Future global concurrent droughts and their effects on maize yield

Development of Trivariate Multiscalar-Standardized Drought Index (TMSDI) for assessing drought characteristics

Drought is an extensive natural hazard influenced by human activities. Drought has a substantial impact on environmental systems and socioeconomic activities globally, posing serious challenges to water resources, agriculture, and ecosystems. Drought as a complicated natural occurrence is difficult to monitor and anticipate. However, to address the detrimental issues of drought, this study examined the innovative Trivariate Multiscalar-Standardized Drought Index (TMSDI). The climatic factors of precipitation, temperature, and Normalized Difference Vegetation Index (NDVI) are components in the development of TMSDI. To check the association of the innovative index with the another drought indices, this study evaluated correlations between the proposed index (TMSDI) and traditional drought indices, i.e., the Standardized Precipitation Index (SPI) and the Standardized Precipitation Temperature Index (SPTI) at 1-, 3-, 6-, 9-, 12-, 24-, and 48-month time scales. The outcomes demonstrate that there is a consistent relationship between the TMSDI and SPI due to higher values of correlation. The lower correlation between TMSDI and SPTI shows that there is a substantial and consistent relationship between TMSDI and SPI than TMSDI and SPTI. Moreover, the long-term behavior of different drought conditions indicates that extreme drought is more likely than extreme wet across the Markov chain's Steady States Probabilities (SSPs). Consequently, the proposed index (TMSDI) is recommended as an effective tool to precisely and accurately monitor drought conditions over different time scales within different climate factors.

Micro-/nanobubble oxygenation irrigation enhances soil phosphorus availability and yield by altering soil bacterial community abundance and core microbial populations

Micro-/nanobubble oxygenation irrigation, as a novel irrigation technique, has been widely utilized to enhance soil phosphorus availability and maize yield. Nevertheless, currently, most of the studies remain unclear about the precise mechanism through which micro-/nanobubble oxygenation improves soil phosphorus availability and maize yield. Therefore, we established two irrigation methods, conventional irrigation (CF) and micro-/nanobubble oxygenation irrigation (MB), to investigate the combined effects on enzyme activity, microbial communities, and soil phosphorus availability in the rhizosphere soil of maize.The results showed that compared to the CF treatment, the MB treatment significantly increased available phosphorus content and alkaline phosphatase activity in maize rhizosphere soil by 21.3% and 15.4%, respectively. Furthermore, MB significantly influenced bacterial diversity in the maize rhizosphere soil but did not considerably affect fungal diversity. Specifically, MB regulated the microbial community structure in the maize rhizosphere by altering the relative abundances of the bacterial phylum Firmicutes and the fungal phyla Mucoromycota, Chytridiomycota, and Basidiomycota. In addition, MB reduced the complexity of the bacterial network while increasing the interaction density among bacterial species. Meanwhile, MB enhanced the complexity of the fungal network. Structural equation modeling indicated that MB primarily promoted soil alkaline phosphatase activity by regulating bacterial community diversity, thereby enhancing soil phosphorus availability. In conclusion, the application of micro-/nanobubble oxygenation irrigation enhances the activity of alkaline phosphatasein the soil by modulating the microbial community within the rhizosphere, thereby facilitating increased phosphorus availability in the rhizosphere of maize.

Cascading spatial drought network: A complex networks approach to track propagation of meteorological droughts to agricultural droughts

Meteorological droughts often propagate to agricultural (and other) droughts, both spatially and temporally. The present study proposes a novel complex networks-based cascading spatial drought network to examine the spatial propagation of meteorological droughts in a region to agricultural droughts in other regions. This is done through: (1) establishing stable homogeneous drought communities; (2) investigating inter-community drought propagation; (3) locating drought sources; and (4) evaluating drought connections within major crop belts. The approach is implemented to study droughts in the Indian-subcontinent during the period 1948-2022. Monthly precipitation and root-zone soil moisture data from GLDAS (Global Land Data Assimilation System) are used to compute the standardized precipitation index (SPI) for meteorological droughts and standardized soil moisture index (SSI) for agricultural droughts. Primarily, the drought network is demarcated into several subsets of network communities within which clusters of localized propagation take place. Multi-community subgraphs combining different communities are also formed to understand the long-distance inter-community drought linkages. Using network centrality measures, such as degree, closeness, and clustering coefficient, network properties of scale-freeness, small-worldness, and presence of rich-clubs are checked. Although the overall network does not exhibit any of these properties, certain subgraphs have significant small-worldness, rich-clubs, and partial scale-freeness. Some of the crucial nodes that support these network properties lie in the monsoon pathways (in the Western Ghats), and others have a strong association with El Niño Southern Oscillation (ENSO) teleconnections, thus validating the ability of the drought network to capture seasonal and climatic features. Additionally, subgraphs of nodes with high productivity of different food crops are created to study drought propagation within crop belts. Barring potential shortcomings related to data dependencies, the cascading spatial drought network helps identify an impending agricultural drought that could strengthen our ability to forecast droughts.

