Affect Crop Yield Research Articles

Water and nitrogen supply at spatially distinct locations improves cotton water productivity and nitrogen use efficiency and yield under drip irrigation

The location of water and fertilizer supply directly affects the distribution of soil moisture and nutrients, thereby affecting crop yield and fertilizer use efficiency. However, the impact of water and nitrogen (N) supply location on cotton water and N use efficiency and yield is not yet clear, especially under drip irrigation conditions. A field experiment was conducted in 2022 and 2023. Four water and N supply patterns were set as: water and N supply at the same location (narrow row (PN) or wide row (PW)), water and N supply at spatially distinct (SD) and spatially and temporally distinct locations (STD). Soil water and N leaching, cotton root growth, water productivity (WP) and recovery efficiency of N (REN), and yield were quantified. The soil moisture and NO3--N vertical distribution range (0-60cm) were deeper at the same location for water and N supply than at spatially distinct locations for water and N supply (0-40cm). Compared to water and N supply at the same location, supply at spatially distinct locations significantly increased cotton root weight, root length density, and root surface area. In addition, water and NO3--N leaching of water and N supply at spatially distinct (SD and STD) were 12%-50% and 32%-59% lower, respectively, than those from the same location (PN and PW), while the yield and WP increased significantly by 7%-11% and 7%-10%, respectively. The REN of water and N supply at spatially and temporally distinct locations was the highest. Therefore, water and N supply at spatially distinct or spatially and temporally distinct locations can improve water productivity, recovery efficiency of N, and yield of cotton, and reduce soil water and N leaching loss under drip irrigation.

The AGAMOUS-LIKE 16-GENERAL REGULATORY FACTOR 1 module regulates axillary bud outgrowth via catabolism of abscisic acid in cucumber.

Lateral branches are important components of shoot architecture and directly affect crop yield and production cost. Although sporadic studies have implicated abscisic acid (ABA) biosynthesis in axillary bud outgrowth, the function of ABA catabolism and its upstream regulators in shoot branching remain elusive. Here, we showed that the MADS-box transcription factor AGAMOUS-LIKE 16 (CsAGL16) is a positive regulator of axillary bud outgrowth in cucumber (Cucumis sativus). Functional disruption of CsAGL16 led to reduced bud outgrowth, whereas overexpression of CsAGL16 resulted in enhanced branching. CsAGL16 directly binds to the promoter of the ABA 8'-hydroxylase gene CsCYP707A4 and promotes its expression. Loss of CsCYP707A4 function inhibited axillary bud outgrowth and increased ABA levels. Elevated expression of CsCYP707A4 or treatment with an ABA biosynthesis inhibitor largely rescued the Csagl16 mutant phenotype. Moreover, cucumber General Regulatory Factor 1 (CsGRF1) interacts with CsAGL16 and antagonizes CsAGL16-mediated CsCYP707A4 activation. Disruption of CsGRF1 resulted in elongated branches and decreased ABA levels in the axillary buds. The Csagl16 Csgrf1 double mutant exhibited a branching phenotype resembling that of the Csagl16 single mutant. Therefore, our data suggest that the CsAGL16-CsGRF1 module regulates axillary bud outgrowth via CsCYP707A4-mediated ABA catabolism in cucumber. Our findings provide a strategy to manipulate ABA levels in axillary buds during crop breeding to produce desirable branching phenotypes.

Driving soil N2O emissions under nitrogen application by soil environmental factor changes in garlic-maize rotation systems

In multiple cropping systems, optimizing nitrogen (N) input can mitigate N2O emissions and sustain agricultural productivity in frequently disturbed environments. Nonetheless, there remains a notable gap in understanding the role of soil environment in the N application process. Hence, a three-annual field experiment spanning six growth seasons from 2019 to 2022 was conducted to assess the impacts of surface water filled-pore space (WFPS), NO3−−N, and meteorological factors under combined N applications during garlic (G: 300 and 240 kg N ha−1) and maize seasons (M: 220, 175, and 130 kg N ha−1) on soil N2O emissions and crop yields. The findings showed that reducing the annual N application rate by 45−150 kg ha−1 led to a significant decrease in N2O emission flux by 27.7%−69.4% and 30.7%−53.6% in maize and garlic season respectively, compared to conventional N application (G300M220). However, decreasing N application notably reduced garlic yield by 4.5–22.8%. Furthermore, reducing annual N application decreased net environmental and diminished net environmental and economic benefits (NEEB) by 3.7%−28.9%. Multiple regression analysis demonstrated that the residual NO3–−N in the soil before nitrogen application significantly influenced short-term N2O emissions post-application, while WFPS exerting a more pronounced effect during the maize season. Precipitation and temperature exhibited contrasting impacts on N2O emissions in the two crop seasons. Principal component analysis revealed that supplemental irrigation enhances crop yield in the maize growing season but also exacerbated N2O emissions due to the alternation of dry and wet conditions. Precipitation in the garlic growing season emerged as a crucial meteorological factor affecting crop yield and N2O emissions. The NEEB analysis suggested that reducing 45 kg N ha−1 in the maize season (G300M175) represents a more balanced N application approach to mitigate productivity and environmental risks in rotation systems. Therefore, accounting for the stimulating effect of soil environmental factors during the short-term N application process, adjusting irrigation practices based on seasonal precipitation and temperature variations can enhance productivity and reduce gaseous nitrogen losses in multiple cropping systems within semi-arid regions.

