Food and Energy Security最新文献

Bio-fertilizer, as an environmentally friendly fertilizer, combined with the application of controlled-release nitrogen (CRN), contributes to increasing rice yield. However, research on the synergistic effects of blended CRN with conventional urea (CU) combined with bio-fertilizer on the yield, quality, and nitrogen (N) utilization of japonica rice remains limited. Therefore, this study selected the high-quality japonica rice variety Nanjing 9108 and conducted a 2-year field experiment with five fertilization treatments: no N fertilizer, 0N (used only for calculating fertilizer use efficiency); application of CU, CU; CU combined with bio-fertilizer, CU-Bio; application of 70% CRN blended with 30% CU, CRBBF; and application of 70% CRN blended with 30% CU combined with bio-fertilizer, CRBBF-Bio. The results showed that compared with CU, the treatments of CU-Bio, CRBBF, and CRBBF-Bio all increased rice yield by 7.48%, 8.34%, and 13.23% in the 2023 and by 8.07%, 8.74%, and 14.99% in the 2024, respectively. This improvement was primarily attributed to the synergistic increase in total spikelet number, seed-setting rate, and 1000-grain weight. Meanwhile, dry matter accumulation at different growth stages, leaf area index (LAI), as well as net photosynthetic rate and soil and plant analyzer development (SPAD) value at the heading stage were significantly enhanced, with the CRBBF-Bio treatment showing the most pronounced effects. Furthermore, CU-Bio, CRBBF, and CRBBF-Bio improved rice quality, significantly increasing head rice rate while significantly reducing chalkiness degree and chalky grain percentage. Additionally, taste value increased due to a reduction in amylose content. In terms of physiological mechanisms, CU-Bio, CRBBF, and CRBBF-Bio significantly enhanced the activities of NR, GS, and GOGAT, promoted N uptake and accumulation across growth stages, and ultimately increased N recovery efficiency (NRE) by 12.08%, 15.49%, and 22.42% in the 2023 and by 12.91%, 16.31%, and 25.38% in the 2024, respectively. These findings effectively advance the practice of high-yield and high-quality rice cultivation and are of great importance for ensuring food security.

The development of cropping systems that simultaneously enhanced farm profitability, reduce energy dependence and limit greenhouse gas emissions is central to climate smart agriculture in south Asia. The study evaluated the energy balance, carbon footprint; carbon budgeting and economic performance of no-till maize legume cropping systems under different residue based mulching practices in the lower Indo-Gangetic plains of eastern India. A 2-year field experiment (2017–2019) was conducted at Sriniketan, West Bengal; India, involving three maize based cropping systems (maize-chickpea, maize-lentil, and maize-lathyrus) combined with five biomass mulching treatments. System productivity, energy input–output relationships, carbon efficiency, greenhouse gas emissions, and economic returns were quantified using standardized energy and emission coefficients. Among the cropping systems, maize-chickpea consistently recorded higher system productivity, energy output, net energy gain, and profitability than maize-lentil and maize-lathyrus systems. Residue-based mulching significantly influenced system performance; the combination of in situ maize stalk mulch with paddy straw applied at 5 t ha⁻¹ produced the highest energy use efficiency, energy productivity, gross returns, and benefit–cost ratio. Although biomass mulching increased carbon inputs and associated emissions related to no mulch treatments, higher crop biomass production under mulched plots improved carbon efficiency and the carbon sustainability index. The no mulch treatment exhibited the lowest carbon footprint due to reduced external carbon inputs, but at the expense of lower productivity and farm income. The results demonstrated the residue-based no-till maize-legume systems can achieve a favourable balance between energy efficiency, economic viability, and carbon sustainability. Despite higher carbon inputs under biomass mulching increased biomass production improved carbon efficiency and carbon sustainability indices. The results indicate that optimized residue based no till maize-legume systems can enhance productivity and farm income while maintaining acceptable productivity scaled environmental performance, supporting climate smart agriculture in the Indo-Gangetic plains.

The cover image is based on the article Seed Pelleting Technologies: Paving the Way for Resilient and Sustainable Future Farming by Bilquees Bozdar et al., https://doi.org/10.1002/fes3.70193.

