Response of leaf photosynthesis, chlorophyll content and yield of hydroponic tomatoes to different water salinity levels.

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.

Exogenous Application of 24-Epibrassinolide Confers Saline Stress and Improves Photosynthetic Capacity, Antioxidant Defense, Mineral Uptake, and Yield in Maize.

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.

Utilizing spectral vegetation indices for yield assessment of tomato genotypes grown in arid conditions.

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.

Investigating the response of soil and vegetable crops to poultry and cow manure using ground and satellite data.

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.

Employment of GIS techniques to assess the long-term impact of tillage on the soil organic carbon of agricultural fields under hyper-arid conditions.

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.

Impact of raking and baling patterns on alfalfa hay dry matter and quality losses.

A field study was conducted to investigate the impact of different patterns of raking and baling operations on the dry matter (DM) and quality losses of the produced alfalfa (Medicago sativa) hay. The experimental work was carried out on a 50 ha center pivot irrigated alfalfa field in a commercial farm located in the Eastern Region of Saudi Arabia. Raking operation was performed following two patterns corresponding to the direction of mowing operation, namely, Raking-I in the same direction of mowing (Mowing→  and Raking→) and Raking-II opposite to the direction of mowing (Mowing→ and Raking←). The baling operation; however, was performed following four patterns corresponding to the directions of both mowing and raking operations, namely, Baling-I (Mowing→, Raking→ and Baling→), Baling-II (Mowing→, Raking→ and Baling←), Baling-III (Mowing→, Raking← and Baling→) and Baling-IV (Mowing→, Raking← and Baling←). Results showed that cumulative DM losses in alfalfa hay yield of 30.93% occurred during the harvesting operations. Out of which, raking induced the most DM losses of 985.22 kg ha-1 (59.66% of the total DM losses and 17.35% of the total hay yield). However, the least DM losses were observed during the baling operation and were estimated at 175.81 kg ha-1 (10.22% of the total DM losses and 3.10% of the total hay yield). Raking opposite to the direction of mowing reduced the DM losses by 130.17 kg ha-1 (7.88% of the total DM losses and 2.29% of the total hay yield) compared to that with the direction of mowing. Results also indicated that out of the 21.04% losses in the total crude protein (CP) content of the produced alfalfa hay, 10.91% occurred during the raking operation. However, the baling operation induced the least amount of CP losses (only 2.32% of the total CP). Overall, the best results in terms of alfalfa hay quality and quantity losses were achieved with Baling-III, where the lowest DM losses (2.01% of the total hay yield) and the lowest CP losses (1.44% of the total CP) were recorded.

Utilization of Landsat-8 data for the estimation of carrot and maize crop water footprint under the arid climate of Saudi Arabia.

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 <1%, while WFAgro-b and WFAgro-gr was 67% and 32%, respectively. The WFAgro-b is occupied as a major portion in WF of silage maize (77%) and carrot (68%) crops. This is due to the high crop water demand combined with a very erratic rainfall, the irrigation is totally provided using groundwater delivered by center pivot irrigation systems. On the other hand, the WFRS-b estimated using Landsat-8 data was varied from 276 (±73) m3 t-1 (carrot) and 2885 (±441) m3 t-1 (silage maize). The variation (RMSE) between WFRS-b and WFAgro-b was about 17% and 14% for silage maize and carrot crops, respectively.

Estimation of gross primary production of irrigated maize using Landsat-8 imagery and Eddy Covariance data.

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.

Assessing the Spatial Variability of Alfalfa Yield Using Satellite Imagery and Ground-Based Data.

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.

Prediction of Potato Crop Yield Using Precision Agriculture Techniques.

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.