Genome-wide identification and expression analysis of CASPL gene family in Zea mays (L.)

Casparian strip membrane domain proteins like (CASPL), exhibit profound associations with root development, stress responsiveness and mineral element uptake in plants. Nonetheless, a comprehensive bioinformatics analysis of the ZmCASPL gene family in maize remains unreported. In the study, we have identified 47 ZmCASPL members at the whole-genome level, systematically classifying them into six distinct groups. Furthermore, our analysis revealed that the same group of ZmCASPL contains similar gene structures and conserved motifs. Duplication events showed whole genome duplication (WGD) and tandem duplication (TD) contribute to the generation of the ZmCASPL gene family together in maize, but the former plays a more prominent role. Furthermore, we observed that most ZmCASPL genes contain MYB-binding sites (CAACCA), which are associated with the Casparian strip. Utilizing RNA-seq data, we found that ZmCASPL21 and ZmCASPL47 are specifically highly expressed only in the roots. This finding implies that ZmCASPL21 and ZmCASPL47 may be involved in the Casparian strip development. Additionally, RNA-seq analysis illuminated that drought, salt, heat, cold stresses, low nitrogen and phosphorus conditions, as well as pathogen infection, significantly impact the expression patterns of ZmCASPL genes. RT-qPCR revealed that ZmCASPL 5/13/25/44 genes showed different expression patterns under PEG and NaCl treatments. Collectively, these findings provide a robust theoretical foundation for further investigations into the functional roles of the ZmCASPL gene family in maize.

Energy-water management system based on robust predictive control for open-field cultivation

Food availability has been endangered by recent global events, where agriculture, the main food source for the global population, is expected to increase even more to fulfill the growing food demand. Along with food production, water and energy consumption are also increased, leading to over-extraction of groundwater and an excess emission of greenhouse gases due to fossil fuel consumption. In this context, a balance of these three resources is crucial; therefore, the water-energy-food nexus is considered to address the previous issues by designing an energy-water management system based on robust predictive control. This controller estimates the future worst-case scenario for multiple climatic conditions, such as solar radiation, ambient temperature, wind speed, precipitation, and groundwater recharge, to define an optimal irrigation volume, maximize crop growth, and minimize water consumption. At the same time, the controller schedules daily irrigation and groundwater extraction, considering energy availability from solar generation and storage, to fulfill the previously defined irrigation volume while minimizing operating costs. Climate prediction is done through fuzzy prediction intervals, whose lower or upper bound are used as worst-case to include climate uncertainty on the controller design. The energy-water management system is tested in different experiments, where results show that considering a robust approach ensures maximum crop development, avoids over-extraction of groundwater, and prioritizes renewable energy sources. This work proposes a robust energy-water management system designed to be sustainable. Considering the water-energy-food nexus, the system ensures food security and proper resource allocation, tackling global starvation, water availability, and energy access.

Weather Extremes Shock Maize Production: Current Approaches and Future Research Directions in Africa

Extreme weather events have led to widespread yield losses and significant global economic damage in recent decades. African agriculture is particularly vulnerable due to its harsh environments and limited adaptation capacity. This systematic review analyzes 96 articles from Web of Science, Science Direct, and Google Scholar, focusing on biophysical studies related to maize in Africa and worldwide. We investigated the observed and projected extreme weather events in Africa, their impacts on maize production, and the approaches used to assess these effects. Our analysis reveals that drought, heatwaves, and floods are major threats to African maize production, impacting yields, suitable cultivation areas, and farmers' livelihoods. While studies have employed various methods, including field experiments, statistical models, and process-based modeling, African research is often limited by data gaps and technological constraints. We identify three main gaps: (i) lack of reliable long-term experimental and empirical data, (ii) limited access to advanced climate change adaptation technologies, and (iii) insufficient knowledge about specific extreme weather patterns and their interactions with management regimes. This review highlights the urgent need for targeted research in Africa to improve understanding of extreme weather impacts and formulate effective adaptation strategies. We advocate for focused research on data collection, technology transfer, and integration of local knowledge with new technologies to bolster maize resilience and food security in Africa.

