Regional Production Research Articles

From urban clusters to megaregions: mapping Australia’s evolving urban regions

This study employs percolation theory to investigate the hierarchical organisation of Australian urban centres through the connectivity of their road networks. The analysis demonstrates how discrete urban clusters have developed into integrated regional entities, delineating the pivotal distance thresholds that regulate these urban transitions. The study reveals the interconnections between disparate urban clusters, shaped by their functional differentiation and historical development. Furthermore, the study identifies a dichotomy of urban agglomeration forces and a persistent spatial disconnection between Australia’s wider urban landscape. This highlights the interplay between urban densification and peripheral growth. It suggests the need for new thinking on potential integrated governance structures that bridge urban development with broader social and economic policies across regional and national scales. Additionally, the study emphasises the growing importance of national coordination in Australian urban development planning to ensure regional consistency, equity, and productivity.

Inward FDI and regional performance in Europe after the Great Recession

Abstract This paper looks at inward foreign direct investment (FDI) and regional labour productivity in the aftermath of the Great Recession, exploring two FDI-induced effects. The first effect is linked with a capacity of FDI per se to trigger short-term productivity gains in response to a global shock. The second effect is associated with the degree of industrial diversification of these investment flows. The results suggest that it is not the amount of foreign investment received per se that matters for productivity recovery but its composition. A low degree of FDI diversification helped regions to gain productivity after the shock. The effect is stronger in regions with an industrial profile concentrated in a limited number of sectors, particularly in services. FDI can support regional recovery, but in the short run, it does so by matching and reinforcing existing regional specialisation profiles and to the benefit of services-oriented regions.

Beyond nearshoring: The political economy of Mexico's emerging electric vehicle industry

Nearshoring and global value chain reconfiguration trends have gained renewed relevance amid mounting disruptions in globalized production models. However, the precise dynamics behind shifts in the nascent electric vehicle (EV) industry value chain remain unclear. This study examines the factors that drive direct investment into Mexico's EV production ecosystem. It analyzes how these investment patterns reshape regional value chains while accelerating the transition toward electromobility. This analysis is based on an original 2019–2023 dataset of 48 Mexican EV production investment projects and three emblematic case studies: Tesla, Metalsa, and Sanhua. The findings suggest that the confluence of USMCA trade pact stipulations, US-China tensions, climate policy, and consumer incentives in the US, alongside specialized capabilities in Mexico, catalyze this nascent EV industry. In this fluctuating landscape, Mexico plays a dual role, both reducing US reliance on Chinese-dominated chains while attracting international firms interested in integrating into regional production networks. Thereby, the study delineates the specific drivers beyond nearshoring that have attracted EV production investment to Mexico. It, therefore, provides insights into the forces shaping Mexico's emergence as a strategic hub for regionalized EV manufacturing and outlines implications for future corporate strategies and public policies.

Detection of extended gamma-ray emission in the vicinity of Cl Danks 1 and 2

Abstract We report the detection of high-energy gamma-ray emission towards the G305 star-forming region. Using almost 15 years of observation data from Fermi Large Area Telescope, we detected an extended gamma-ray source in this region with a significance of ∼13σ. The gamma-ray radiation reveals a clear pion-bump feature and can be fitted with the power law parent proton spectrum with an index of −2.5. The total cosmic ray (CR) proton energy in the gamma-ray production region is estimated to be the order of $10^{49}\ \rm erg$. We further derived the CR radial distribution from both the gamma-ray emission and gas distribution and found it roughly obeys the 1/r type profile, though a constant profile is not ruled out. This is consistent with other similar systems and expected from the continuous injection of CRs by the central powerful young massive star cluster Danks 1 or Danks 2 in this region. Together with former detections of similar gamma-ray structures, such as Cygnus cocoon, Westerlund 1, Westerlund 2, NGC 3603, and W40, the detection supports the hypothesis that young massive star clusters are CR accelerators.