Diversified cropping systems (e.g., intercropping) can enhance soil health and crop productivity via the integrate utilization of resources, and thus have been recognized as a core strategy for advancing sustainable agriculture and safeguarding long-term security. However, varying row configurations in intercropping systems can directly alter soil properties and crop productivity, and existing research findings remain inconsistent due to differences in experimental sites and agronomic management practices. To address this, a split-plot field experiment was conducted at two sites (Pingdu and Changyi in Shandong, China) to evaluate row configuration effects on soil properties and crop productivity. Treatments included cotton (Gossypium hirsutum L) monocropping (MC), peanut (Arachis hypogaea L.) monocropping (MP), and three intercropping configurations, namely C2P4 (2 rows of cotton intercropped with 4 rows of peanuts), C4P4 (4 rows of cotton intercropped with 4 rows of peanuts), and C4P6 (4 rows of cotton intercropped with 6 rows of peanuts). The results revealed that, on average, compared with monocropping, cotton-peanut intercropping systems demonstrated comprehensive improvements, reducing soil bulk density by 4.2%–15.5%, increasing soil organic matter (5.2%–15.5%), available nitrogen (4.4%–14.1%), and phosphorus (4.7%–12.0%), while enhancing microbial abundance (bacteria: 14.5%–17.4%; fungi: 27.0%–35.7%; actinomycetes: 24.7%–27.3%). Pearson's correlation analysis showed that humus fractions, microbial abundance, and soil nutrient availability are all key determinants of crop yield. These benefits increased progressively with the peanut-to-cotton row ratio. Specifically, the C4P6 configuration (4 rows of cotton intercropped with 6 rows of peanuts) delivered peak performance: cotton and peanut yields reached 4741.65 kg·ha⁻¹ and 5484.75 kg·ha⁻¹, respectively, while the soil quality index (SQI) hit a maximum of 1335—an increase of 82.4% compared with monocropping systems. In conclusion, cotton-peanut intercropping enhances crop productivity through optimized root-soil interactions that improve soil structure, nutrient availability, and microbial functionality, with the C4P6 configuration exhibiting superior performance by synchronizing interspecific facilitation. This study provides a practical measure for sustainable agricultural intensification in the Yellow River Basin of China and semiarid regions with analogous soil constraints.

Surface drip fertigation can accurately regulate nitrogen application, increase the suitable planting density and reduce the nitrogen input. However, there are few studies on the interaction between planting density and nitrogen fertilizer under drip fertigation. Compared with the local planting density and traditional irrigation and fertilization methods (CK), a two-year field experiment was conducted using surface drip fertigation with two planting densities (60,000 plants ha⁻¹ and 90,000 plants ha⁻¹) and three nitrogen rates (180, 240 and 300 kg ha⁻¹). We analyzed nitrogen uptake dynamics and evaluated the effects of density and nitrogen on material accumulation and yield. The results showed that the nitrogen daily accumulation in traditional irrigation and fertilization methods showed a single peak curve, and the nitrogen absorption of surface drip fertigation showed two peaks from the 12th leaf stage to the silking stage (V12-R1) and from the milk stage to the dough stage (R3–R5). Optimized planting density (90,000 plants ha⁻¹) and nitrogen application (240 kg ha⁻¹) significantly enhanced population level performance, increasing leaf area duration (25.98%–71.58%), dry matter accumulation (11.19%–175.05%) and nitrogen accumulation (10.29%–131.56%) across growth stages compared to CK. Importantly, this approach maintained the individual plant biomass and the grain development, ultimately boosting the total nitrogen uptake (36.42%) and yield (48.49%) of the population. Our findings highlight the potential of dense planting and surface drip fertigation to optimize the nutrient use efficiency (balancing nutrient supply and population demand), enhance yield, and provide an efficient strategy for high-yield and high-efficiency maize planting.

Sorghum (Sorghum bicolor L. Moench) is a resilient cereal crop with remarkable adaptability to diverse environments. Nitrogen use efficiency (NUE) is critical for improving sorghum yields, resource utilization, livelihood security, and environmental sustainability of the target ecologies. To dissect the physio-genetic variation of sorghum for NUE/Nitrogen (N) stress tolerance, a set of 186 diverse sorghum accessions was evaluated for 15 agro-physiological and NUE-related traits under three N regimes (0%, 50%, and 100% of the recommended [90 kg ha⁻¹] dose) across two seasons. Genotyping-by-sequencing (GbS) SNP data enabled genome-wide association studies (GWAS). A total of 1369 marker-trait associations (MTAs) were detected across sorghum chromosomes, along with 69 candidate genes linked to N metabolism, including glutamine synthetase (GS), nitrate transporters, and sucrose-phosphate synthase. Transcriptome analysis of contrasting sorghum accessions detected 2229 (shoot) and 8661 (root) differentially expressed genes (DEGs). Integration of GWAS and transcriptomic data identified 10 key candidate genes such as the master N-regulators: the NIN-like protein (NLP), AP2/ERF transcription factor, ABC transporter, glutamine synthetase (GS), amino acid selective channel protein, F-box protein (FBP), SWEET transporter, glucose-1-phosphate adenylyltransferase (AGPase), and phosphofructokinase (PFK). Analysis of identified homologous gene groups across major cereals revealed evolutionary relationships and genetic conservation. Furthermore, this study identified contrasting sorghum accessions for N stress tolerance. The identified candidate genes and contrasting genetic stocks provide a foundation for the molecular dissection of NUE-related traits, offering clear targets for crop improvement via genomics-assisted breeding and gene editing technologies.

