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Tomatoes are delicate and prone to damage quickly, which ultimately leads to lower quality and increased post-harvest losses. Hence, an ideal storage environment is very important to maintain the quality of tomato fruits after harvest. Therefore, this study was conducted to determine the effect of storage conditions on the quality parameters of tomato fruits. Experiments were de-signed for six storage periods (4, 8, 12, 16, 20, and 24 days) and two temperatures (12 °C and room air temperature “22 °C”). Three tomato fruit quality parameters (Brix, color, and firmness) have been selected and measured for three tomato varieties (Ghandowra-F1, Forester-F1, and Feisty-Red) grown hydroponically at three salinity levels (2.5, 6.0, and 9.5 dS m−1) of the nutrient solution. Results showed that the highest mean Brix values, for all varieties, were recorded at the highest salinity (9.5 dS m−1), and were significantly (Pr < 0.0001) higher than those at medium (6.0 dS m−1) and low (2.5 dS m−1) salinity levels. In addition, the highest fruit firmness was recorded at high salinity level (9.5 dS m−1), but there was no significant difference to that recorded at medium salinity (6.0 dS m−1). Regarding tomato fruit color, the highest average values were recorded for the Ghandowra-F1 (2.51) and Forester-F1 (2.69) varieties at medium salinity (6.0 dS m−1), while the highest average color value for the Feisty-Red variety (1.54) was obtained at high salinity (9.5 dS m−1). On the other hand, the Brix, color, and firmness of tomato fruits were significantly affected by the storage temperature. Moreover, the mean Brix values (7.66%) were slightly higher at 12 °C storage temperature compared to those at 22 °C (7.38%). In general, the fruit color values gradually increased with the storage period, especially under 22 °C storage temperature, with peak color values of 2.73, 2.70, and 1.66 recorded on the 12th day of the storage period for Ghandowra-F1, Forester-F1, and Feisty-Red, respectively. Tomato fruit firmness decreased faster with the storage period at 22 °C compared to the storage temperature of 12 °C. However, the highest average values of fruit firmness for Ghandowra-F1 (9.37 N cm−1) and Forester-F1 (9.41 N cm−1) recorded at control condition were not significantly different those recorded on the 8th day of storage at 12 °C storage temperature. By contrast, the highest average value of fruit firmness for Feisty-Red (8.85 N cm−1) recorded at control condition was not significant than that recorded on the 4th day of the storage period at 12 °C storage temperature (8.82 N cm−1). Overall, tomato fruits can be stored at 12 °C temperature for up to 20–24 days, without negative effects on fruit quality.

Tomato (Solanum lycopersicum L.) is an important vegetable crop that grows easily under controlled conditions, such as in greenhouses and hydroponics. To overcome freshwater scarcity, researchers are searching for alternatives to groundwater sources such as desalinated water (saline water) for irrigation. High salinity in irrigation water alters physiological functions and crop development, thereby reducing the yield. Best management practices and the use of grafted tomato plants on salt-tolerant rootstocks can alleviate salinity stress. The present study was conducted to address the impact of salinity stress on leaf transpiration (Tr), stomatal conductance (gs), photosynthesis (Pn), leaf chlorophyll content, proline content, and yield of hydroponically cultivated tomato plants. Saline (NaCl) water was used for the preparation of nutrient solution with three salinity levels, electrical conductivity (EC, dS m-1) of 2.5 (control), 6.0, and 9.5. Three commercial tomato cultivars (Valouro-RZ, Ghandora-F1, and Feisty-Red) were used. Both self-rooted plants and plants grafted onto Maxifort rootstocks were transplanted onto a perlite substrate. The recorded data revealed that all studied cultivars were critically affected by higher salinity (≈ 9.5 dS m-1) compared to low (≈ 2.5 dS m-1) and medium (≈ 6.0 dS m-1) salinity levels. The Variations in Tr, Pn, gs, chlorophyll content of leaf, and yield between medium and high salinity trials were reported at 3%, 5%, 9%, 5%, and 7.1%, respectively, whereas no significant differences were observed between low and medium salinities. However, at medium salinity levels, grafted plants performed better in photosynthesis than non-grafted plants. This is due to the accumulation of leaf proline, which maintains osmotic regulation and photosynthetic activity by preventing cell damage at medium salinities. Hence, this study confirmed the use of saline water for growing tomatoes under hydroponic conditions up to an EC of 6.0 dS m-1 including the EC of nutrient fertilizers.

To overcome the scarcity of fresh water, researchers have turned to investigating different techniques that enable using saline water to irrigate crops, aiming to increase the efficiency of using available water resources. A glasshouse experiment was conducted to investigate the yield responses of grafted and non-grafted (self-rooted) tomato plants grown hydroponically under three levels of water salinity (2.5, 6.0, and 9.5 dS m−1). Three tomato varieties (Ghandowra-F1, Forester-F1, and Feisty-Red) were grafted onto five rootstocks (Maxifort, Unifort, Dynafort, Vivifort, and Beaufort). The implemented treatments were studied in terms of tomato fruit yield and quality parameters. Although increasing the concentration of salts in the nutrient solution led to a decrease in fruit yield, the moderate salinity level (S-2: 6.0 dS m−1) showed its superiority over both low salinity (S-1: 2.5 dS m−1) and high salinity (S-3: 9.5 dS m−1) in terms of tomato yield parameters. The studied rootstocks did not significantly improve the tomato fruit yield, but the interaction between the grafting combinations and salinity was significant for both production and quality. More specifically, tomato plants grafted onto the rootstocks “Vivifort and Beaufort” rendered the highest yield at a low salinity level (S-1: 2.5 dS m−1) and a moderate salinity level (S-2: 6.0 dS m−1), respectively, while at high salinity (S-3: 9.5 dS m−1), grafting did not improve tomato productivity, irrespective of the rootstock. These results confirm that tomatoes can be successfully grown under hydroponic systems using salinity levels of up to 6.0 dS m−1 without sacrificing fruit yield and quality. Among the studied tomato varieties, Feisty-Red was found to be appropriate for hydroponic production. The results also demonstrated that Vivifort and Beaufort rootstocks are suitable for grafting hydroponic tomatoes under low and moderate salinity levels, respectively.

