Summer Crops Research Articles

Drought stress mitigation and improved yield in Glycine max through foliar application of zinc oxide nanoparticles.

The impact of climate change on agricultural production is apparent due to declining irrigation water availability vis-à-vis rising drought stress, particularly affecting summer crops. Growing evidence suggests that zinc (Zn) supplementation may serve as a potential drought stress management strategy in agriculture. Field studies were conducted using soybean (Glycine max var. Saba) as a model crop to test whether foliar application of zinc oxide nanoparticles (ZnO-NPs) or conventional Zn fertilizer (ZnSO4) would mitigate drought-related water stress and improve soybean yield. Each fertilizer was foliar applied twice at a two-week interval during the flowering stage. Experiments were concurrently conducted under non-drought conditions (70% field capacity) for comparison. Results showed drought significantly reduced relative water content, chlorophyll-a, and chlorophyll-b in untreated control plants by 35.7%, 47.7%, and 41.4%, respectively, compared to non-drought conditions (p < 0.05). Under drought conditions, ZnO-NPs (200mg Zn/L) led to 33.1% and 20.7% increase in chlorophyll-a and chlorophyll-b levels, respectively, compared to ZnSO4 at 400mg Zn/L. Likewise, catalase, peroxidase and superoxide dismutase activities increased by 62.6%, 39.5% and 28.5%, respectively, with ZnO-NPs (200mg Zn/L) under drought compared to non-drought conditions. Proline was significantly increased under drought but was remarkably suppressed (~ 54% lower) with ZnO-NPs (200mg Zn/L) treatment. More importantly, the highest seed yield was observed with ZnO-NPs (200mg Zn/L) treatment under drought (39% higher than untreated control) and non-drought (79.4% higher than control) conditions. Overall, the findings suggest that ZnO-NPs could promote seed yield in soybean under drought stress via increased antioxidant activities, increased relative water content, decreased stress-related proline content, and increased photosynthetic pigments. It is recommended that foliar application of 200mg Zn/L as ZnO-NPs could serve as an effective drought stress management strategy to improve soybean yield.

Projecting impacts of extreme weather events on crop yields using LASSO regression

Extreme weather events are recognized as major drivers of crop yield losses, which threaten food security and farmers’ incomes. Given the increasing frequency and intensity of extreme weather under climate change, it is crucial to quantify the related future yield damages of important crops to inform prospective climate change adaptation planning. In this study, we present a statistical modeling approach to project the changes in crop yields under climate change for eight majorly cultivated field crops in Germany, estimating the impacts of nine types of extreme weather events. To select the most relevant predictors, we apply the least absolute shrinkage and selection operator (LASSO) regression to district-level yield data.The LASSO models select, on average, 62% of the features, which align with well-known biophysical impacts on crops, suggesting that different extremes at various growth stages are relevant for yield prediction. We project on average 2.5-times more severe impacts on summer crops than on winter crops. Under RCP8.5, crop yields experience a mean change from -2.53% to -8.63% in the far future (2069-98) for summer crops and from -0.80% to -2.88% for winter crops, without accounting for CO2 fertilization effects. Heat impacts are identified as the primary driver of yield losses across all crops for 2069-98, while shifting precipitation patterns exacerbate winter and spring waterlogging, and summer and fall drought.Our findings underscore the utility of LASSO regression in identifying relevant drivers for projecting changes in crop yields across multiple crops, crucial for guiding agricultural adaptation. While the present analysis can identify empirical relationships, replicating these findings in biophysical models could provide new insights into the underlying processes.