Impact of investments in mining on economic growth of Krasnoyarsk Krai

Aim. To evaluate the impact of investments in mineral extraction on the economic growth of Krasnoyarsk Krai using the dynamics of data for 2004–2021.Objectives. To prepare initial data for modeling in comparable prices; to build statistical models with a time lag; to determine the multiplier and gas pedal coefficients of investment; to demonstrate the possibilities of applying the obtained dependencies.Methods. The authors used the method of economic and mathematical modeling, in particular the calculation of socio-economic indicators using mathematical statistics. The regression model was built using the initial data that meet the requirements of comparability and homogeneity, are relevant and statistically reliable.Results. Dependencies reflecting the investment multiplier effect, i.e. the increase in the gross regional product (GRP) and the volume of shipped products in response to the increase in investment in mining were obtained. Dependencies reflecting the investment gas pedal effect are also obtained, showing how increased income affects the size of investment. The dependencies are applied to solve a number of practical problems.Conclusions. It has been established that investments in mining in Krasnoyarsk Krai have an impact on the growth of GRP and the volume of shipped products. The return on investment has a temporary character. The strongest impact of investments in the current year have on the growth of GRP and shipped products for the next year. The multiplier coefficient is 2.72. Increased income affects the size of investments: the growth of income from mining stimulates the growth of induced investments in the following year with the multiplier coefficient, which is equal to 0.14. The comparison of actual values of investments in mineral resources extraction and volume of shipped products with the target values laid down in the Strategy of socioeconomic development of the region until 2030 has been carried out. The target values, according to the Strategy, are determined with the help of the obtained dependencies. It was established that the actual volume of investments is sufficient to ensure the GRP growth in accordance with the Strategy at the first stage; to ensure growth at the second stage it is necessary to increase investments by 12–15 % annually; to ensure growth at the third stage it is necessary to increase investments by 9–13 % annually from the current state. In order to ensure the values of indicators on the volume of production provided for in the Strategy, it is necessary to increase output by 4–6 % annually compared to 2021.

No-Till and Crop Rotation Are Promising Practices to Enhance Soil Health in Cotton-Producing Semiarid Regions: Insights from Citizen Science

This on-farm study was conducted to assess the impact of six prevalent crop management practices adopted by growers in West Texas on various indicators of soil health. This study is a part of a citizen science project, where we collaborated with cotton growers who helped with standardized sample and data collection from 2017 to 2022. This project aimed to identify soil management practices that increase carbon sequestration, enhance biological activities, and improve overall soil health. We monitored soil moisture, soil organic matter (SOM), inorganic nitrogen (NH4+-N and NO3−-N) and other exchangeable nutrients, and soil microbial abundances as obtained via fatty acid methyl ester (FAME) in 85 fields, incorporating different management practices during the cotton growing season. In our study, volumetric moisture content (VWC) was increased by no-till, irrigation, and crop rotation, but the addition of residue decreased VWC. No-till, irrigation, and crop rotation increased SOM, but a cover crop decreased SOM. No-till and residue retention also increased microbial biomass carbon (MBC). Tillage, irrigation, and crop rotation influenced the abundance of the main microbial groups, including bacterial, fungi, and arbuscular mycorrhizal fungi (AMF). Additionally, water content, SOM, and microbial abundances are correlated with clay percentage. Our results indicate that no-till and crop rotation are the two most crucial soil management approaches for sustainable soil health. As such, implementing both no-till and crop rotation in the cropping systems has the most promising potential to increase the soil resilience in dryland cotton production in semiarid regions, thereby helping growers to maintain cotton production.

Study on Spatiotemporal Characteristics and Influencing Factors of High-Resolution Single-Season Rice