In Malaysia, wetland rice is cultivated over two cropping seasons: the main season, from June to November, and the off-season, from January to June. The aim of this study was to investigate tillage operations in rice production in relation to actual field operations and under real field conditions for two rice cultivation seasons. The results showed that 80.7%, 17%, and 2.3% of the total time was spent on the actual operation, turning time, and reversing time, respectively. The results also showed that the mean effective field capacity, field efficiency, and fuel consumption were 1.2 ha/h, 80%, and 7.6 L/ha, respectively. The distribution of energy used in the first, second, and third tillage passes amounted to 37%, 33%, and 30% of the total energy, respectively. Fuel, machinery, and total GHG emissions were 62.4, 7.6, and 70 kg CO2eq/ha, respectively. Fuel represented the highest contributor of energy expenditure and GHG emissions. The distributions of GHG emissions in the first, second, and third tillage passes were 37%, 32%, and 31% of the total GHG emissions. The results reveal that carrying out minimum-tillage operations led to a reduction in environmental impacts.

Remotely sensed images provide effective sources for monitoring crop growth and the early prediction of crop productivity. To monitor carrot crop growth and yield estimation, three 27 ha center-pivot irrigated fields were studied to develop yield prediction models using crop biophysical parameters and vegetation indices (VIs) extracted from Sentinel-2A (S2) multi-temporal satellite data. A machine learning (ML)-based image classification technique, the random forest (RF) algorithm, was used for carrot crop monitoring and yield analysis. The VIs (NDVI, RDVI, GNDVI, SIPI, and GLI), extracted from S2 satellite data for the crop ages of 30, 45, 60, 75, 90, 105, and 120 days after plantation (DAP), and the chlorophyll content, SPAD (Soil Plant Analysis Development) meter readings, were incorporated as predictors for the RF algorithm. The RMSE of the five RF scenarios studied ranged from 7.8 t ha−1 (R2 ≥ 0.82 with Scenario 5) to 26.2 t ha−1 (R2 ≤ 0.46 with Scenario 1). The optimal window for monitoring the carrot crop for yield prediction with the use of S2 images could be achieved between the 60 DAP and 75 DAP with an RMSE of 8.6 t ha−1 (i.e., 12.4%) and 11.4 t ha−1 (16.2%), respectively. The developed RF algorithm can be utilized in carrot crop yield monitoring and decision-making processes for the self-sustainability of carrot production.

Salinity is one of the major environmental stresses threatening crop production, the natural ecosystem, global food security, and the socioeconomic health of humans. Thus, the development of eco-friendly strategies to mitigate saline stress and/or enhance crop tolerance is an important issue worldwide. Therefore, this study was conducted during the summer of 2022 to investigate the potential of 24-Epibrassinolide (EBL) for mitigating saline stress and improving photosynthetic capacity, antioxidant defense systems, mineral uptake, and yield in maize (Zea mays L.) grown under a controlled hydroponic system. Three saline stress levels—S1 (control/no added NaCl), S2 (60 mM NaCl), and S3 (120 mM NaCl)—were continuously applied with nutrient solution, whereas exogenous EBL (i.e., control, 0.1 µM and 0.2 µM) was applied as exogenous application three times (i.e., 40, 55, 70 days after sowing). The experiment was designed as a split-plot in a randomized complete block design (RCBD) in which saline stress was the main factor and EBL treatment was the sub-factor. Results showed that saline stress significantly affected plant growth, physiological performance, biochemistry, antioxidant activity, and yield attributes. However, the exogenous application of EBL at 0.2 µM significantly mitigated the salt stress and thus improved plant performance even under 120 mM NaCl saline stress. For instance, as compared to untreated plants (control), 0.2 µM EBL application improved plant height (+18%), biomass (+19%), SPAD (+32%), Fv/Fm (+28%), rate of photosynthesis (+11%), carboxylation efficiency (+6%), superoxide dismutase (SOD +14%), catalase (CAT +18%), ascorbate peroxidase (APX +20%), K+ (+24%), 100-grain weight (+11%), and grain yield (+47%) of maize grown under salt stress. Additionally, it resulted in a 23% reduction in Na+ accumulation in leaves and a 25% reduction in for Na+/K+ ratio under saline stress as compared to control. Furthermore, the Pearson’s correlation and principal component analysis (PCA) highlighted the significance of exogenous EBL as saline stress mitigator in maize. Overall, our results indicated the protective effects of EBL application to the alleviation of saline stress in crop plants. However, further exploration of its mechanism of action and crop-specific response is suggested prior to commercial use in agriculture.