Population structure and markers analysis associated with powdery mildew resistance in pumpkin, Cucurbita pepo L

Pumpkin (Cucurbita pepo L.) is an economically important vegetable and summer crop. The seeds have high nutritional value due to their edible oil and protein content with a high medicinal value. Pumpkin is attacked by several fungal diseases; one of which is powdery mildew (PM) caused by Podosphaera xanthii race-0. PM causes severe disease on pumpkin leading to major yield losses globally. In this study, we analyzed the genetic diversity and population structure of fourteen local pumpkin cultivars, all under Cucurbita pepo L. based on dominance in the region using 15 Inter-Simple-Sequence-Repeats-(ISSR) primer-pairs in association with resistance against PM as well as regulating the expression of three resistant marker genes i.e. SGT1, bHLH and PSK via qRT-PCR at three stages with 10 days' interval post-inoculation-stages-(SPI) with the powdery mildew agent, P. xanthii race-0. The results showed that ISSR markers demonstrated 13 primers out of 15 primers generated 169 distinct amplified bands, out of which 143 bands showed polymorphism. The mean polymorphism information content (PIC), marker index (MI), effective-number of alleles (I), expected heterozygosity (H), and Nei's gene diversity parameters were 0.354, 3.344, 0.334, 0.205 and 0.200, respectively. According to PIC, MI, I, H, and Nei indices evaluation, ISSR10 primer had the best performance in genetic diversity of the related pumpkin population. NTSYS pc 2.02e software and several similarity coefficients (r = 0.964), placed the related genotypes into five distinct groups. Of which, ‘Maragheh1′ and ‘Shahreza’ as resistant ones with 9.4 % and 6.1 % disease severity (DS), and ‘Gorgan’, ‘Urmia1′ and 3 and ‘Maragheh3’ with 79.6–84.8 % DS, as susceptible ones into two distinct groups, respectively. Further, the marker genes SGT1, bHLH and PSK expression level changes showed that the effect of variable factors including different genotypes (susceptible and resistant), disease-causing fungus, SPI, and the mutual effect of these factors is significant with the highest increase in resistant genotypes. Considering the relative compatibility in the classification of pumpkin genotypes in the dendrograms of DS and ISSR markers, it can be expected that increasing the number of markers in evaluating the genetic diversity of these genotypes makes it possible to differentiate pumpkin genotypes resistant and susceptible to PM disease based on the degree of disease resistance. The markers associated with resistance are recommended for use in marker assisted breeding.

Agronomic adaptations to heat stress: Sowing summer crops earlier

CONTEXTSummer crops are exposed to heat and drought stresses at critical stages during and after flowering, and their intensity and frequency are likely to increase with climate change. Agronomic stress avoidance offers the opportunity to temporally separate critical crop stages from heat and drought events. However, it might require sowing cold-sensitive summer crops earlier into colder than recommended soil temperatures. There is a need to understand how cold is too cold to sow summer crops early in late winter as well as what are the yield benefits and risks. OBJECTIVEHere, we quantify the likely benefits and trade-offs of sowing sorghum, a summer cereal, earlier to adapt to the increased frequency and intensity of heat and water stresses during flowering and grain filling. METHODSTwo years of multi-environment (n=32) genotype by management trials were conducted across the main sorghum growing regions of Australia. Environments (E) consisted of the combination of years, sites, three times of sowing (early, spring, and summer), and the use of supplementary irrigation. At each E a factorial combination of four plant populations (M) and eight commercial sorghum hybrids (G) were sown with three replications. Crop growth and yield components were measured, and the APSIM model was used to simulate all trials and treatments to quantify risks and derive insights into functional relationships between simulated and measured environmental covariates, and measured crop traits. RESULTSThe tested hybrids showed small differences in cold tolerance during crop establishment. Across the tested environments, the G×M combinations produced up to 60% variation in treatment yields across environment yields, which varied between <0.5 to about 10t ha-1; this translated into a ~5.5-fold variation in water use efficiency. Significant G×E and M×E interactions were observed for grain yield components. No G×M or G×E×M interactions were observed on yield or yield components. Early sowing was associated with a reduced risk of heat stress and water use transfer from vegetative to reproductive stages. Early sowing in late winter or early spring resulted in no significant yield gain or loss when all sites and years were included in the analysis. However, early sowing yielded between 1-2 t ha-1 more when the hottest sites and years were considered separately. This resulted from both the avoidance of heat stresses and milder or no terminal drought stresses. CONCLUSIONSEarly sowing of sorghum can reduce the likelihood of heat stresses around flowering as well as the likelihood of terminal drought stresses. Advantages include reduced yield losses in the hottest years and a transfer of water use to grain filling stages, resulting in increased grain yield and improved grain quality parameters. IMPLICATIONSEarly sowing, an agronomic adaptation, offers the opportunity to quickly adapt to the increase in the frequency and intensity of extreme hot events during critical crop stages. However, for the practice to be de-risked, there is a need to increase cold and chilling tolerance in sorghum and/or identify interventions that enhance seed germination and seedling vigour when the crop is sown early into cold soils.