Single-season rice describes the area under rice cultivation from May–October of the year. Many scholars have used lower-resolution data to study single-season rice in different regions, but using high-precision and high-resolution single-season rice data can reveal new phenomena. This paper uses a long-time-series, high-precision, and high-resolution single-season rice cultivation dataset to conduct an in-depth analysis of the spatial–temporal variability characteristics of single-season rice in Jiangsu Province, China, from 2017 to 2021. It explores the correlation between meteorological factors and greenhouse gasses for single-season rice. It analyzes the driving role of social factors on single-season rice. The results showed that single-season rice was mainly grown in the central and northeastern regions of the study area. The single-season rice cultivation was significantly reduced in 2020 due to the impact of COVID-19. Single-season rice strongly correlates with meteorological factors in time but shows a weak spatial correlation. This is because human factors largely dominate the area under single-season rice cultivation. Methane emissions in the study area are mainly influenced by anthropogenic activities rather than single-season rice. Social factors are essential in controlling single-season rice cultivation in the study area. This study was conducted in Jiangsu Province, China. Still, the methodology and results have important implications for agricultural production and environmental management studies in other regions, and some findings have general applicability.

Features, reasons, and significance of radon and thoron attributable radiological dose in the indoor environment

Humans receive around 50% of natural radiation dose due to 222Rn (radon), 220Rn (thoron) and their decay products. Several field campaigns measuring these gases and the decay products in different regions of India have been conducted in the recent past. Some of these studies measured indoor activity concentration and/or dose due to these gases and the associated decay products. This work compares the fraction of 222Rn and decay products and 220Rn and decay products in inhalation dose for 10 studies conducted in Uttarakhand state. It is seen that AEDT (annual effective dose due to 220Rn and decay products) for these regions varies between 21 and 48% and it is significantly higher than the averaged worldwide reference value of 6%. Based on elaborative measurements performed in the Bageshwar district (present work), Almora and Nainital districts (our previous campaigns); the reasons for this high value have been explored. It was observed that a higher source term for mud houses could be the main reason for the high AEDT range. Interestingly, preliminary analysis revealed that the fraction is higher for the dwellings situated at higher altitudes thus indicating the role of the unavailability of modern building construction materials at remote locations. The study highlights the significant contribution of thoron in the Indian Himalayas.

Factors influencing regional disparities in online shopping

Online shopping has grown exponentially in the Russian Federation (hereinafter referred to as RF, Russia) in recent years. This growth has significantly accelerated during the COVID-19 pandemic. However, data shows that there are inter-regional disparities in the use of online shopping. This includes intergenerational and rural-urban disparities. This study investigates the factors responsible for inter-regional differences in the development of online shopping in Russia. The author has identified 5 main factors that can influence the development: internet infrastructure (measured by regional expenses for the introduction of digital technologies and the number of connected mobile subscribers), economic wealth (measured by gross regional product), standard of living (measured by the population income), rate of poverty, and the region’s population. The research uses data of the Federal State Statistics Service and Association of Internet Trade Companies to analyse 85 regions in the RF. A multi-level regression analysis has enabled examination of the 5 factors and the contextual influence of 8 federal districts of Russia in level 2. The results show that internet infrastructure, economic wealth, population size, and the 8 federal districts has influenced the development of online shopping in the RF, but standard of living is not statistically significant. The author recommends that policymakers pay attention to these underlying factors.

Distinct pollinator communities persist among co-flowering specialty crops in Indiana

Diverse bee communities pollinate fruits and vegetables, and the composition of these communities has been described for many specialty crops in major production regions. However, pollinator communities in landscapes dominated by agronomic crops may differ in species composition and the contribution of wild bees. With over 4 million ha of maize and soybean, Indiana presents a novel landscape to compare pollinator communities among specialty crops that differ in their use of managed bees and bloom phenology, with potential implications for the composition of wild bee communities and their contributions to flower visitation. We sampled pollinator communities with flower observations and pan traps in spring-blooming apples and blueberries and summer-blooming tomatoes and watermelons, allowing us to compare communities between specialty crops with overlapping and distinct bloom times. Apples, blueberries, and watermelons were stocked with honey bees, and watermelons additionally had managed bumble bees. Across two years of sampling, we observed 1,651 flower visits by 13 taxa, collected 1,967 bees, and identified 84 taxa from collected specimens. Apples and blueberries hosted the richest pollinator communities (34 and 51 taxa, respectively) followed by watermelons (22 taxa), and tomatoes (19 taxa). While 70% of flower visits in apples and blueberries were attributed to honey bees, wild bees accounted for 82% and 99% of flower visits in watermelons and tomatoes, respectively. Our results indicate that distinct pollinator communities persist among co-flowering specialty crops in a landscape dominated by maize and soybean production and underscore the contribution of wild bees for specialty crop pollination, particularly in watermelons and tomatoes.