Salinity is one of the most threatening abiotic stresses to agricultural production, alarmingly expanding both through natural salinization phenomena and anthropogenic activities in recent times. The exploration of sustainable and eco-friendly strategic approaches for mitigating the negative impact of salinity on food crops is of vital importance for future food security. Therefore, our study aimed to evaluate zinc oxide nanoparticles (ZnO-NPs) as potent salinity mitigators in maize (Zea mays L.). Three ZnO-NPs foliar treatments (i.e., 0, 50, and 100 mg/L) were applied 40, 55, and 70 days after sowing on maize plants exposed to continuous salinities of 0 mM NaCl (S0), 60 mM NaCl (S1), and 120 mM NaCl (S3) in a semi-automated greenhouse facility. Results showed that the highest salinity (i.e., 120 mM NaCl) significantly affected plant growth attributes, physiological performance, nutrient profiles, antioxidant activity, plant yield, and yield-contributing characteristics of maize plants. Thus, 120 mM NaCl resulted in −53% number of grains per cob (NG), −67% grains weight per cob (GW), −36% 100-grains weight (HGW), and −72% grain yield per plant (GY) compared to controls. However, foliar treatment of maize plants with ZnO-NPs successfully mitigated salinity and significantly improved all studied parameters, except transpiration rate (TR) and intrinsic water use efficiency (iWUE). Foliar application of 100 mg/L of ZnO-NPs alleviated NG, GW, HGW, and GY by 31%, 51%, 13%, and 53%, respectively. Furthermore, principal component analysis (PCA) and Pearson’s correlation further strengthened the significance of ZnO-NP application as salinity mitigators.

Tomato is among important vegetable crops cultivated in different climates; however, heat stress can greatly affect fruit quality and overall yield. Crop reflectance measurements based on ground reflectance sensor data are reliable indicators of crop tolerance to abiotic stresses. Here, we report on using non-destructive spectral vegetation indices to monitor yield traits of 10 tomato genotypes transplanted on three different dates (Aug. 2, Sept. 3 and Oct. 1) during 2019 growing season in the Riyadh region. The ten genotypes comprised six commercial cultivars–(Pearson Improved, Strain B, Valentine, Marmande VF, Super Strain B, and Pearson early) ––and four local Saudi cultivars (Al-Ahsa, Al-Qatif, Hail and Najran). Spectral reflectance data were utilized using a FieldSpec 3 spectroradiometer in the range of 350–2500 nm to calculate nine vegetation indices (VIs): Normalized Water Band Index (NWBI), Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Red Edge Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index (SAVI), Red Edge Normalized Difference Vegetation Index (RENDVI), Renormalized Difference Vegetation Index (RDVI), and Normalized Difference Nitrogen Index (NDNI). VIs and yield parameters (total fruit yield, harvest index) revealed that second transplanting date was optimal for all the genotypes. Valentine showed the best growth performance followed by Najran, Hail, Super Strain B and finally Pearson early. For all the three transplanting dates, Valentine recorded the highest total fruit yield. Additionally, some genotypes had no significant differences in the VIs values or the total fruit yield between the second and third transplanting dates. This study indicated that yield parameters could be linked to rapid, non-destructive hyperspectral reflectance data to predict tomato production under heat stress.

In Saudi Arabia, irrigation water is mainly obtained from aquifers and is mostly characterized by moderate to high levels of salinity. Hence, detailed information on crop response to salinity is of great importance in order to optimize irrigation and fertilizer management. Therefore, this study was conducted to evaluate the effect of salinity and grafting on the spectral behavior and yield of three tomato (Solanum lycopersicum) cultivars (Valouro-RZ, Ghandowra-F1 and Feisty-Red) grown in a hydroponic glass greenhouse. Three salinity levels (2.5, 6.0 and 9.5 dS m−1) were used in this study. For the three tomato cultivars, the increase in salinity level was associated with an increase in the spectral reflectance in the Visible, Red-Edge and NIR regions of the electromagnetic spectrum. However, Valouro-RZ and Feisty-Red cultivars showed no significant differences in the spectral reflectance in the Visible range between salinity1 (2.5 dS m−1) and salinity2 (6.0 dS m−1). Slight reduction, but not significant, in the total fruit yield was recorded under salinity2 compared to salinity1 (2.5 dS m−1) for Valouro-RZ (6.76%) and Feisty-Red (6.79%). For salinity3 (9.5 dS m−1), significant reductions in total fruit yield were recorded compared to salinity1 (Valouro-RZ: 31.77%, Feisty-Red: 33.53%). Ghandowra-F1 cultivar was found to be the most salt tolerant among the studied tomato cultivars, where a significant reduction was observed in the total fruit yield only when the salinity increased from 2.5 to 6.0 dS m−1 (10.85%) and 9.5 dS m−1 (30.63%). Grafting on Maxifort rootstock showed neither a significant effect on the spectral response nor a significant yield improvement; hence, no positive change in salinity tolerance, due to grafting, of the studied tomato cultivars. Therefore, further research on rootstock and fruit variant combinations for the feasibility of grafting for salinity tolerance is necessary. The results of this study indicated that the Valouro-RZ and Feisty-Red tomato cultivars could be grown successfully under a hydroponic system using irrigation water of up to 6.0 dS m−1 salt concentration without sacrificing the total fruit yield while taste may improve.

The effects of saline water on three greenhouse tomato cultivars (Feisty-Red, Ghandowra-F1, and Valouro-RZ) under three salinity concentrations (S1, ~2.5 dS m−1; S2, ~6.0 dS m−1; and ~9.0 dS m−1) and four nutrient regimes (N1–N4) were studied by evaluating the vegetative growth, chlorophyll content, leaf area, water use efficiency (WUE), and fruit yield of the cultivars. Vegetative growth parameters, such as plant height, leaf area, and stem diameter, were negatively correlated with increased levels of salinity. Also, the lowest WUE was noted for the high-salinity (~9.0 dS m−1) treatments. The Valouro-RZ cultivar performed better in terms of vegetative growth parameters when compared to both the Ghandowra-F1 and Feisty-Red cultivars. The plants grafted onto Maxifort rootstock showed more tolerance to salinity stress, with significant differences in plant growth, tomato yield, and WUE when compared with the non-grafted plants. The use of a modified nutrient solution (N2) in combination with moderately saline water (S2, ~6.0 dS m−1) resulted in a high mean yield (30.7 kg m−2), with a reduction of about ~1.6% compared with the mean yield of the control (i.e., the combination of S1 and N1), which was estimated to be about 31.2 kg m−2. High salinity significantly affected the mean WUE, which was the highest at 31.3 kg m−3 for the control plants (low salinity—S1), followed by the moderate-salinity (S2) plants at 30.4 kg m−3, and the lowest mean WUE was recorded for the high-salinity (S3) plants at 17.7 kg m−3. These results indicate that a combination of grafting onto rootstocks and using an appropriate nutrient recipe (i.e., N2 in this study) can mitigate the negative effects of salt stress on tomato plants grown under hydroponic conditions.

