomass (dry matter) reasonably well with low normalized root mean square error (RMSEn) in various irrigation intervals. The model simulated reasonably well for days to anthesis (RMSE = 2.53, d-stat = 0.96, and r2 = 0.90), days to physiological maturity (RMSE = 2.55), seed yield (RMSE = 1504), and tops biomass dry weight at maturity (RMSE = 3716). Simulation results indicated good agreement between measured and simulated soil water content (SWC) with low RMSEn values (4.0 to 16.8% in 2014 and 4.3 to 18.2% in 2015). Further results showed that IF2I125 irrigation regime produced the highest seed yield. Generally, model evaluation performed reasonably well for all studied parameters with both years' experimental data. Results also showed that the crop model would be a precision agriculture tool for the extrapolation of the allocation of irrigation water resources and decision management under current and future climate.