Effects of biochar in combination with cattle slurry and mineral nitrogen on crop yield and nitrogen use efficiency in a three-year field experiment

Applying biochar can improve soil characteristics and functions, resulting in significant increases in yield in tropical soils. However, whether biochar can boost soil yield in temperate climates with high soil fertility is mostly unknown. The optimal biochar application rates and combinations with organic and mineral nitrogen (N) fertilizers remain to be determined. To address this research gap, a factorial three-year field experiment in southern Germany was conducted using mineral N fertilizer (0, 60, 120, and 180 kg ha−1 a−1), and biochar (0, 500, and 1000 kg ha−1 a−1 biochar C) mixed with cattle slurry before application (0 and 100 kg ha−1 a−1 slurry N). The effects on crop (silage maize, winter wheat, and winter barley) yield, N uptake, and N use efficiency were studied. Spectral measurements were taken at selected growth stages, and the vegetation index REIP (Red-Edge Inflection Point) was calculated.The silage maize dry matter yield reached 27.2 t ha−1 while the winter wheat and winter barley grain yield reached 10.4 t ha−1, and 9.6 t ha−1, respectively. Biochar consistently, but mostly non-significantly, decreased crop yield (e.g., winter wheat, 5.09, 4.74, and 4.50 t ha−1) and N uptake (74.3, 70.8, and 67.4 kg ha−1) at biochar C rates of 0, 500, and 1000 kg ha−1 a−1 when biochar was mixed with cattle slurry before field application in treatments without mineral N input in all trial years. In the third trial year, the biochar-related yield reductions were significant. Consequently, N use efficiency decreased slightly but significantly. At high additional mineral N fertilizer rates no yield-reducing effects were observed. Biochar applied alone (without cattle slurry or mineral N fertilizer) did not affect crop yield. Positive yield effects of biochar were not observed in any of the trial years.The vegetation index REIP decreased non-significantly with increasing biochar addition to cattle slurry in all three years and correlated very closely (up to r = 0.97) with crop yield.The results show that the yield effect of biochar depends on the combination with organic and mineral fertilizers. The derivation of optimal ratios of biochar, cattle slurry and mineral fertilizer requires further investigation. Based on the yield effects, however, it can be deduced that the more biochar is used, the higher the compensation with nitrogen fertilizer must be to maintain the yield level.

Impact of Climate Change on Agriculture: A Review

Climate change presents unprecedented challenges to global agriculture, affecting crop yields, livestock productivity, water availability, soil health, and ecosystem stability. This review examines the multifaceted impacts of climate change on agriculture, encompassing changes in temperature, precipitation patterns, extreme weather events, pest and disease dynamics, and soil degradation. Through synthesizing existing literature, the review elucidates the complex interactions between climate change and agricultural systems, highlighting the implications for food security, rural livelihoods, and environmental sustainability. Furthermore, the review discusses adaptive strategies, policy interventions, and technological innovations aimed at enhancing agricultural resilience and mitigating the adverse effects of climate change on agriculture.

Influence of Bacillus subtilis strain Z-14 on microbial ecology of cucumber rhizospheric vermiculite infested with fusarium oxysporum f. sp. cucumerinum

Fusarium oxysporum (FO) is a typical soil-borne pathogenic fungus, and the cucumber wilt disease caused by F. oxysporum f. sp. cucumerinum (FOC) seriously affects crop yield and quality. Vermiculite is increasingly being used as a culture substrate; nevertheless, studies exploring the effectiveness and mechanisms of biocontrol bacteria in this substrate are limited. In this study, vermiculite was used as a culture substrate to investigate the control effect of Bacillus subtilis strain Z-14 on cucumber wilt and the rhizospheric microecology, focusing on colonization ability, soil microbial diversity, and rhizosphere metabolome. Pot experiments showed that Z-14 effectively colonized the cucumber roots, achieving a controlled efficacy of 61.32% for wilt disease. It significantly increased the abundance of Bacillus and the expression of NRPS and PKS genes, while reducing the abundance of FO in the rhizosphere. Microbial diversity sequencing showed that Z-14 reduced the richness and diversity of the rhizosphere bacterial community, increased the richness and diversity of the fungal community, and alleviated the effect of FO on the community structure of the cucumber rhizosphere. The metabolomics analysis revealed that Z-14 affected ABC transporters, amino acid synthesis, and the biosynthesis of plant secondary metabolites. Additionally, Z-14 increased the contents of phenylacetic acid, capsidol, and quinolinic acid, all of which were related to the antagonistic activity in the rhizosphere. Z-14 exhibited a significant control effect on cucumber wilt and influenced the microflora and metabolites in rhizospheric vermiculite, providing a theoretical basis for further understanding the control effect and mechanism of cucumber wilt in different culture substrates.

