Assessing environmental thresholds in relation to plant structure and nutritional value for improved maize calendar ensuring food security

Maize Grain Metabolite Profiling by NMR: Effects of Growing Year, Variety, and Cropping System

Considering that maize (Zea mays L.) is a staple food for a large segment of the population worldwide, many attempts have been made to improve the nutritional value of its grain and at the same time to achieve sustainable cropping systems. The present study aimed to characterize the composition and nutritional value of maize grain as influenced by cropping system, genetic background (variety), and growing year using untargeted NMR metabolomics. The composition of both water- (sugars and polyols, organic acids, and amino acids) and liposoluble metabolites (free and esterified fatty acids, sterols, and lipids) extracted from the maize grain was determined. Multivariate statistical analyses (PCA and ANOVA) pointed to the growing year and the variety as the most important random and fixed factors, respectively, influencing the metabolite profile. The samples were separated along PC1 and PC3 according to the growing year and the variety, respectively. A higher content of citric acid and diunsaturated fatty acids and a lower content of tyrosine, trigonelline, and monounsaturated fatty acids was observed in the organic with respect to the conventional variety. The effect of the cropping system was overwhelmed by the random effect of the growing year. The results provide novel knowledge on the influence of agronomic practices on maize micronutrient contents.

Modeling the feasibility of Se-rich corn cultivation in Se-deficient agricultural fields using random forest algorithm

Selenium constitutes an essential trace element for the human body. Moderate Se intake plays a pivotal role in preserving overall health. The absorption of Se by plants is primarily influenced by the available Se levels in soils, rather than by the soil total Se content, offering potential for exploring Se-rich crops in Se-deficient regions. In this study, we explore the factors influencing the Se bioaccumulation coefficient in corn based on a land quality geochemical survey at a 1:50,000 scale and establish predictive models for corn seed Se content using random forest and multiple linear regression approaches. The results indicate that the surface soil in the study area is deficient in Se (0.18-1.21 mg/kg), but 54% of the corn grain samples met the standards for Se-rich products (0.02-0.30 mg/kg). The factors influencing the Se biological enrichment coefficient in corn seeds are soil pH and CaO and MgO content, with impact levels of 0.54, 0.42, and 0.35, respectively. Compared to multiple linear regression models, the RF model provides more accurate and reliable predictions of corn Se content. The random forest model indicates that approximately 41% of the farmland within the study area is conducive to the cultivation of naturally Se-rich corn, which is a 26% increase in the planting area compared to recommendations based solely on soil Se content. In this research, we introduce an innovative methodological framework for organically cultivating naturally Se-rich corn within regions affected by Se deficiency.

Ca and Mg stimulate protein synthesis in maize kernel through the action of endogenous hormones and defense enzymes

Soil calcium (Ca) and magnesium (Mg) mineral states in rain-fed arid regions of Northwest China are inefficient, and their levels of substitution and water-soluble states are far below the lowest threshold required for maize growth, resulting in frequent physiological diseases, restricting synthesis of kernel protein (CRP). Our study set up different levels of foliar spraying of Ca and Mg fertilizers before maize pollination to examine the response characteristics of physiological and biochemical indicators in kernel, and the driving process of CRP synthesis. The main findings were: (1) Ca and Mg significantly increased the levels of CRP and endogenous hormones, and the activities of defense enzymes and CRP synthesis enzymes, which decreased significantly and stabilized at the maturity stage of maize. (2) The synthesis and accumulation of CRP were synergistically regulated by endogenous hormones, defense enzymes, and CRP synthase enzymes, with the degree of regulation varying with the level of Ca and Mg supplementation. Indole-3-acetic acid (IAA), gibberellin (GA), zeatin riboside (ZR), catalase (CAT), malondialdehyde (MDA), and glutamate dehydrogenase (GDH) were the primary physiological driving indicators of CRP synthesis, with CRP having a significant synergistic relationship with CAT and a remarkable trade-off with other driving indicators. (3) The dominant driving pathway of CRP synthesis was "Ca, Mg-IAA or GA or ZR-CAT-GDH-CRP". Ca and Mg positively affected IAA and GA levels, and IAA and GA positively regulated CAT activity. However, CAT negatively regulated GDH levels, causing GDH to negatively influence the synthesis and accumulation of CRP and its components. The findings provide theoretical support for further study of inter-root endogenous hormones and soil microbe-driven processes in the regulation of maize quality by Ca and Mg.