Radiation Limits the Yield Potential of Main Crops Under Selected Agrivoltaic Designs—A Case Study of a New Shading Simulation Method

Agrivoltaics (APVs) represent a growing technology in Europe that enables the co-location of energy and food production in the same field. Photosynthesis requires photosynthetic active radiation, which is reduced by the shadows cast on crops by APV panels. The design of the module rows, material, and field orientation significantly influences the radiation distribution on the ground. In this context, we introduce an innovative approach for the effective simulation of the shading effects of various APV designs. We performed an extensive sensitivity analysis of the photovoltaic (PV) geometry influence on the ground-incident radiation and crop growth of selected cultivars. Simulations (2013–2021) for three representative arable crops in eastern Austria (winter wheat, spring barley, and maize) and seven different APV designs that only limited to the shading effect showed that maize and spring barley experienced the greatest annual above-ground biomass and grain yield reduction (up to 25%), with significant differences between the APV design and the weather conditions. While spring barley had similar decreases within the years, maize was characterized by high variability. Winter wheat had only up to a 10% reduction due to shading and a reduced photosynthetic performance. Cold/humid/cloudy weather during the growing season had more negative yield effects under APVs than dry/hot periods, particularly for summer crops such as maize. The lowest grain yield decline was achieved for all three crops in the APV design in which the modules were oriented to the east at a height of 5 m and mounted on trackers with an inclination of +/−50°. This scenario also resulted in the highest land equivalent ratios (LERs), with values above 1.06. The correct use of a tracker on APV fields is crucial for optimizing agricultural yields and electricity production.

Incidence Angle Normalization of C-Band Radar Backscattering Coefficient over Agricultural Surfaces Using Dynamic Cosine Method

The radar-backscattering coefficient (σ0) depends on surface characteristics and instrumental parameters (wavelength, polarization, and incidence angle). For Sentinel-1 (S1), with incidence angles ranging from 25° to 45°, σ0 for similar targets typically differs by a few dB depending on their localization in the S1 swath. Overcoming this angular dependence is crucial for the operational applications of radar data. In theory, σ0 follows a cosine function with an exponent “N” that represents the degree of dependence between σ0 and the incidence angle. In order to reduce the effect of the incidence angle on σ0, dynamic N normalizations based on vegetation descriptors, NDVI and SAR Ratio (VV/VH), were applied and then compared to the results obtained with temporally fixed N normalizations. N was estimated at each S1 date during the period of the study for three main summer crops: corn, soybean, and sunflower. Analysis shows that the angular dependence of the S1 σ0 is similar for all three crops. N varies from 3.0 for low NDVI values to 2.0 for high NDVI values (stage of maximal vegetation development) in the VV polarization and from 2.5 to 1.5 for the VH polarization. Furthermore, N fluctuates strongly during the periods before plant emergence and after harvesting, due to variations in the soil roughness. Finally, the results demonstrated that the dynamic normalization of σ0 significantly reduces its angular dependence compared to fixed N (N = 1 and N = 2), with SAR ratio-based normalization performing similarly to NDVI-based normalization.

Factors Influencing the Variation of Plants' Cardinal Temperature: A Case Study in Iran.

The establishment and spread of plants in their native or alien geographical ranges are determined by their germination. This study investigated the impact of different factors on variations in cardinal temperatures. We used the lm procedure and measured the effect size by the Eta-square approach to find the association of different factors (species, ecotypes, origin (native/alien), year, and life cycle) with the cardinal temperatures of 31 species. Our results showed that the base, optimum, and maximum temperatures responded differently to these factors. The base temperature was less impacted by ecotypes compared with the optimum and maximum temperatures, whereas the species had a higher impact on the variation in the base temperature. The effect of the origin of weedy plants on the base temperature was higher than the optimum and maximum temperatures. The effect of the year on the optimum temperature was more prominent than that on the base and maximum temperatures. The results confirmed that weedy alien plants preferred high and narrow ranges of base, optimum, and maximum temperatures and probably will be more problematic in summer crops. The results indicate that alien plants can benefit from warmer conditions in invaded areas at the germination stage. These findings lay the foundation for further studies to elucidate which factors are more important.