A study was conducted, on a 30 ha wheat field under a solar energy powered center pivot irrigation system in a commercial farm located 400 km north of Khartoum, Sudan, to evaluate the feasibility of variable rate fertilizer application of Diammonium Phosphate (DAP) on wheat crop based on variable soil phosphorus content. Soil phosphorus content was divided into three categories (low: 3.75 to 4.50 ppm, medium: 4.51 to 5.25 ppm and high: 5.26 to 6.00 ppm) and a GIS soil phosphorus content map of the experimental field was generated. Three variable application rates (200 kg ha−1, 160 kg ha−1 and 120 kg ha−1) of granular DAP fertilizer were determined to fit the low, medium and high soil phosphorus contents, respectively. The the DAP fertilizer rate of 200 kg ha−1 was the rate practiced for wheat production in the experimental farm.The normalized Difference Vegetation Index (NDVI), measured at different wheat growth stages using sentinel-2 satellite images, and wheat grain yield were used to evaluate the response of wheat crop to the variable DAP fertilizer application rates. Excluding the tillering stage, the results showed significant differences in the NDVI values among different soil phosphorus levels and DAP fertilizer application rates at other growth stages, including stem elongation, grain filling and maturity stages. Moreover, wheat yield results showed significant differences among different soil phosphorus contents (P > F = 0.0001) and DAP fertilizer application rates (P > F = 0.0457). On the average, the highest yield of 2.449 t ha−1 was recorded in the field areas treated with the high DAP fertilizer application rate (200 kg ha−1), where the second highest yield of 2.441 t ha−1 was observed in field areas under the medium DAP fertilizer application rate (160 kg ha−1); however, no significant differences between these two yield values. Based on these results, the total savings of the DAP fertilizer was estimated to be 792 kg (equivalent to 475.2 $) in the experimental field (30 ha), only when the medium DAP fertilizer rate (160 kg ha−1) was used in the medium and high soil phosphorus zones, saving 15.84 $ ha−1 without affecting production.

Salinity is one of the most devastating environmental factors limiting crop productivity worldwide. Therefore, our study investigates the effect of seed priming with zinc oxide nanoparticles (ZnO NPs: 0, 50, and 100 mg L−1), 24-epibrassinolide (EBL: 0.0, 0.2, and 0.4 µM), and their combined treatments on maize (Zea mays L.) grown with different levels of saline stress (i.e., control, 5, 10 dS m−1) under semi-controlled conditions. Higher saline stress (10 dS m−1) negatively influenced the growth traits, physiological attributes, and elemental (i.e., Zn and K) uptake for both roots and shoots of maize, whereas it increased Na+ accumulation and Na+/K+ ratio in comparison to other treatments. However, seed priming with ZnO NPs and EBL as well as their combinations showed amelioration of the detrimental effects of saline stress on the growth and physiological and biochemical performance of maize. In general, seed priming with combined treatments of ZnO NPs and EBL were significantly more effective than either ZnO NPs or EBL as individual treatments. A combination of 100 mg L−1 ZnO NPS + 0.2 µM EBL resulted in the highest values of root length, root surface area, stem diameter, relative leaf water contents, total chlorophyll, net rate of photosynthesis, zinc accumulation, and K+ uptake, while it resulted in the lowest Na+ and Na+/K+ ratio, especially under the highest saline-stress treatment. Thus, we concluded that seed priming with combined ZnO NPs and EBL can effectively mitigate the saline-stress-mediated decline in the morphological, physiological, and biochemical traits of maize.

Saline stress is one of the most critical abiotic stress factors that can lessen crops’ productivity. However, emerging nanotechnology, nano-fertilizers, and developing knowledge of phytochromes can potentially mitigate the negative effects of saline stress on seed germination. Therefore, the aim of this study was to investigate the effects of seed priming either with zinc oxide nanoparticles (ZnO-NPs; 50 and 100 mg L−1) or 24-epibrassinolide (EBL; 0.2 and 0.4 μM) and their combinations on maize (Zea mays L.) grains sown in salt-stressed soil (50 and 100 mM NaCl). Saline stress treatments significantly affected all germination traits and chemical analysis of seeds as well as α-amylase activity. Compared to un-primed seeds, seed priming with ZnO-NPs or EBL and their combinations significantly increased the cumulative germination percentage, germination energy, imbibition rate, increase in grain weight, K+ content, and α-amylase activity, and significantly reduced germination time, days to 50% emergence, Na+ uptake, and Na+/K+ ratio of maize sown in salt-stressed-soil (50 or 100 mM NaCl). The combination of 100 mg ZnO-NPs L−1 + 0.2 μM EBL resulted in the highest improvements for most of the studied traits of maize seeds sown in salt-stressed soil in comparison to all other individual and combined treatments.

