Search

Growing degree days (GDDs) and leaf area index (LAI) greatly influence the growth and yield of many crops grown in arid regions. Therefore, variation in LAI due to GDD can provide a theoretical basis for predicting crop growth, water consumption, plant development, and yield in arid agriculture via the development of mathematical growth models. This study described the relationship between plant biomass production and variation in LAI due to GDD in arid regions under different types of irrigation (fresh water and saline water) and soils amended with different substances (manure+sandy soil, compost+sandy soil, clay+sandy soil, and sandy soil). Mathematical models for LAI were established for GDDs. In addition, different water quality irrigation techniques were used as independent variables to calculate the LAI of halophytic plants (Hedysarum scoparium) in arid regions under different soil amendment treatments. Furthermore, mathematical models for plant biomass production were developed by using the LAI and GDDs. For this purpose, Logistic, Gaussian, modified Gaussian, and Cubic polynomial models were used. Modified Gaussian and Cubic polynomial models are the best among all developed models, but Cubic polynomial models are more suitable among all developed models because of their simple quadratic equations that can be solved by using the first derivative. It was observed that with increased salt concentration in the irrigation water, the growth of per plant production decreased. However, soil amendments like manure and compost enhance salt tolerance against salt stress and enable plants to sustain their growth. Furthermore, Hedysarum scoparium attains maximum LAI when its GDD is about 1117.5 °C under both irrigation regimes and in all soil amendment treatments. It was concluded that these predicted mathematical models can provide crucial insights for enhancing production in arid regions by using eco-friendly soil amendments to improve water use efficiency across diverse types of water irrigation. [ABSTRACT FROM AUTHOR]

The morphological adjustments of euhalophytes are well-known to be influenced by the soil-soluble salt variation; however, whether and how these changes in morphological traits alter the biomass allocation pattern remains unclear, especially under different NaCl levels. Therefore, an allometric analysis was applied to investigate the biomass allocation pattern and morphological plasticity, and the carbon (C), nitrogen (N), and phosphorus (P) stoichiometric characteristics of the euhalophyte Suaeda Salsa (S. salsa) at the four soil-soluble salt levels of no salt (NS), light salt (LS), moderate salt (MS), and heavy salt (HS). The results showed that soil-soluble salts significantly change the biomass allocation to the stems and leaves (p < 0.05). With the growth of S. salsa, the NS treatment produced a downward leaf mass ratio (LMR) and upward stem mass ratio (SMR); this finding was completely different from that for the salt treatments. When S. salsa was harvested on the 100th day, the HS treatment had the highest LMR (61%) and the lowest SMR (31%), while the NS treatment was the opposite, with an LMR of 44% and an SMR of 50%. Meanwhile, the soil-soluble salt reshaped the morphological characteristics of S. salsa (e.g., root length, plant height, basal stem diameter, and leaf succulence). Combined with the stoichiometric characteristics, N uptake restriction under salt stress is a vital reason for inhibited stem growth. Although the NS treatment had the highest biomass (48.65 g root box−1), the LS treatment had the highest salt absorption (3.73 g root box−1). In conclusion, S. salsa can change its biomass allocation pattern through morphological adjustments to adapt to different saline–alkali habitats. Moreover, it has an optimal biological desalting effect in lightly saline soil dominated by NaCl. [ABSTRACT FROM AUTHOR]

The objective of this study is to produce multi-criteria model for the dry weight prediction of Wedelia trilobata under flooding and nitrogen conditions. Plants of W. trilobata were grown in a greenhouse, and treatments were given for two months. Growth parameters of 60 plants were used to build a numerical model. The neural network model was built using Quasi-Newton approaches that containing Broyden-fletcher-goldfarb-shanno gradient (BFGS) learning algorithm, multilayer perceptron (MLP) training algorithm and sigmoid axon transfer function along with 10 neurons at the input network, 9 neurons in the hidden layer, and 1 neuron in the output layer (10-9-1). The selection and validation of the best predictor model were based on lower values of errors and higher value of R². The selected model had a higher values of R² = 0.90 and lower values of errors i.e (relative approximate error, RAE = 0.004, root mean square error, RMS = 0.027, mean absolute error, MAE = 0.004, mean absolute percentage error, MAPE = 0.013). Moreover, the highest rank 1 was obtained for leaf area during sensitivity analysis followed by water potential and photosynthesis ranked 2rd and 3th, respectively. The constructed model of W. trilobata under flooding and nitrogen conditions is the new feature in the management of invasive plant species and gives direction to control its spread. [ABSTRACT FROM AUTHOR]