Modified QuEChERS sample preparation method and applied for the analysis of 250 pesticide residues in Iran’s summer crops in 2021–2023 applying gas chromatography with mass spectrometry

Modified QuEChERS sample preparation method and applied for the analysis of 250 pesticide residues in Iran’s summer crops in 2021–2023 applying gas chromatography with mass spectrometry

Drought and rewatering practices improve adaptability of seedling maize to drought stress by a super-compensate effect

Periodic drought adversely affects the growth and yield of summer crops in the Huang-Huai-Hai Plain. Drought-rewatering practice as one of the important agronomic measures to improve crop drought resistance. A field experiment was conducted to investigate practice physiological, biochemical, and molecular responses of maize seedling after two rounds of repeated drought and rewatering treatments. The results demonstrated that rewatering following repeated drought events had a compensatory effect on the photosynthetic rate (Pn) and on osmotic and antioxidant regulation. Specifically, the Pn and stomatal conductance (Gs) increased by 10.12% and 5.61%, respectively, compared to the control (CK) during the second round of treatment. Additionally, soluble protein (sPro) and proline (Pro) content rose significantly, with increases of 26.12% and 343.49% observed on day 5 of the second round, leading to a gradual reduction in leaf water content and osmosis. Following drought exposure, the activities of superoxide dismutase (SOD) and peroxidase (POD) contributed to the decreased levels of malondialdehyde (MDA), with both enzymes recovering during rewatering. In contrast, plant height, leaf area, and biomass were significantly reduced in the CK group. Notably, root length increased by 21.05% after the drought-rewatering practice, enhancing the maize seedlings' ability to adapt to drought stress. Overall, maize seedlings exhibited enhanced adaptability to drought conditions following two cycles of drought-rewatering treatments.

Temporal variability of spatial patterns of correlations between summer rainfall and the Oceanic Niño Index in the Pampean region

The Argentinean Pampean region is essential for global food security, known for its extensive production of soybeans, corn, and wheat. The November to January (NDJ) trimester is critical for rainfed summer crops, as precipitation during this period directly affects soil moisture and crop yields. The El Niño-Southern Oscillation (ENSO), particularly its Oceanic Niño Index (ONI), plays a crucial role in influencing precipitation patterns in this region. This study investigates the spatial correlation between the ONI and NDJ precipitation from 1990 to 2021 sing a 20-year sliding window approach. We conducted Pearson correlation and cluster analyses to identify regions with consistent ONI-precipitation relationships. Our findings reveal notable temporal variability, with a general decrease in correlation strength since the window 1995–2014. This decline is likely driven by changes in ENSO dynamics and the influence of other climate variability modes, highlighting the need to consider factors modulating the ONI-precipitation relationship. Notably, the addition of the strong 2015 El Niño, which exhibited inconsistent precipitation behaviour compared to previous strong El Niño events such as 1997, contributed to this weakening. While the 1997 El Niño brought widespread positive rainfall anomalies, the 2015 event was marked by weaker and even negative precipitation anomalies in part of the region. This difference mirrors similar patterns reported in other parts of South America, such as Ecuador and Coastal Peru, and may be linked to a poleward shift in the jet streams during the 2015/2016 El Niño. The results underscore the complexity of ENSO's impact on regional climate and highlight the need for adaptive agricultural planning. By enhancing the understanding of ONI-precipitation dynamics, this study aims to improve long-term climate predictions and support sustainable agricultural practices in the Pampean region.