Based on the massive production of cow and poultry manures, farmers in Saudi Arabia are moving towards the application of organic fertilizers in their farms. Therefore, the present work was conducted to study the response of soil and selected vegetable crops to poultry and cow manures, using ground data and Landsat-8 and Hyperion images. The studied vegetable crops are cabbage, cauliflower, broccoli, and lettuce. A total of 100 t ha−1 organic manures were applied as a pre-planting treatment. A 12.5 ha field in Tawdeehiya Farms, 200 km southeast of Riyadh, was earmarked for this study. The field was divided into sectors cultivated with the above-mentioned vegetable crops. Soil characteristics, including the soil pH, the electric conductivity (EC), the nitrogen (N), the phosphorus (P) and the potassium (K), were examined before the application of manures and 25 days after the transplanting process. Observations on crops chlorophyll content, number of leaves, the diameter of merchantable products and yield were also investigated. Furthermore, the relationship between the crop performance and yield was investigated through the satellite images generated vegetation indices (VIs). This study revealed the better performance of poultry manure compared to cow manure in terms of development and production parameters of the experimental crops. Dynamics of the chlorophyll content across the crop growth period revealed that all the tested crops responded significantly (R2 = 0.69; P = 0.001) to the poultry manure treatments. Among the tested crops, the chlorophyll content, curd or head sizes and crop yields were quite better in poultry manure applied plots. The investigation of crop yield was significant with poultry manure (R2 = 0.64; P = 0.001) than cow manure (R2 = 0.57; P = 0.001) using the OSAVI and mNDVI, respectively. Keywords: Poultry manure, Cow manure, Satellite images, Vegetation indices, Vegetable crops

Successfully evaluating and improving the salt tolerance of genotypes requires an appropriate analysis tool to allow simultaneous analysis of multiple traits and to facilitate the ranking of genotypes across different growth stages and salinity levels. In this study, we evaluate the salt tolerance of 56 recombinant inbred lines (RILs) in the presence of salt-tolerant and salt-sensitive control genotypes using multivariate analysis of plant dry weight, measured at 75 (PDW-75) and 90 (PDW-90) days from sowing, biological yield (BY), grain yield (GY), and their salt tolerance indices (STIs). All RILs and genotypes were evaluated under the control and 15 dS m−1 for two consecutive years (2019/2020 and 2020/2021). Results showed significant main effects of salinity and genotype as well as their interactions on four plant traits. Significant genotypic differences were also found for all calculated STIs. STIs exhibited moderate to strong relationships with the four plant traits when measured under either the control or salinity conditions and between each other. The principal component analysis (PCA) showed that the most variation among all analyzed variables was explained by the first two PCs, with the PC1 and PC2 explained at 61.8–71.8% and at 28.0–38.2% of the total variation, respectively. The PC1 had positive and strong correlations with the four plant traits measured under salinity conditions and STI, YI, REI, SWPI, MRPI, MPI, GMPI, and HMPI. The PC2 had strong correlations with BY and GY measured under the control conditions and SSI, TOL, RSE, and YSI. The PC1 was able to identify the salt-tolerant genotypes, while the PC2 was able to isolate the salt-sensitive ones. Cluster analysis based on multiple traits organized 64 genotypes into four groups varied from salt-tolerant to salt-sensitive genotypes, with the salt-tolerant group attaining higher value for plant traits under salinity conditions and the STIs related to the PC1. In conclusion, the use of multivariate analysis together with the STIs that evaluated the performance of genotypes under contrasting environmental conditions will help breeders to distinguish salt-tolerant genotypes from salt-sensitive ones, even at the early growth stages of plant development.

Understanding the spatial pattern of soil chemical properties along with the topologic indicators is essential for site-specific agriculture management. A study was conducted on a 50 ha field to investigate the effect of selected topographic indicators, including elevation (DEM), slope (SL), flow accumulation (FA) and Topographic Wetness Index (TWI) on forage crop production. The soil samples and yield data were obtained from the field inventory. Topographical parameters of elevation and slope were estimated with the use of a real-time kinematic global positioning system (RTK-GPS), and then the DEM was generated. The collected soil samples were analyzed for pH, EC, nitrogen and soil organic carbon. Sentinel-2 images were for the creation of yield maps of alfalfa and Rhodes grass. Subsequently, on the basis of DEM, the generated elevation, slope and FA model were then compared with the yield and soil chemical properties. Statistical analysis revealed that the SL, FA and TWI, which are associated with water distribution, were significantly related to crop yields. The FA showed a medium-to-non-significant correlation with the productivity of both alfalfa (R2 = 0.586; p = 0.015) and Rhodes grass (R2 = 0.578; p = 0.01). A significant inverse correlation was recorded between the SL and the yield of both crops (R2 = −0.591 to −0.617; p = 0.01). The yield map revealed that the majority of the area (37.56%) of the experimental field was occupied by the medium-yield class, followed by the high-yield class (33.03%).

Increasing demand for food, climate change, and other human interventions are leading to significant increases in water consumption by the agricultural sector. This requires rationalizing the water used for the production of agricultural crops through improved irrigation management practices. Therefore, this study aimed to estimate the water footprint (WF) of onion (Allium cepa L.) and carrot (Daucus carota) crops using the CROPWAT model and the SSEB (Simplified Surface Energy Balance) algorithm. Experiments were carried out at two center-pivot irrigated fields belonging to Tawdeehiya Commercial Farms in the southeastern region of the Riyadh governorate, Saudi Arabia. Individual bands and vegetation indices (VIs) were retrieved from Sentinel-2 satellite data, including the normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), optimized soil adjusted vegetation index (OSAVI), renormalized difference vegetation index (RDVI), and enhanced vegetation index (EVI), and the land surface temperatures (LST) extracted from Landsat-8 data were used to estimate crop productivity (CP), crop water use (CWU) (i.e., evapotranspiration—ETa), and crop WF. Crop growth/phenology stages and georeferenced biophysical parameters were recorded during the growth period, and crop yield samples were collected randomly from predetermined sampling locations. It was found that the NIR band was appropriate for predicting onion yield (R2 = 0.68; p > F = 0.02) and carrot yield (R2 = 0.77; p > F = 0.02). The results also showed the feasibility of using the RDVI and EVI to estimate the yields of onion and carrot crops, with bias values of 15% and –17%, respectively. The CWU has also been successfully estimated using the SSEB algorithm, with an overall accuracy of 89%. The SSEB-estimated CWU was relatively high compared to the applied amounts by 10.6% (onions) and 12.6% (carrots). Finally, the crop WF was successfully estimated at 312 m3 t−1 and 230 m3 t−1 for carrots and onions, respectively, with an overall accuracy of 71.11%. The outcomes of this study can serve as a reference for crop irrigation management practices in the study region and areas with similar environmental conditions.