Enhanced control efficacy of spinosad on corn borer using polylactic acid encapsulated mesoporous silica nanoparticles as a smart delivery system

Asion corn borer (Ostrinia furnacalis (Guenee)) is one of the most important factors affecting the normal growth and yield of corn. However, chemical control methods currently in use cause severe pollution. In the present study, aminated mesoporous silica nanoparticles (MSNs-NH2) and polylactic acid (PLA) were used as the carrier and capping agent respectively to construct an insect gut microenvironment nano-response system that loaded spinosad, a biopesticide used to control O. furnacalis. The resulting spinosad@MSNs-PLA demonstrated high loading capacity (38.6 %) and improved photostability of spinosad. Moreover, this delivery system could intelligently respond to the intestinal microenvironment of the corn borer's gut and achieve the smart release of spinosad. Compared with the conventional pesticide, spinosad@MSNs-PLA exhibited superior efficacy in controlling the O. furnacalis and could uptake and transport in maize plants without adverse effects on their growth. Furthermore, the toxicity of spinosad@MSNs-PLA on zebrafish was reduced by over 50 times. The prepared spinosad@MSNs-PLA has great potential and could be widely applied in agricultural production in the future. This approach could improve the utilization of pesticide and reduce environmental pollution. In addition, MSNs-PLA nano vectors provide new ideas for the control of other borer pests.

Probability of cultivating Se-rich maize in Se-poor farmland based on intensive field sampling and artificial neural network modelling

Selenium (Se) is a necessary micronutrient for humans, and its supplementation from crop grains is important to address the ubiquitous Se deficiency in people worldwide. Se uptake by crops largely depend on soil bioavailable Se rather than soil total Se content, which provides possibilities to explore the Se-rich crops in Se-poor area. Here, the possibility of cultivating Se-rich maize grains in Se-poor farmland was tested based on intensive field sampling and mathematical modelling. Sampling was conducted at county scale, and a total of 7779 topsoil samples and 109 maize samples with paired rhizosphere soils samples were collected. Results showed that although the soil Se content in the study county from southwestern China was at a low level (0.01-2.75 mg kg^-1), 54.1% of the maize grain samples satisfied the standard for Se-rich products (0.02-0.30 mg kg^-1). Soil organic matter, iron oxide, and phosphorus levels were correlated negatively with Se bioconcentration factor (BCF) of maize grain. Compared with the multivariate linear regression model, the artificial neural network (ANN) model was more accurate and reliable in predicting maize Se BCF. Prediction using the ANN model showed that 22.7% of the county's farmland was suitable for cultivating naturally Se-rich maize, which increased 21.3% growing areas than that from cultivation based on simply soil total Se. This study provided a new methodological framework for natural Se-rich maize production and verified the probability of cultivating naturally Se-rich maize in Se-poor farmland.

Agricultural Insurance, Climate Change, and Food Security: Evidence from Chinese Farmers

As an effective risk management mechanism, agricultural insurance can reduce the risk of uncertainty in agricultural production and guarantee food security. Based on Chinese provincial panel data from 2003 to 2020, this study uses the Entropy Method to measure food security and systematically examines the impact of climate change and agricultural insurance on food security as well as its mechanisms. The present study found that climate change, especially extreme temperatures, has a significant negative impact on food security and food production. The promotion effect of agricultural insurance on food security increases with increased investments in technology, education, and other factors. Furthermore, our findings suggest the presence of geographical variations in the contribution of agricultural insurance to ensuring food security, with greater coverage in major food-producing regions. Additionally, maize yields are better protected by agricultural insurance than wheat and rice yields. To encourage sustainable agricultural development, the Chinese government should set up a diversified subsidy scheme with various planting scales and plant structures.