Tropospheric ozone pollution: Implication for food security and crop nutrition in South Asia

The study was conducted on ambient ozone (O3), the most phyto-toxic air pollutant, and its effects on the growth and quality of okra (Abelmoschus esculentus) and peas (Pisum sativaum) grown in Northern Pakistan during the summer and winter of 2018. Okra was subjected to ambient O3 levels ranging from 43 to 63 ppb during the summer, with a mean O3 concentration of 55 ppb, while peas experienced lower winter concentrations of 15–25 ppb, with a mean O3 concentration of 19 ppb. The results indicated significant impacts on the growth and nutritional quality of crops, especially okra. Anti-ozonant ethylene diurea (EDU) was used for soil drenching to protect okra and green peas from O3 damage. Okra showed notable enhancements of 20%, 20%, 29%, and 13% in ash, protein, fiber, and non-fiber carbohydrates (NFE), respectively. Increase in plant height, leaf numbers, pod length, and dry weight was observed in EDU-treated okra plants. Conversely, peas exhibited less variation, although melioration was observed in plant height, pod numbers, length, and weight with EDU treatment. It was concluded that the concentration of ambient O3 in Peshawar is toxic enough to cause significant damage to crop growth and production. The stark difference in O3 impact during different seasons suggests that higher summer concentrations could severely compromise crop quality. This elicits significant concerns regarding food security in South Asia, especially for summer crops that can jeopardize future food security. It is recommended that further research be conducted on the effects of O3 on other regional crops to assess fully its implications for agricultural sustainability in the area.

Classification of Agricultural Crops with Random Forest and Support Vector Machine Algorithms Using Sentinel-2 and Landsat-8 Images

Monitoring crop development and mapping cultivated areas are important for reducing risks to food security due to climate change. Remote sensing techniques contribute significantly to the efficient and effective management of agricultural production. In this study, agricultural fields (sunflower, wheat, maize, oat, chickpea, sugar beet, alfalfa, onion, fallow) and other fields (non-agricultural, pasture, lake) were identified by using Random Forest (RF) and Support Vector Machines (SVM) machine learning algorithms with Sentinel-2 and Landsat-8 images in the area covering Polatlı, Haymana and Gölbaşı districts of Ankara province Multi-temporal images were used to distinguish winter and summer crops, taking into account crop development periods. As a result of classification; the overall accuracy of RF and SVM models with S2 images are 89.5% and 84.6% and kappa coefficients are 0.88 and 0.83, while the overall accuracy of RF and SVM models with L8 images are 79% and 78.1% and kappa coefficients are 0.76 and 0.75. RF model was found to have higher prediction accuracy than SVM. Sentinel-2 imagery has a higher accuracy in all classes compared to Landsat-8, indicating that Sentinel-2 imagery with its high temporal and spatial resolution is more suitable and has a great potential for agricultural crop pattern detection.

Millets and sorghum as promising alternatives to maize for enhancing climate change adaptation strategies in the Mediterranean Basin

ContextClimate change is increasingly requiring the adoption of both climate-resilient alternative crops and sustainable management practices. Millets and sorghum are increasingly recommended as alternatives to maize in addressing these issues, yet there are no studies comparing the environmental impacts of food-crop millets and sorghum with maize, under sustainable management in Mediterranean area. ObjectiveThe present study examined for the first time the environmental and economic impacts, as well as agronomic performances, of rainfed cultivated proso millet, sorghum and maize over a three-year period under challenging climatic conditions in Emilia-Romagna region, Italy. MethodsDifferent kinds of trials were realized during three years of experimentation in one location in Ravenna province. The first trial aimed to compare proso millet, sorghum and maize agronomical performances and water use efficiency in a low-input system. The second trial aimed to compare soil fertility and biodiversity impacts of two different agronomical management systems (low-input and high input) for the summer crops previously described. Soil basic fertility parameters were monitored and ground dwelling arthropods were collected and analyzed using pitfall traps. The last trial of this study intended to evaluate the environmental and economic performances of the previous cereal crops cultivated in the low-input and high-input systems, applying the Life Cycle Assessment (LCA) and the Life Cycle Costing (LCC) methodologies. ResultsBoth organic sorghum and millet showed high potential as viable summer-crop alternatives, not only to organic maize, based on yield, water use efficiency, disease tolerance and weed competition, but also to conventional maize, based on reduced environmental and economic impacts. Positive land impacts including improved beneficial arthropod abundances and preserved soil fertility were evident under organic management. In fact, the comparative LCA and LCC, carried out with primary data from conventionally cultivated maize and sorghum within central-north Italy and the organic experimental field under investigation, showed that the Global Warming and Eutrophication Potential, were comparable between the organically cultivated crops and significantly lower than conventional maize and sorghum. ConclusionsThe results highlighted the potential of sorghum and millet cultivation as rainfed summer-crop alternative to maize in climate-change context, especially in low-input agronomical systems. In particular, under rainfed, organic management over three years, proso millet yielded consistently. ImplicationsUnder the sustainable practices of the present study, proso millet outperformed maize for yield and WUE stability, as well as potential costs saved, related to the production amount per unit area and potential revenue.