Ensuring food security with limited water resources in arid countries requires urgent development of innovative water-saving strategies. This study aimed to investigate the effects of various tillage and mulching practices on soil water storage (SWS), growth, production, irrigation water use efficiency (IWUE), and water productivity (WP) of wheat under full (FL) and limited (LM) irrigation regimes in a typical arid country. The tillage practices comprised the conventional tillage (CT) and reduced tillage (RT), each with five mulching treatments (MT), including non-mulched (NM), plastic film mulch (PFM), wheat straw mulch (WSM), palm residues mulch (PRM), and a mixture of wheat straw and palm residues at 50/50 ratio (MM). Results showed higher SWS at different measured time points in CT than RT at 20–40 cm, 40–60 cm, and 0–60 cm soil depth under FL regime, and at 40–60 cm under LM regime, while the opposite was observed at 0–20 cm and 20–40 cm soil depth under LM regime. SWS at different soil depths under MT, in most cases, followed the order of PFM > PRM ≈ MM > WSM > NM under FL, and PFM ≈ PRM > MM > WSM > NM under LM regimes. No significant differences were observed for traits related to growth between CT and RT, but RT increased the traits related to yield, IWUE, and WP by 5.9–11.6% than did CT. PFM and PRM or PRM and MM showed the highest values for traits related to growth or yield, IWUE, and WP, respectively. No significant differences in all traits between CT and RT under the FL regime were observed, however, RT increased all traits by 8.0–18.8% than did CT under the LM regime. The yield response factor (Ky) based on plant dry weight (KyPDW) and grain yield (KyGY) under RT was acceptable for four MT, while KyGY under CT was acceptable only for PRM, as the Ky values in these treatments were 2 range 0.57 to 0.92), while they exhibited a second order polynomial and moderate correlation with IWUE and WP (R2 range 0.29 to 0.54). Overall, combining RT with plant residue mulching, particularly using the readily available palm residues in sufficient amount is a feasible and sustainable water-saving strategy for enhancing wheat yield and WP in irrigated arid countries, such as Saudi Arabia.

Innovations in water-saving cultivation strategies are urgently needed to achieve high yield and elevated water use efficiency (WUE) simultaneously in arid regions with limited water resources. Here, we conducted a two-year field study to compare the impacts of eight combinations of planting patterns (PPs) and mulching on the soil water content (SWC) in the top 60 cm soil layer, the growth, the yield, and the WUE of wheat under two irrigation rates (1.00 and 0.50 ET). These combinations included three conventional flat planting (CF) patterns, including CF without mulch (CFNM), with plastic film (CFPM), and with wheat straw mulch (CFSM); three raised-bed planting (RB) patterns, including RB without mulch (RBNM), with plastic film (RBPM), and wheat straw (RBSM) mulch; and two ridge–furrow planting (RF) patterns, including RF without mulch (RFNM) and with plastic film mulch (RFPM). The results showed that the tested treatments affected the SWC at different depths under both irrigation rates. Compared with the two non-mulched treatments under 0.50 ET, the SWC of the three PPs with plastic film and the two PPs with wheat straw mulching were significantly higher before irrigation by 14.4–22.0% and 6.9–17.2% at 0–20 cm soil depth, 16.4–29.0% and 6.6–14.9% at 20–40 cm soil depth, and 3.3–34.8% and 3.4–14.5% at 40–60 cm soil depth, respectively. All measured wheat parameters, except harvest index, were significantly affected by the interaction between irrigation rate and PPs. The highest values for plant dry weight (PDW), yield components, grain yield (GY), and WUE under 1.00 ET were obtained in the two PPs with wheat straw mulch, while the three PPs with plastic film showed the highest values of these parameters under 0.50 ET. The yield response factor (Ky) based on PDW was acceptable for all PPs mulched with plastic film and wheat straw as well as for RFNM, while Ky based on GY was acceptable only for the PPs mulched with plastic film and for RFNM, as the Ky values of these PPs were less than 1 under 0.50 ET. The SWC at different depths exhibited quadratic and nonsignificant relationships with all parameters under 1.00 ET, while these relationships were linear and strong under 0.50 ET, with a few exceptions. Overall, we conclude that combining any PPs with plastic film mulching could be used as a feasible and effective strategy for obtaining high wheat yield and WUE in the irrigated and arid agroecosystem.