Dynamics of Energy Fluxes in a Mediterranean Vineyard: Influence of Soil Moisture

Accurate evaluation of grapevine water use is essential for optimizing water management and maximizing grapevine yield and berry quality in Mediterranean climates. Understanding the water and heat flux dynamics in a vineyard during grapevine berry maturation is of utmost importance. This study focuses on evaluating sensible and latent energy fluxes at the canopy, the soil beneath the canopy, and the interrow areas. The primary objective is to develop a model framework for accurately estimating these energy fluxes, contributing to a better understanding of their behavior during berry ripening. The model’s accuracy was assessed by comparing the estimated fluxes with those measured by an eddy-covariance system installed at a reference height of three meters in the experimental vineyard. This validation step was essential to confirm the model’s ability to capture the intricate energy flux dynamics of the vineyard, especially during grape maturation. The results revealed a high level of agreement between the observed and estimated fluxes, confirming the model’s reliability. This comprehensive evaluation of energy fluxes provides valuable insights for optimizing irrigation strategies. By doing so, this study contributes to improving grape quality, ensuring sustainable water resource use, and ultimately enhancing vineyard productivity in arid and water-scarce regions.

Impact of Heat Stress on Milk Yield, Milk Fat-to-Protein Ratio, and Conception Rate in Thai-Holstein Dairy Cattle: A Phenotypic and Genetic Perspective.

Heat stress severely affects dairy cattle production and reproduction performances in tropical regions. Genetic selection to maintain adequate yield and reproductive performance while enhancing their ability to withstand heat is essential for improving the genetics of dairy cows. Therefore, in this study, we aimed to estimate genetic parameters affecting production and reproduction performances under heat stress conditions in dairy cattle and to investigate the threshold point of heat stress for milk yield (MY), milk fat-to-protein ratio (FPR), and conception rate (CR) in Thai-Holstein dairy cattle. The data included 168,124 records related to MY and milk FPR and 21,278 records of CR in Thai-Holstein dairy cattle, covering the period from 1990 to 2007. A multiple-trait threshold-linear random regression model based on a Bayesian approach via Gibbs sampling was used to estimate variance components, genetic parameters (heritability values, and genetic correlations), and decline rates for each studied trait. The threshold point of heat stress was identified as a temperature and humidity index (THI) of 76. At THI76, a decline was observed in the MY, milk FPR, and CR of Thai dairy cattle. The heritability estimates for MY, milk FPR and CR were 0.347 ± 0.032, 0.293 ± 0.021, and 0.032 ± 0.001, respectively. The genetic correlation between MY and milk FPR and MY and CR were -0.24 and -0.53, respectively, whereas those between milk FPR and heat tolerance as well as between CR and heat tolerance were -0.48 and -0.49, respectively. In addition, the decline rates in MY, milk FPR, and CR were found to be associated with a high percentage of Holstein genetics. In conclusion, the results obtained in this study reveal that the simultaneous consideration of the MY, milk FPR, CR, and heat tolerance traits of Thai-Holstein dairy cattle is possible. In addition, developing a genetic model that incorporates THI is essential for sustainably addressing heat stress problems.

Revealing hidden viruses inducing similar yellowing symptoms or remaining asymptomatic in cucurbit crops