Genetic trends in the Zimbabwe's national maize breeding program over two decades

Monitoring genetic gains within breeding programs is a critical component for continuous improvement. While several national breeding programs in Africa have assessed genetic gain using era studies, this study is the first to use two decades of historical data to estimate genetic trends within a national breeding program. The objective of this study was to assess genetic trends within the final two stages of Zimbabwe's Department of Research & Specialist Services maize breeding pipeline between 2002 and 2021. Data from 107 intermediate and 162 advanced variety trials, comprising of 716 and 398 entries, respectively, was analyzed. Trials were conducted under optimal, managed drought stress, low nitrogen stress, low pH, random stress, and disease pressure (maize streak virus (MSV), grey leaf spot (GLS), and turcicum leaf blight under artificial inoculation. There were positive and significant genetic gains for grain yield across management conditions (28-35 kg ha-1 yr-1), under high-yield potential environments (17-61 kg ha-1 yr-1), and under low-yield potential environments (0-16 kg ha-1 yr-1). No significant changes were observed in plant and ear height over the study period. Stalk and root lodging, as well as susceptibility to MSV and GLS, significantly decreased over the study period. New breeding technologies need to be incorporated into the program to further increase the rate of genetic gain in the maize breeding programs and to effectively meet future needs.

Assessment of the combined vulnerability to droughts and heatwaves in Shandong Province in summer from 2000 to 2018

Droughts and heat waves exhibit synergistic effects and are among the world's most costly disasters. To explore the spatiotemporal differences and formation mechanisms of the combined vulnerability to droughts and heat waves in Shandong Province over the past 20 years, a vulnerability scoping diagram (VSD) model with three dimensions-exposure, sensitivity, and adaptability-was constructed to assess and compare the combined vulnerability to high-temperature and drought events, considering economic and social conditions. The results showed that (1) over the past 20 years, heat waves and droughts have increased in Shandong Province. The number of high-temperature events significantly increased in the west and decreased along the eastern coast, and drought change was characterized by an increase in the south and a decrease in the north. (2) The combined exposure to summer droughts and heat waves in Shandong Province showed a significant increasing trend (P < 0.05) at a rate of approximately 0.072/10a; the combined sensitivity significantly decreased (P < 0.05) at a rate of approximately 0.137/10a, and the combined adaptability continued to increase at a rate of approximately 0.481/10a. (3) The combined vulnerability to summer droughts and heat waves in the western inland area of Shandong Province was high and gradually decreased toward the southeastern coast. The overall decrease trend was nonsignificant with a decrease of approximately 0.126/10a, and the decline rate decreased from northwest to southeast, in which Laiwu, Yantai, Jinan, and Zibo cities exhibited a significant decreasing trend (P < 0.05). Although the compound vulnerability of Shandong Province has decreased insignificantly, the frequency of combined drought and heat wave events has increased, and the combined vulnerability will increase in the future.

Effect of rosin based quaternary ammonium salt on mechanical, hydrophily, antibacterial of cornstarch/polydopamine film for food packaging

Food packaging made of biobased materials is environmentally friendly, among which starch film is a type of biobased packaging with great development value. Some existing studies have attempted to add polydopamine (PDA) to enhance cross-linking, but there are still problems such as weakness and hydrophilicity, which greatly limit its application. Therefore, this study synthesized rosin based quaternary ammonium salt-modified cornstarch (ST-B), which was used to replace part of unmodified cornstarch (ST). In the prepared ST/PDA0.5/ST-B5 film, the introduction of a rigid rosin structure increased the stress and water contact angle of the ST/PDA0.5 film by 62 % and 26 %, respectively, while reducing its wettability and WVP; thus, further enhancing its antioxidant activity. Due to the antibacterial ability of rosin quaternary ammonium cations, the packaging film containing 7 wt% ST-B can kill >94.6 % of S. aureus and 99.9 % of E. coli, and can also extend the shelf life of strawberries. In addition, it is proven that the packaging film has good biocompatibility and high safety within cytotoxicity tests and 30-day gavage tests in mice. Therefore, the prepared ST/PDA/ST-B film has more potential for application in food preservation.

Impact of Water Shortage on Soil and Plant Attributes in the Presence of Arbuscular Mycorrhizal Fungi from a Harsh Environment

Arbuscular mycorrhizal fungi (AMF) play a crucial role in plant health due to their ability to improve tolerance to biotic and abiotic stresses. Our aim was to evaluate the effectiveness of a pool of native AMF from a harsh environment on plant performance and changes in soil attributes under different levels of drought. An experiment using maize was established, varying the soil water content to simulate severe drought (30% of the water-holding capacity [WHC]), moderate (50% of the WHC) and no drought (80% of the WHC, control treatment). Soil and plant attributes were measured (enzyme activity, microbial biomass, AMF root colonisation and plant biomass and nutrient uptake). There was a two-fold increase in plant biomass under moderate drought when compared to no drought treatment, but there was no difference in nutrient uptake. Under severe drought, there were the highest enzyme activities related to phosphorus (P) cycling and P microbial biomass, indicating higher P microbial immobilization. The increase in AMF root colonisation was observed in plants under moderate and no drought. Our findings demonstrated that the better use of the AMF inoculum varied according to drought levels, with better performance under moderate drought due to the increase in plant biomass.