Mathematical models have been widely employed for the simulation of growth dynamics of annual crops, thereby performing yield prediction, but not for fruit tree species such as jujube tree (Zizyphus jujuba).  The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter.  The model was established using data collected from dedicated field experiments performed in 2016–2018.  Simulated growth dynamics of dry weights of leaves, stems, fruits, total biomass and leaf area index (LAI) agreed well with measured values, showing root mean square error (RMSE) values of 0.143, 0.333, 0.366, 0.624 t ha^–1 and 0.19, and R² values of 0.947, 0.976, 0.985, 0.986 and 0.95, respectively.  Simulated phenological development stages for emergence, anthesis and maturity were 2, 3 and 3 days earlier than the observed values, respectively.  In addition, in order to predict the yields of trees with different ages, the weight of new organs (initial buds and roots) in each growing season was introduced as the initial total dry weight (TDWI), which was calculated as averaged, fitted and optimized values of trees with the same age.  The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI.  The modelling performance was significantly improved when it considered TDWI integrated with tree age, showing good global (R²≥0.856, RMSE≤0.68 t ha^–1) and local accuracies (mean R²≥0.43, RMSE≤0.70 t ha^–1).  Furthermore, the optimized TDWI exhibited the highest precision, with globally validated R² of 0.891 and RMSE of 0.591 t ha^–1, and local mean R² of 0.57 and RMSE of 0.66 t ha^–1, respectively.  The proposed model was not only verified with the confidence to accurately predict yields of jujube, but it can also provide a fundamental strategy for simulating the growth of other fruit trees.

 

Crop harvesting and residue removal from croplands often result in imbalanced biogeochemical cycles of carbon and nutrients in croplands, putting forward an austere challenge to sustainable agricultural production.  As a beneficial element, silicon (Si) has multiple eco-physiological functions, which could help crops to acclimatize their unfavorable habitats.  Although many studies have reported that the application of Si can alleviate multiple abiotic and biotic stresses and increase biomass accumulation, the effects of Si on carbon immobilization and nutrients uptake into plants in croplands have not yet been explored.  This review focused on Si-associated regulation of plant carbon accumulation, lignin biosynthesis, and nutrients uptake, which are important for biogeochemical cycles of carbon and nutrients in croplands.  The tradeoff analysis indicates that the supply of bioavailable Si can enhance plant net photosynthetic rate and biomass carbon production (especially root biomass input to soil organic carbon pool), but reduce shoot lignin biosynthesis.  Besides, the application of Si could improve uptake of most nutrients under deficient conditions, but restricts excess uptake when they are supplied in surplus amounts.  Nevertheless, Si application to crops may enhance the uptake of nitrogen and iron when they are supplied in deficient to luxurious amounts, while potassium uptake enhanced by Si application is often involved in alleviating salt stress and inhibiting excess sodium uptake in plants.  More importantly, the amount of Si accumulated in plant positively correlates with nutrients release during the decay of crop biomass, but negatively correlates with straw decomposability due to the reduced lignin synthesis.  The Si-mediated plant growth and litter decomposition collectively suggest that Si cycling in croplands plays important roles in biogeochemical cycles of carbon and nutrients.  Hence, scientific Si management in croplands will be helpful for maintaining sustainable development of agriculture.