AbstractMixed viral infections occur frequently in plants, leading to diseases that can be difficult to diagnose, especially when an unknown virus is hidden behind expression of symptoms common to other viruses. We monitored aphid‐ and whitefly‐transmitted viruses in two cucurbit crops (melon and watermelon) for three consecutive seasons (2021–2023) across three production regions in Spain, focusing on the common yellowing and mosaic symptoms. A total of 984 symptomatic leaf samples from 246 field plots were tested for 10 frequently found cucurbit viruses. Cucurbit aphid‐borne yellows virus (CABYV) was the most prevalent virus infecting both cucurbit crops over the three seasons. Additionally, occurrence of watermelon mosaic virus (WMV) in samples with mosaic symptoms was significant. However, an important proportion of yellowing symptomatic samples tested negative for known viruses. Using a sequence‐independent approach, we identified a novel polerovirus, Pepo aphid‐borne yellows virus (PABYV), which was widespread, infecting both crops. Analysis of our long‐term cucurbit frozen‐sample collection revealed that PABYV had emerged in Spain in 2018, possibly unnoticed as its yellowing symptoms were similar to CABYV, with which it was frequently associated. Additionally, we found the cryptic Cucumis melo endornavirus (CmEV) in all tested melon samples from 2011 and, for the first time, in pumpkin. Genetic characterization of CABYV, PABYV and CmEV populations revealed a replacement of ancient CABYV isolates by contemporary ones, while PABYV and CmEV isolates were genetically homogenous among their populations. This study underlines the need for continuous surveillance and further investigation into common symptoms of mixed viral infections.

Analysis of Flow Loss Characteristics of a Multistage Pump Based on Entropy Production

To reveal the internal flow loss characteristics of a multi-stage pump, the unsteady calculation of the internal flow field of a seven-stage centrifugal pump was carried out, and the entropy production theory and Q criterion were utilized to analyze the unsteady flow characteristics of each flow component under different flow rates. The research results show that as the flow rate increases, the entropy production value and the energy loss inside the flow components also increase accordingly. The viscous dissipation entropy production caused by fluid viscosity is very small, and the turbulent dissipation entropy production caused by turbulent fluctuations and wall dissipation entropy production are the main sources of energy loss. The impellers, diffusers, and outlet chamber are the main regions of energy loss in the multistage pump. The entropy production value of the first-stage impeller is significantly higher than that of other impellers, while the entropy production value of the first-stage diffuser is significantly lower than that of other diffusers. Through vortex structure analysis, it is found that the high entropy production regions in the impeller are concentrated in the impeller inlet area, the blade suction surface, and the impeller outlet area.

Winter wheat identification in China through FY-3D NDVI&EVI satellite data and DNN Fusion

ABSTRACT Medium Resolution Spectral Imager-II (MERSI-II) on FengYun 3D (FY-3D) meteorological satellite is a visible and infrared spectral imaging instrument comparable with Moderate Resolution Imaging Spectroradiometer (MODIS), which provides ample opportunities for regional crop mapping. However, current research may have overlooked the potential of combining FY-3D MERSI-II data with deep neural network (DNN) algorithms for winter wheat identification. This research utilizes a DNN method to train a nonlinear model with the synthetic normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) at a 250 m resolution from FY-3D MERSI-II as the eigenvalues, enabling to accurately identify spatial distribution of winter wheat in China’s main production regions and filling the gap in the application of FY-3D MERSI-II data. The results indicate that the winter wheat identification with the combination of NDVI and EVI achieved an accuracy of 95.32%, with a Kappa coefficient of 0.87 and a determination coefficient (R 2 ) of 0.73, improving the overall accuracy by 1.27% and 1.07% compared to models trained solely using NDVI or EVI, respectively. In terms of spatial distribution, the overlap rate with the winter wheat dataset of China from MODIS at a 500 m resolution exceeded 95%, with an area bias of 2.67%. This study indicates that the medium resolution FY-3D MERSI-II remote sensing dataset combined with the DNN algorithm can accurately identify crop information over large areas.