Impact of Greenhouse Size on the Growth and Yield of Warm Season Vegetables During the Summer Ladakh, India

No guidelines exist on the size of naturally ventilated passive solar greenhouses in mountain regions, especially above 10,000 feet above mean sea level (AMSL). Two different-sized greenhouses in Ladakh were studied, and it was figured out that a large greenhouse (60 feet in length, 24 feet in width, 9 feet 6 inches in height) was better than a small greenhouse (32 feet in length, 18 feet width, 9 feet 6 inches height) for growing cucumber, capsicum, and brinjal in summer. The mean maximum and minimum temperature of the large greenhouse was 3.6±4.1°C and 1.3±1.6°C warmer in comparison to the small greenhouse. Cucumber was harvested seven days earlier, while capsicum and brinjal were harvested 17 days earlier in the large greenhouse. The marketable fruit numbers in cucumber, capsicum, and brinjal were 50.5 %, 46.9 %, and 67.7 % higher in the large greenhouse. The average marketable fruit yield of cucumber, capsicum and brinjal was 112 %, 55 % and 71.4 % higher in the large greenhouse than in the small greenhouse. Hence, large greenhouses are suggested for high-altitude Ladakh regions for growing warm-season crops in summer.

Quantifying the adoption of conservation agriculture: Development and application of the Conservation Agriculture Appraisal Index

CONTEXTEstimates of conservation agriculture (CA) adoption vary worldwide because of a lack of a standardized methodology to quantify the simultaneous utilization of its core principles of minimum soil disturbance, permanent soil organic cover and crop diversification. Comparisons of CA adoption among farms across regions requires estimation of the farm area and cropping season where CA principles are applied. OBJECTIVETo develop the Conservation Agriculture Appraisal Index (CAAI) as a standardized conceptual framework with defined thresholds that indicates the intensity and frequency of use of each CA core principle. CAAI was subsequently applied to quantify CA adoption on farms across four wheat (triticum aestivum) growing regions, both with and without livestock, including dryland and irrigated systems in Australia and Mexico, respectively. METHODSCAAI is a continuous scoring system that estimates the intensity and frequency of application of the core principles and their concurrent utilization to assess the extent of CA adoption. CAAI score is the sum of the scores of each core principle, accounting for the percentage of the farm area and cropping season where CA is applied. CAAI emerged from semi-structured interviews, questionnaires, and farm visits that captured underlying patterns of CA use in regional-specific contexts. RESULTS AND CONCLUSIONSCAAI assessed annual CA adoption on 100 farms in four wheat growing regions with different environments and farming systems. The adoption of CA was higher in Australia than Mexico, where partial adoption was more prevalent, especially for summer crops. ‘No adoption’ of CA occurred when one of the core principles consistently scored zero within a year. SIGNIFICANCEThe CAAI can be used as a benchmarking research tool at the farm level to standardize units for comparisons and identify levels of CA adoption by farm area and cropping seasons between and across regions.

