Effect of Digestate and Biochar Amendments on Photosynthesis Rate, Growth Parameters, Water Use Efficiency and Yield of Chinese Melon (Cucumis melo L.) under Saline Irrigation

Despite the recent interest in biochar and digestate as soil amendments for improving soil quality and increasing crop production, there is inadequate knowledge of the effect of the combination of biochar and digestate, particularly under saline irrigation conditions. A pot experiment with Chinese melon was conducted in a greenhouse, biochar (5%) and digestate (500 mL/pot) were used with and without the recommended mineral NPK (Nitrogen, Phosphorus and Potassium) fertilizer dose (120-150-150 Kg ha−1). The plants were irrigated with tap water (SL0) and 2 dS/m (SL1) NaCl solution. The growth, photosynthesis rate, water use efficiency (WUE) and yield of Chinese melon were affected positively when biochar was combined with digestate amendment, particularly under saline irrigation water with and without mineral NPK fertilizer. The maximum yield under normal water was obtained by digestate (SL0: 218.87 t ha−1) and biochar amendment combined with digestate (SL1: 118.8 t ha−1) under saline water. The maximum WUE values were noticed with the biochar and digestate combination under all water treatments (SL0: 32.2 t ha−1 mm−1 and SL1: 19.6 t ha−1 mm−1). It was concluded that digestate alone was more effective than the use of biochar, particularly with normal water. The combination of biochar with digestate had a significant effect on the Chinese melon growth, photosynthesis rate, water use efficiency and yield under saline irrigation, and it can be used as an alternative fertilizer for mineral NPK fertilizer

Efficiency of Two Models for Prediction of Exchangeable Sodium Percentage from Sodium Adsorption Ratio on Saline and Non Saline Soil

Abstract The relationships between soil physical and chemical properties play a key role in facilitating the measurement of soil properties, particularly Exchangeable Sodium percentage (ESP) measurement, which is often using laborious and time-consuming laboratory tests. The aim of this study is to investigate the efficiency of the United States Salinity Laboratory (USSL) model and the ESP-SAR model for prediction of exchangeable Sodium percentage (ESP) from Sodium Adsorption Ratio (SAR) on saline and non-saline soil samples. For this purpose, 23 soil samples were collected from the field of experiment, Jabal Awliya, south of Khartoum state, Sudan. Exchangeable Sodium Percentage (ESP) was estimated as a function of soil SAR in order to compare the predicted results with measured ESP using laboratory tests. The results show that on saline soil samples, the Standard Error of Mean (SEM) of predicted ESP obtained by USSL model and ESP-SAR model was (1.084) and (1.463) respectively. On non-saline soil samples, the Standard Error of Mean (SEM) of predicted ESP acquired by USSL model was (0.7034) and (0.6070) for ESP-SAR model. The statistical results indicated that USSL model has a good prediction on saline soil samples compared with ESP-SAR model. On non-saline soil samples, USSL model showed less prediction performance than ESP-SAR model. It can be concluded that the United States Salinity Laboratory model can be recommended on saline soil samples and ESP-SAR model is more reliable on non-saline soil samples

Modeling of Soil Exchangeable Sodium Percentage Function to Soil Adsorption Ratio on Sandy Clay Loam Soil, Khartoum- Sudan

An experiment was conducted at the Wadi Soba farm, Khartoum- Sudan. The aim of this study is to estimate the Exchangeable Sodium Percentage (ESP) function to Sodium Adsorption Ratio. In this study, linear regression model (ESP-SAR model) for predicting soil ESP from SAR was suggested. For this purpose, 30 soil samples were collected from the field of experiment, soil ESP was estimated from soil SAR in order to compare the predicted results with measured SAR using laboratory tests on saline and non- saline soil samples. The results show that on saline soil samples, the Standard Error of Mean (SEM) of predicted ESP obtained by ESP-SAR model was (0.9389) and the P-value was (0.0572). On non- saline soil samples, the Standard Error of Mean (SEM) of predicted ESP acquired by ESP-SAR model was (0.2920) and the P-value was (0.2628). The statistical results indicated that the linear regression model (ESP-SAR model), ESP= 0.84 × SAR + 2.17 with R2 = 0.7347 has a good performance in predicting soil ESP from SAR meanwhile the ESP-SAR model reflected more accuracy on non- saline soil samples and it can be recommended for both saline soil and non-saline soil samples. &nbsp

Variability in Some Soil Physical and Chemical Properties of Shambat Farm, Khartoum- Sudan

An experiment was conducted on the farm of the Faculty of Agricultural Studies, Sudan University of Science and Technology, this soil belongs to the Central Clay Plain of the Sudan which has been formed by alluvial deposit of the Nile, primarily of basaltic origin, and it consider largely as Vertisols. The objective of this study is to evaluate the variability in some physical and Chemical properties of soil under investigation in order to identify their spatial distribution to assist in designing land management and support agricultural production. For these purposes, some physical and Chemical properties at five sites across the farm have been investigated. The results indicated that the soils are variably affected by saline and sodic conditions. Non-saline, slightly saline, moderately saline sub soil and non-sodic to moderately sodic soils are found on the farm. Soil texture is clayey throughout, and hydraulic conductivity is very slow to slow .The whole of soil profile is compacted except at the surface layer, the average of soil bulk density is very high when the soil is dry. The soils under investigation are characterized by high water retention but rather narrow range of available moisture as noticed from the difference between the moisture retained between field capacity and wilting point. &nbsp

Effect of Irrigation Regimes and Soil Texture on the Potassium Utilization Efficiency of Rice

Understanding the effects of irrigation regime and soil texture on potassium-use efficiency (KUE) of rice (Oryza sativa. L) is essential for improving rice productivity. In this regard, experiments were conducted from July to October in 2016 and 2017 by using a randomized complete block design in a factorial arrangement with four replications. The rice plants were grown in three soils, with clay contents of 40%, 50%, and 60%, which were marked as S (40%), S (50%), and S (60%), respectively. For each soil type, irrigation regimes, namely, R (F, S100%), R (F, S90%), and R (F, S70%), were established by setting the lower limit of irrigation to 100%, 90%, and 70% of saturated soil water content, respectively, and the upper limit of irrigation with 30 mm of flooding water above the soil surface for all irrigation regimes. Results showed that the responses of the roots and shoots and the potassium accumulation (KA) and KUE of rice were significantly affected by the water regime and soil texture. In the same irrigation regime, increasing the soil clay content improved the K utilization of rice. Under the same soil type, R (F, S100%) was the optimal water management practice for growing rice. The R (F, S100%) S (60%) treatment presented the highest KUE, which was 56.4% in 2016 and 68.1% in 2017. The R (F, S70%) S (40%) treatment showed the lowest KUE, which was 13.8% in 2016 and 14.9% in 2017. These results enrich knowledge regarding the relationship among soil, water, and rice, and provide valuable insights on the effect of irrigation regime and soil texture on the KA and KUE of rice