Climate-Related Risks and Agricultural Yield Assessment in the Senegalese Groundnut Basin

Climate change and variability pose significant threats to agricultural production, particularly in regions heavily dependent on rainfed agriculture like Senegal. The problem addressed in this study revolves around the impact of climate-related risks on agricultural yields in the Senegalese Groundnut Basin as a key agricultural region. Daily rainfall, temperatures, and yield over 1991–2020 were used. The data were analyzed using multiple regression, trend analysis, and correlation approaches. The results indicate that the overall seasonal precipitation increases over time (98 mm in the north and 103 mm in the south). However, we found that the south Groundnut Basin has a much slower seasonal precipitation rate than the northern zone. Our results also show that the northern zone exhibits a more consistent and predictable growing season, with onset and offset, in contrast with the southern zone, which shows higher variability. The analysis further reveals that both the northern and southern zones are experiencing a warming trend, with the southern zone showing a more pronounced increase in maximum temperatures (+0.7 °C) than to the northern zone (+0.4 °C). Estimates from the regression analysis revealed that total seasonal precipitation and maximum temperature positively and significantly influence groundnut, millet, and maize yields in the northern and southern zones. All the other weather-related parameters have different influences depending on the zone. These findings highlight the heterogeneous nature of the study area and the significant role climatic factors play in crop yield variability in the Groundnut Basin. Understanding these influences is crucial for developing targeted agricultural strategies and climate adaptation measures to mitigate risks and enhance regional productivity. The study provides valuable insights for policymakers and farmers aiming to improve crop resilience and sustain agricultural outputs amidst changing climatic conditions.

Identification of Reliable Reference Genes for Use in Gene Expression Studies in Rat Febrile Seizure Model.

The study of the pathogenesis of febrile seizures and their consequences frequently necessitates gene expression analysis. The primary methodology employed for such analysis is reverse transcription with quantitative polymerase chain reaction (RT-qPCR). To ensure the accuracy of data obtained by RT-qPCR, it is crucial to utilize stably expressed reference genes. The objective of this study was to identify the most suitable reference genes for use in the analysis of mRNA production in various brain regions of rats following prolonged neonatal febrile seizures. The expression stability of eight housekeeping genes was evaluated using the online tool RefFinder in the dorsal and ventral hippocampal regions and in the temporal and medial prefrontal cortex of the brain. The Ppia gene exhibited the greatest stability of expression. Conversely, the genes with the least stable expression levels were Actb and Ywhaz; thus, it is not recommended to use them for normalization in a febrile seizure model. Additionally, the majority of housekeeping genes demonstrate age-related, region-specific fluctuations. Therefore, it is crucial to employ the appropriate housekeeping genes for each brain structure under investigation when examining the expression dynamics of genes of interest in a febrile seizure model.

Development of Brassica carinata A. Braun resistant to acetolactate synthase–inhibiting herbicides

AbstractBrassica carinata A. Braun (carinata) has become an important oil crop for biofuel production in subtropical regions. Carinata is highly sensitive to acetolactate synthase (ALS)‐inhibiting herbicides, limiting its introduction into existing crop rotations. The objective of the study was to develop carinata lines resistant to ALS‐inhibiting herbicides. A susceptible carinata line was crossed with a resistant Brassica napus L. line. Lines derived from those crosses were screened at high doses of imidazolinones, which allowed identifying five lines with high levels of resistance. Doses to reduce plant growth 50% (GR50) and cause 50% injury (ID50) were four to nine times greater than susceptible lines. Resistant lines exhibited cross resistance with halosulfuron (sulfonylurea). Resistance was confirmed under field conditions with doses 2X and 4X for imazethapyr and 4X–8X for halosulfuron of their respective label doses. While susceptible lines died, resistant lines exhibited no injury or growth reductions compared with nontreated controls. Sequencing of the ALS gene indicated that all resistant lines carried a Trp574Leu amino acid substitution, a mutation responsible for resistance in other species. Crosses between resistant lines and a susceptible line demonstrated that the inheritance of the mutation corresponded with the resistance phenotype in the F2. The resistance trait behaved as a single, fully dominant allele, which makes it easier to transfer it to carinata lines with desirable agronomic traits. The resistant lines developed here provide flexibility for use in multiple crop rotations and opens the possibility to use ALS‐inhibiting herbicides for weed control within this crop's growing season.