Although plant chlorophyll (Chl) is one of the important elements in monitoring plant stress and reflects the photosynthetic capacity of plants, their measurement in the lab is generally time- and cost-inefficient and based on a small part of the leaf. This study examines the ability of canopy spectral reflectance data for the accurate estimation of the Chl content of two wheat genotypes grown under three salinity levels. The Chl content was quantified as content per area (Chl area, μg cm−2), concentration per plant (Chl plant, mg plant−1), and SPAD value (Chl SPAD). The performance of spectral reflectance indices (SRIs) with different algorithm forms, partial least square regression (PLSR), and stepwise multiple linear regression (SMLR) in estimating the three units of Chl content was compared. Results show that most indices within each SRI form performed better with Chl area and Chl plant and performed poorly with Chl SPAD. The PLSR models, based on the four forms of SRIs individually or combined, still performed poorly in estimating Chl SPAD, while they exhibited a strong relationship with Chl plant followed by Chl area in both the calibration (Cal.) and validation (Val.) datasets. The SMLR models extracted three to four indices from each SRI form as the most effective indices and explained 73–79%, 80–84%, and 39–43% of the total variability in Chl area, Chl plant, and Chl SPAD, respectively. The performance of the various predictive models of SMLR for predicting Chl content depended on salinity level, genotype, season, and the units of Chl content. In summary, this study indicates that the Chl content measured in the lab and expressed on content (μg cm−2) or concentration (mg plant−1) can be accurately estimated at canopy level using spectral reflectance data.

An area of growing interest in wheat-breeding programs for abiotic stresses is the accurate and expeditious phenotyping of large genotype collections using nondestructive hyperspectral sensing tools. The main goal of this study was to use data from canopy spectral signatures (CSS) in the full-spectrum range (400–2500 nm) to estimate and predict the plant biomass dry weight at booting (BDW-BT) and anthesis (BDW-AN) growth stages, and biological yield (BY) of 64 spring wheat germplasms exposed to 150 mM NaCl using 13 spectral reflectance indices (SRIs, consisting of seven vegetation-related SRIs and six water-related SRIs) and partial least squares regression (PLSR). SRI and PLSR performance in estimating plant traits was evaluated during two years at BT, AN, and early milk grain (EMG) growth stages. Results showed significant genotypic differences between the three traits and SRIs, with highly significant two-way and three-way interactions between genotypes, years, and growth stages for all SRIs. Genotypic differences in CSS and the relationships between the three traits and a single wavelength over the full-spectrum range depended on the growth stage. Water-related SRIs were more strongly correlated with the three traits compared with vegetation-related SRIs at the BT stage; the opposite was found at the EMG stage. Both types of SRIs exhibited comparable associations with the three traits at the AN stage. Principal component analysis indicated that it is possible to assess plant biomass variations at an early stage (BT) through published and modified SRIs. SRIs coupled with PLSR models at the BT stage exhibited good prediction capacity of BDW-BT (57%), BDW-AN (82%), and BY (55%). Overall, results demonstrated that the integration of SRIs and multivariate models may present a feasible tool for plant breeders to increase the efficiency of the evaluation process and to improve the genetics for salt tolerance in wheat-breeding programs.

The incorporation of stress tolerance indices (STIs) with the early estimation of grain yield (GY) in an expeditious and nondestructive manner can enable breeders for ensuring the success of genotype development for a wide range of environmental conditions. In this study, the relative performance of GY for sixty-four spring wheat germplasm under the control and 15.0 dS m−1 NaCl were compared through different STIs, and the ability of a hyperspectral reflectance tool for the early estimation of GY and STIs was assessed using twenty spectral reflectance indices (SRIs; 10 vegetation SRIs and 10 water SRIs). The results showed that salinity treatments, genotypes, and their interactions had significant effects on the GY and nearly all SRIs. Significant genotypic variations were also observed for all STIs. Based on the GY under the control (GYc) and salinity (GYs) conditions and all STIs, the tested genotypes were classified into three salinity tolerance groups (salt-tolerant, salt-sensitive, and moderately salt-tolerant groups). Most vegetation and water SRIs showed strong relationships with the GYc, stress tolerance index (STI), and geometric mean productivity (GMP); moderate relationships with GYs and sometimes with the tolerance index (TOL); and weak relationships with the yield stability index (YSI) and stress susceptibility index (SSI). Obvious differences in the spectral reflectance curves were found among the three salinity tolerance groups under the control and salinity conditions. Stepwise multiple linear regressions identified three SRIs from each vegetation and water SRI as the most influential indices that contributed the most variation in the GY. These SRIs were much more effective in estimating the GYc (R2 = 0.64 − 0.79) than GYs (R2 = 0.38 − 0.47). They also provided a much accurate estimation of the GYc and GYs for the moderately salt-tolerant genotype group; YSI, SSI, and TOL for the salt-sensitive genotypes group; and STI and GMP for all the three salinity tolerance groups. Overall, the results of this study highlight the potential of using a hyperspectral reflectance tool in breeding programs for phenotyping a sufficient number of genotypes under a wide range of environmental conditions in a cost-effective, noninvasive, and expeditious manner. This will aid in accelerating the development of genotypes for salinity conditions in breeding programs.

A study was conducted to understand the potential of Landsat-8 in the estimation of gross primary production (GPP) and to quantify the productivity of maize crop cultivated under hyper-arid conditions of Saudi Arabia. The GPP of maize crop was estimated by using the Vegetation Photosynthesis Model (VPM) utilizing remote sensing data from Landsat-8 reflectance (GPPVPM) as well as the meteorological data provided by Eddy Covariance (EC) system (GPPEC), for the period from August to November 2015. Results revealed that the cumulative GPPEC for the entire growth period of maize crop was 1871 g C m−2. However, the cumulative GPP determined as a function of the enhanced vegetation index – EVI (GPPEVI) was 1979 g C m−2, and that determined as a function of the normalized difference vegetation index – NDVI (GPPNDVI) was 1754 g C m−2. These results indicated that the GPPEVI was significantly higher than the GPPEC (R2 = 0.96, P = 0.0241 and RMSE = 12.6%). While, the GPPNDVI was significantly lower than the GPPEC (R2 = 0.93, P = 0.0384 and RMSE = 19.7%). However, the recorded relative error between the GPPEC and both the GPPEVI and the GPPNDVI was −6.22% and 5.76%, respectively. These results demonstrated the potential of the landsat-8 driven VPM model for the estimation of GPP, which is relevant to the productivity and carbon fluxes.