Comparative Study of the Impacts of Maize and Soybean on Soil and Water Conservation Benefits during Different Growth Stages in the Loess Plateau Region

Maize (Zea mays L.) and soybean (Glycine max L. Merr.) are prevalent summer crops planted widely in the Loess Plateau region of China, which is particularly susceptible to severe soil erosion on the sloping farmland. However, which crop exhibits superior soil and water conservation capabilities while maintaining economic viability, and how their performance in soil and water conservation is affected by slope gradient and rainfall intensity remains unclear. The objective of this study was to compare the impacts of maize and soybean on regulating runoff and sediment through rainfall simulation experiments, and explore the main control factors of soil and water conservation benefits. Five slope gradients (8.7, 17.6, 26.8, 36.4, and 46.6%) and two rainfall intensities (40 and 80 mm h−1) were applied at five respective crop growth stages. Both maize and soybean effectively reduced soil and water losses compared with bare ground, although increasing slope gradient and rainfall intensity weakened the vegetation effect. Compared with slope gradient and rainfall intensity, vegetation coverage was the main factor affecting the performance of maize and soybean in conserving soil and water. The average time delay benefit (TDB), runoff reduction benefit (RRB), and sediment reduction benefit (SRB) of soybean (246.48 ± 11.71, 36.34 ± 2.51, and 54.41 ± 3.42%) were significantly higher (p &lt; 0.05) than those of maize (100.06 ± 6.81, 25.71 ± 1.76, and 43.70 ± 2.91%, respectively) throughout growth. After planting, the increasing rates of vegetation coverage, TDB, RRB, and SRB with time were consistently higher with soybean than maize. Moreover, under the same vegetation coverage, the TDB, RRB, and SRB of soybean were also consistently higher than those of maize. In conclusion, these findings indicate that soybean outperformed maize in terms of soil and water conservation benefits under the experimental conditions, making it more suitable for cultivation on sloping farmland. This finding offers crucial guidance for the cultivation of dry farming in regions plagued by severe soil erosion, facilitating a balance between economic objectives and ecological imperatives.

Optimal Planting Time for Summer Tomatoes (Lycopersicon esculentum Mill.) Cropping in Korea: Growth, Yield, and Photosynthetic Efficiency in a Semi-Closed Greenhouse.

In Korea, greenhouses are traditionally used for crop cultivation in the winter. However, due to diverse consumer demands, climate change, and advancements in agricultural technology, more farms are aiming for year-round production. Nonetheless, summer cropping poses challenges such as high temperatures, humidity from the monsoon season, and low light conditions, which make it difficult to grow crops. Therefore, this study aimed to determine the best planting time for summer tomato cultivation in a Korean semi-closed greenhouse that can be both air-conditioned and heated. The experiment was conducted in the Advanced Digital Greenhouse, built by the National Institute of Agricultural Sciences. The tomato seedlings were planted in April, May, and June 2022. Growth parameters such as stem diameter, flowering position, stem growth rate, and leaf shape index were measured, and harvesting was carried out once or twice weekly per treatment from 65 days to 265 days after planting. The light use efficiency and yield per unit area at each planting time was measured. Tomatoes planted in April showed a maximum of 42.9% higher light use efficiency for fruit production and a maximum of 33.3% higher yield. Furthermore, the growth form of the crops was closest to the reproductive growth type. Therefore, among April, May, and June, April is considered the most suitable planting time for summer cultivation, which is expected to contribute to reducing labor costs due to decreased workload and increasing farm income through increased yields. Future research should explore optimizing greenhouse microclimates and developing crop varieties tailored for summer cultivation to further enhance productivity and sustainability in year-round agricultural practices.

Conservation and Utilization of Summer Crops Biodiversity in Nepal

Nepal faces a pressing challenge with the alarming loss of around 50% of its summer crop genetic resources (SCGRs) and the endangerment of native landraces. To combat this decline, the national genebank in Nepal has developed 101 good practices for agricultural genetic resources (AGRs) conservation and utilization. Red zoning and red listing strategies aid in identifying conservation priorities. The Genebank collaborates with stakeholders to collect, characterize, and promote SCGRs, resulting in 6177 accessions representing 71 summer crop species stored in Seed Banks. Diverse conservation repositories include genebanks, tissue banks, DNA banks, community genebanks, school field genebanks, and agro-gene sanctuaries. In 2022, 724 accessions of 20 summer crops were distributed for research, while the registration of 19 landraces after genetic enhancements led to their inclusion under the National Seed Board. The free distribution of germplasm accelerates its utilization, further facilitated by online access. The genebank also promotes agro-insect field genebanks recognizing the importance of agro-insects and pollinators in biodiversity conservation. To maintain native SCGRs, value additions are emphasized, underlining the need to actively enhance genetic diversity in agricultural fields. These comprehensive measures underscore Nepal’s commitment to safeguarding agrobiodiversity, ensuring food security, and bolstering agricultural resilience to climate and other stresses.