The design and performance analysis of agrivoltaics installations for a tomato farm in the hot and dry climate of Botswana is presented. The study investigates unique agrivoltaics solutions to solve some energy, food and water issues in rural Southern Africa. Two agrivoltaics scenarios, the low PV density and high PV density, were mapped out together with the research control scenario, which was just ordinary tomato farming. The three study cases were then modelled and simulated using the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model and PV*SOL software to deduce the tomato growth and energy output of the PV installations, respectively. The results from the crop growth simulations showed that tomato harvest is reduced when cultivated in agrivoltaics settings, and that worsens as the PV density is increased. Validation of the aforementioned results by comparing with other similar studies highlighted some possible limitations of crop modelling, since in practice, shade-tolerant plants tend to thrive in low-density agrivoltaics. The generation of PV electricity improved the land use efficiency of the farm by 15% and 8% in the low-density and high-density agrivoltaics, respectively. This means that the farmer or landowner extracts more value from their land by implementing agrivoltaics instead of persisting with conventional tomato farming. Therefore, it is concluded that agrivoltaics technology can be successfully implemented in the hot and dry climate of Botswana to enjoy some synergetic benefits between crops and PV systems, as well as improve the overall efficiency of the land use.

This study investigates the dynamics of household food insecurity in Nigeria using panel data from three waves (2012, 2015, and 2018) of the General Household Survey, situating micro-level evidence within the broader macroeconomic context. This survey is a nationally representative sample of approximately 5000 households that have been surveyed six times across the three waves. We document that the sharp deterioration in food security after 2015 coincided with three major national developments: a steep naira depreciation, a 57.3% increase in the food consumer price index, and a collapse in real food imports from $11.34 billion in 2012 to $4.21 billion in 2018, largely shaped by the 2015 oil price collapse and foreign exchange restrictions on food imports. These indicators highlight a macro-monetary transmission channel through which the oil price collapse and subsequent policy responses amplified retail food price pressures, raising household vulnerability. To identify the distributional impact of these shocks, we employ a difference-in-differences design that exploits the differential exposure of urban versus rural households. Urban households, more reliant on monetized and import-exposed food markets, serve as the treatment group, while rural households, with partial self-provisioning capacity, act as the control. Results reveal a significant post-shock rise in food insecurity across all households, with an additional and statistically robust increase among urban households. These findings clarify the mechanism by which macroeconomic and trade shocks transmit through urban retail markets to household welfare, underscoring the importance of targeted policy responses. By linking national price and trade disruptions directly to household outcomes, the paper offers a concrete evidence-based framework to guide interventions aimed at mitigating the welfare costs of macroeconomic shocks.

With the rapid digitalization of rural areas, its effects have been widely studied in terms of economic returns and lifestyle changes, yet little is known about whether and to what extent it affects household food security. Using data from rural China for the period 2019 - 2020, this study examines the causal effect of digital rural construction on household food security. Food security is measured using the Chinese Healthy Eating Index and the Diet Balance Index. The results show that digital rural construction significantly improves household food security, with stronger effects among high-income households. We further explore two potential mechanisms: dietary availability and household engagement with online dietary and health information. The findings suggest that digital rural construction significantly improves dietary availability, while its effect on online information engagement is not statistically significant. Moreover, we examine the effects of different dimensions of digital rural construction and find that rural life digitalization exerts the strongest influence on household food security. Overall, the evidence implies that advancing digital rural development can serve as an effective policy instrument to strengthen household food security in rural areas of developing countries.

This study investigates the dynamics of household food insecurity in Nigeria using panel data from three waves (2012, 2015, and 2018) of the General Household Survey, situating micro-level evidence within the broader macroeconomic context. This survey is a nationally representative sample of approximately 5000 households that have been surveyed six times across the three waves. We document that the sharp deterioration in food security after 2015 coincided with three major national developments: a steep naira depreciation, a 57.3% increase in the food consumer price index, and a collapse in real food imports from $11.34 billion in 2012 to $4.21 billion in 2018, largely shaped by the 2015 oil price collapse and foreign exchange restrictions on food imports. These indicators highlight a macro-monetary transmission channel through which the oil price collapse and subsequent policy responses amplified retail food price pressures, raising household vulnerability. To identify the distributional impact of these shocks, we employ a difference-in-differences design that exploits the differential exposure of urban versus rural households. Urban households, more reliant on monetized and import-exposed food markets, serve as the treatment group, while rural households, with partial self-provisioning capacity, act as the control. Results reveal a significant post-shock rise in food insecurity across all households, with an additional and statistically robust increase among urban households. These findings clarify the mechanism by which macroeconomic and trade shocks transmit through urban retail markets to household welfare, underscoring the importance of targeted policy responses. By linking national price and trade disruptions directly to household outcomes, the paper offers a concrete evidence-based framework to guide interventions aimed at mitigating the welfare costs of macroeconomic shocks.