A study on six 50 ha agricultural fields was conducted to investigate the effect of conservation tillage practices on the long-term (1990-2016) changes in the soil organic carbon (SOC) content of the topsoil layers (0-10 cm) of agricultural fields. The experimental fields were selected from the 49 fields of the Tawdeehiya Arable Farm (TAF), located 200 kilometers southeast of Riyadh, the capital city of the Kingdom of Saudi Arabia. Data sets from laboratory determined SOC and the corresponding Landsat images generated vegetation indices, namely, the Normalized Difference Vegetation Index (NDVI) and the Bare Soil Index (BSI), were utilized for the prediction of SOC using multivariate regression techniques. Long-term changes in the SOC content of the experimental fields, as a result of different tillage practices, were also studied. The developed SOC prediction models exhibited high accuracy indicated by R2 values ranging from 0.73 to 0.85, RMSE values of 0.34 to 0.85 g kg-1 and P-values of less than 0.0001. The cross-validation results (R2 of 0.61-0.70, RMSE value of 0.34-0.85 g kg-1 and P-values of less than 0.0001) confirmed the high accuracy of the developed SOC prediction models. Results also revealed that the change in the SOC content was clearly associated with soil tillage practices. On the average, 76% of the all agricultural fields in the experimental farm showed a decrease of up to 24 g kg-1 in their SOC content after 10 years (1990-2000) of continuous conventional tillage practices. On the other hand, an average increase of up to 37 g kg-1 in the SOC content was observed in 88% of the studied fields at the end of the study period (2016), where conservation tillage was a continous and consistent practice in the experimental farm.

The crop Water Footprint (WF) can provide a comprehensive knowledge of the use of water through the demarcation of the amount of the water consumed by different crops. The WF has three components: green (WFg), blue (WFb) and grey (WFgr) water footprints. The WFg refers to the rainwater stored in the root zone soil layer and is mainly utilized for agricultural, horticultural and forestry production. The WFb, however, is the consumptive use of water from surface or groundwater resources and mainly deals with irrigated agriculture, industry, domestic water use, etc. While the WFgr is the amount of fresh water required to assimilate pollutants resulting from the use of fertilizers/agrochemicals. This study was conducted on six agricultural fields in the Eastern region of Saudi Arabia, during the period from December 2015 to December 2016, to investigate the spatiotemporal variation of the WF of silage maize and carrot crops. The WF of each crop was estimated in two ways, namely agro-meteorological (WFAgro) and remote sensing (WFRS) methods. The blue, green and grey components of WFAgro were computed with the use of weather station/Eddy covariance measurements and field recorded crop yield datasets. The WFRS estimated by applying surface energy balance principles on Landsat-8 imageries. However, due to non-availability of Landsat-8 data on the event of rainy days, this study was limited to blue component (WFRS-b). The WFAgro of silage maize was found to range from 3545 m3 t-1 to 4960 m3 t-1; on an average, the WFAgro-g, WFAgro-b, and WFAgro-gr are composed of < 1%, 77%, and 22%, respectively. In the case of carrot, the WFAgro ranged between 297 m3 t-1 and 502 m3 t-1. The WFAgro-g of carrot crop was estimated at

Understanding the temporal and spatial variability in a crop yield is viewed as one of the key steps in the implementation of precision agriculture practices. Therefore, a study on a center pivot irrigated 23.5 ha field in Saudi Arabia was conducted to assess the variability in alfalfa yield using Landsat-8 imagery and a hay yield monitor data. In addition, the study was designed to also explore the potential of predicting the alfalfa yield using vegetation indices. A calibrated yield monitor mounted on a large rectangular hay baler was used to measure the actual alfalfa yield for four alfalfa harvests performed in the period from October 2013 to May 2014. A total of 18 Landsat-8 images, representing different crop growth stages, were used to derive different vegetation indices (VIs). Data from the yield monitor was used to generate yield maps, which illustrated a definite spatial variation in alfalfa yield across the experimental field for the four studied harvests as indicated by the high spatial correlation values (0.75 to 0.97) and the low P-values (4.7E-103 to 8.9E-27). The yield monitor-measured alfalfa actual yield was compared to the predicted yield form the Vis. Results of the study showed that there was a correlation between actual and predicted yield. The highest correlations were observed between actual yield and the predicted using NIR reflectance, SAVI and NDVI with maximum correlation coefficients of 0.69, 0.68 and 0.63, respectively.

Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Therefore, remote sensing and GIS techniques were employed, in this study, to predict potato tuber crop yield on three 30 ha center pivot irrigated fields in an agricultural scheme located in the Eastern Region of Saudi Arabia. Landsat-8 and Sentinel-2 satellite images were acquired during the potato growth stages and two vegetation indices (the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI)) were generated from the images. Vegetation index maps were developed and classified into zones based on vegetation health statements, where the stratified random sampling points were accordingly initiated. Potato yield samples were collected 2-3 days prior to the harvest time and were correlated to the adjacent NDVI and SAVI, where yield prediction algorithms were developed and used to generate prediction yield maps. Results of the study revealed that the difference between predicted yield values and actual ones (prediction error) ranged between 7.9 and 13.5% for Landsat-8 images and between 3.8 and 10.2% for Sentinel-2 images. The relationship between actual and predicted yield values produced R2 values ranging between 0.39 and 0.65 for Landsat-8 images and between 0.47 and 0.65 for Sentinel-2 images. Results of this study revealed a considerable variation in field productivity across the three fields, where high-yield areas produced an average yield of above 40 t ha-1; while, the low-yield areas produced, on the average, less than 21 t ha-1. Identifying such great variation in field productivity will assist farmers and decision makers in managing their practices.