Contribution of the postharvest period to soil N2O emissions from arable Mediterranean crops

Soil nitrous oxide (N2O) emissions are a relevant contributor to the global warming potential of Mediterranean agro-ecosystems and therefore should be accurately quantified. Here, we investigated the quantitative relevance of considering postharvest N2O measurements when calculating annual soil N2O emissions from herbaceous crops (excluding rice). Data from 25 studies conducted in Mediterranean climates were compiled from a variety of crops and cropping systems, soil types, tillage practices, and nitrogen (N) fertilizer management practices. The differences between cumulative N2O emissions in the cropping period (preharvest emissions) and in the postharvest period were evaluated through a meta-analysis, as were the maximum N2O peaks in both periods and the resultant N2O emission factors (EFs). The relative contribution of the postharvest period to total cumulative N2O emissions was a mean 26%, but showed high variability. The average N2O EFs in the field experiments included in this study were 0.21% and 0.27% when not considering and when considering the postharvest period, respectively. The relative and absolute contribution of postharvest emissions was significantly greater for winter cereals than for either horticultural crops or maize. The maximum preharvest fluxes were higher than the maximum postharvest fluxes in 72% of the observations, but notable postharvest N2O peaks after soil rewetting were obtained in some studies. On average, postharvest emissions in nonfertilized plots were similar to those in fertilized winter crops. Other factors such as N source (greater relevance for organic fertilizers, particularly in summer crops), N rate, tillage intensity and soil texture significantly affected the amount of postharvest emissions. Taking measurements during the postharvest period in Mediterranean cropping systems are encouraged in studies that include winter crops, use of organic fertilizers or have unbalanced N rates. Our results may contribute to improving N2O measurement protocols and to re-evaluating N2O EFs in Mediterranean and semiarid areas.

Assessment of the impact of observations at Nainital (India) and Comilla (Bangladesh) on the CH4 flux inversion

Methane emission in South Asia is poorly understood due to a lack of observations, despite being a major contributor to methane emissions globally. We present the first results of atmospheric CH4 inversions using air samples collected weekly at Nainital, India (NTL), and Comilla, Bangladesh (CLA), in addition to surface background flask measurements by NOAA, CSIRO and AGAGE using the MIROC4-ACTM. Our simulations span from 2000 to 2020 (considering the fixed “edge” effect), but the main analysis period is 2013–2020, when both the NTL and CLA datasets are available. An additional flux uncertainty reduction of up to 40% was obtained (mainly in the northern part of the Indian subcontinent), which enhanced our confidence in flux estimation and reaffirmed the significance of observations at the NTL and CLA sites. Our estimated regional flux was 64.0 ± 4.7 Tg-CH4 yr−1 in South Asia for the period 2013–2020. We considered two combinations of a priori fluxes that represented different approaches for CH4 emission from rice fields and wetlands. By the inversion, the difference in emissions between these combinations was notably reduced due to the adjustment of the CH4 emission from the agriculture, oil and gas, and waste sectors. At the same time, the discrepancy in wetland emissions, approximately 8 Tg-CH4 yr−1, remained unchanged. In addition to adjusting the annual totals, the inclusion of NTL/CLA observations in the inversion analysis modified the seasonal cycle of total fluxes, possibly due to the agricultural sector. While the a priori fluxes consisted of a single peak in August, the a posteriori values indicated double peaks in May and September. These peaks are highly likely associated with field preparation for summer crops and emissions from rice fields during the heading stage (panicle formation). The newly incorporated sites primarily exhibit sensitivity to the Indo-Gangetic Plain subregion, while coverage in southern India remains limited. Expanding the observation network is necessary, with careful analysis of potential locations using back-trajectory methods for footprint evaluation.