Plant height (PH) plays a crucial role in determining per-plant growth and biomass production. Various characteristics of PH, along with the formulation of mathematical growth models, can provide a theoretical yield or biomass production based on water quality, fruit quality, and yields. The aim of this study was to investigate the relationship between PH and biomass per-plant production of two fodder crops (Cluster bean and Sesbania) under different water quality irrigation parameters in the Thar desert of Pakistan. Universal models of PH were established in which growing degree days (GDDs) and different water quality irrigation techniques have been applied as independent variables to calculate the maximum plant height of both of these crops. For this purpose, the logistic growth model, Gaussian growth model, modified Gaussian growth model, and Cubic polynomial growth model were used. Furthermore, universal biomass per plant production models have been developed for both crops, between biomass per plant, GDDs, and PH. However, among all these developed models, the modified Gaussian and Cubic polynomial growth models produced the best results. The Cubic polynomial model has meaningless parameters that make the model not very accurate, so the modified Gaussian growth model is the best among all models. Furthermore, the relationship between biomass per plant and different water qualities was established using Michaelis–Menten equations for both crops. It was observed that an increase in salt concentration within the water quality led to a decline in biomass per plant, indicating a negative linear relationship between these factors. The growth of Cluster bean and Sesbania ceased when the electrical conductivity (EC) reached or exceeded 12.34 ds/m and 11.51 ds/m, respectively. Furthermore, the results show that Cluster bean and Sesbania have the maximum plant height under brackish water irrigation when the GDD is at 1500 °C, while in freshwater irrigation, the maximum plant height of Sesbania and Cluster bean was observed when the GDD is at 1444 °C and 1600 °C. It was concluded that these developed mathematical models can provide crucial insights for enhancing production in desert conditions by improving water use efficiency across diverse irrigation water qualities. [ABSTRACT FROM AUTHOR]

Under the sufficient nitrogen supply, it is of great significance to investigate the law of biomass allocation, root morphological traits, and the salt absorption capacity of euhalophytes to evaluate their biological desalination in saline soil. Although the curvilinear responses of biomass accumulation and root morphology in response to soil salinity have been recognized, these perceptions are still confined to the descriptions of inter-treatment population changes and lack details on biomass allocation in organs at an individual level. In this study, Suaeda salsa was grown in root boxes across a range of soil salt levels. The study showed that their growth and development were significantly affected by soil soluble salts. The law of biomass allocation was described as follows: increased soil soluble salts significantly increased the leaf mass ratio and decreased the stem mass ratio, and slightly increased the root mass ratio among treatments. For individuals at each treatment, leaf mass ratio > stem mass ratio > root mass ratio, except in the control treatment at the flower bud and fruit stages. Biomass responses of the control treatment indicated that salt was not rigorously required for Suaeda salsa in the presence of an adequate nitrogen supply, as verified by the correlation between biomass, nitrogen, and soil soluble salt. Salt could significantly inhibit the growth of Suaeda salsa (P<0.01), whereas nitrogen could significantly promote its growth (P<0.01). Root morphology in response to soil soluble salts showed that salt acquisition by the root was highest at a salt level of 0.70%, which corresponds to light saline soil. Consequently, we conclude that phytodesalination by Suaeda salsa was optimal in the light saline soil, followed by moderate saline soil., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Guo, Tian, Zhao, Zhang and Mai.)