Symbiotic N2 fixation in cowpea varieties is markedly enhanced by inoculation with elite Bradyrhizobium strains

Because of its excellent ability to fix atmospheric nitrogen, cowpea [Vigna unguiculata (L.) Walp] makes a significant contribution to soil sustainability and productivity in the resource limited tropical regions. However, due to in part to ineffectiveness and limited availability of bio-inoculant, its symbiotic N contribution and yield remained low in the field. Therefore, this study examined the effect of elite cowpea infecting Bradyrhizobium strains (CP-24 and CP-37) on shoot biomass and symbiotic nitrogen contributions of four cowpea varieties (Keti, TVU, Black eye bean, and White wonderer trailing). For this a two-year field experiment was carried out at three sites using a factorial randomized complete block design with four replications. The natural abundance of the 15N technique was used to compute the symbiotic N contribution. Bradyrhizobium inoculation led to significantly higher nodule formation, % Ndfa, amounts of N fixed, and shoot biomass, demonstrating the effectiveness and ability of the strains to enhance soil fertility. Inoculating cowpea with CP-24 strain increased shoot N content, % Ndfa and N fixed by 40%, 15%, and 41%, respectively, in comparison to the un-inoculated control. Furthermore, the inoculant by variety interaction had a significant effect on nodule number, nodule dry weight, and amount of N fixed, with TVU and White Wonderer trailing in combination with CP-24 exhibiting the most outstanding performance. There was also a strong positive correlation between biomass accumulation and N fixed, as well as N fixed and seed yield. Therefore, Bradyrhizobium inoculation on cowpea varieties TVU and White Wonderer trailing with CP-24 strain is recommended at all three tested sites and similar agro-ecologies for improved symbiotic N contribution and associated yield advantage of cowpea. This study highlights that, the use of elite and crop specific Bradyrhizobium strains can boost symbiotic nitrogen contribution, soil fertility, and the yield performance of legumes. Thus, it helps resource-poor farmers who are suffering from rising mineral fertilizer cost to achieve food security while reducing climate change risks.

Strategic cultivar and sowing time selection for weed management and higher redgram productivity in semi-arid Indian regions

IntroductionRedgram (Cajanus cajan L. Mill sp.), a leguminous crop commonly grown in tropical and subtropical climates, is highly valued for its high protein content (21%), which contributes significantly to food and nutritional security. However, its production faces challenges primarily due to terminal dryness experienced during critical growth stages because of changing rainfall patterns. To overcome this, adaptive techniques become imperative as the productivity of this crop is intricately linked to environmental factors and the crop’s growth cycle.MethodsHence, the field experiment was conducted at the National Pulses Research Centre, Vamban, Pudukkottai, Tamil Nadu, in South India under rainfed condition, during the kharif (monsoon) seasons of 2017–18 and 2018–19. The primary objectives were to determine the optimal sowing time and identify suitable redgram cultivars, especially in the context of the late onset of the monsoon in Tamil Nadu, a common issue under changing climate conditions. The experiments tested six different sowing dates with three redgram cultivars.Results and discussionThe findings highlighted the substantial influence of different redgram cultivars and sowing times on the crop’s growth characteristics and yield. Among the six sowing dates tested, planting in later half of June (S6) resulted in notably higher plant height (201 cm), a greater number of pods per plant (287), a seed yield of 1,112 kg ha−1, and a benefit-cost ratio of 2.61 Notably, this sowing period (S6) demonstrated comparable performance with the treatment of redgram sowing in the latter part of September (S4). CO 6 (V1) is the most productive of the three redgram cultivars, with the highest mean pant height (200 cm), number of pods per plant (237), grain yield (1,017 kg ha−1), and benefit cost ratio (2.38). Extended phenological phases along with extra days to reach phenological stages could account for the increased yield in comparison to the other cultivars. Among the two short-duration cultivars, VBN (Rg) 3 (V3) had a significantly higher mean grain yield of 958 kg ha−1 with the benefit-cost ratio of 2.24. Even though CO 6 (V1) obtained a higher yield due to its long duration nature, it matured in 187 days whereas VBN (Rg) 3 (V3) matured within 129 days. Consequently, the short-duration redgram cultivars emerge as highly suitable choices for integrating into crop sequences, thereby augmenting farm cropping intensity.