A dual-branch neural network for crop disease recognition by integrating frequency domain and spatial domain information

Crop diseases severely affect crop yield and quality, and accurate identification of crop diseases is crucial for disease management. Although deep neural networks have made progress in the task of crop disease identification, the complex environment of crop diseases, including background interference, morphological differences, and scale variations, has led to limited accuracy in disease recognition. To address these issues, this study proposes a dual-branch deep neural network for crop disease identification, integrating both frequency domain and spatial domain information. The frequency branch takes frequency domain information as input to extract rich crop disease frequency component features, while the deformable attention Transformer branch excels in representing global features and selectively focusing on local features of crop diseases. A new fusion method, Multi-Spectral Channel Attention Fusion (MSAF), is adopted to better integrate crop disease frequency and spatial features. Additionally, an improved bias loss function (cv_bias) is proposed to optimize the dual-branch network model, achieving an accuracy of 96.7 % on the test dataset, which is 2.0 % higher than the existing state-of-the-art deformable attention Transformer model. With only 14 M model parameters, this study's model provides an effective method for future applications in complex environment.

Strip tillage promotes crop yield in comparison with no tillage based on a meta-analysis

Conservation tillage (e.g. no tillage, minimum tillage) is regarded as an effective way to maintain sustainable crop productivity and improve soil quality globally. However, the claim that conservation tillage could improve crop yield are still controversial. It is hypothesized that whether conservation tillage increase crop yield in comparison with conventional tillage (CT) depends on the different conservation tillage practices, for example, no tillage (NT) and strip tillage (ST), and different variables including in agronomic managements, climate conditions, and soil properties. Herein, a meta-analysis was conducted to evaluate how tillage practices affect crop yield and which factors dominate yield performance mostly. Based on the 53 published articles with 290 paired-comparisons across the world, the effects of ST vs. CT and ST vs. NT on crop yield were conducted. It was showed that crop yield under ST had an increasing trend compared to that under CT and NT. Especially, ST significantly increased crop yield by 4.81% in contrast with NT, which indicated that ST might be a promising practice of conservation tillage in terms of crop yield. Under the agronomic managements of continuous cropping, multiple cropping, graminaceous crops, and straw removing, ST significantly increased crop yields by 5.40%, 10.29%, 7.66%, and 7.60% compared to NT, respectively. ST achieved significantly higher crop yield by 5.68% on average and 11.63% as compared to NT under all soil texture and neutral soil. Concerning the climate conditions, crop yield significantly increased by 3.64% under ST as compared to NT in cooler area where mean annual temperature (MAT) was lower than 10°C. Importance analysis indicated that cropping system and MAT were the key factors affecting the performance of tillage practice on crop yield. Overall, present study revealed that ST might be a favorable conservation tillage practice in continuous and multiple cropping systems with graminaceous crop (e.g. maize) in cooler (MAT <10℃) region in terms of yield promotion. This meta-analysis study demonstrated the importance of conservation tillage optimization for food safety and sustainable development of agriculture.

Response of maize yield to changes in soil organic matter in a Swedish long‐term experiment

AbstractAgricultural practices that lead to soil carbon sequestration may be a win–win strategy for mitigating global warming and improving soil fertility and resource use efficiency. The mechanisms through which soil organic carbon (SOC) concentration affects crop yields are numerous but difficult to separate. The objective of this study was to disentangle these processes and estimate to what extent the yield response to SOC is mainly driven by changes in physical or biochemical properties and processes. This was achieved by analysing the response of yields in continuous maize to SOC concentrations during 20 years (2000–2019), which had evolved in 14 experimental treatments in a Swedish long‐term field experiment at Ultuna since 1956, ranging from 0.94% to 3.65% in the topsoil (0–20 cm). Average maize yields during this period varied between 1.9 and 8.4 Mg dry mass per hectare in the different treatments. The treatments comprise applications of different mineral nitrogen (N) fertilizers and organic amendments and combinations thereof. Our analysis showed that maize yield in the treatments that were not severely limited by nitrogen supply or soil acidity increased by 16% for each percentage unit increase in SOC. We applied the widely used concept of critical N concentration in plant biomass to diagnose the N status in maize in the different treatments (N nutrition index [NNI]) and parameterized a response function between yield and pH (RpH). Dry soil bulk density (BD) was used as a proxy for soil physical properties. These three variables NNI, RpH and BD explained 95% of the variation in maize yields among treatments. Further analysis of the relationship between BD, SOC and plant available water capacity revealed that about two thirds of the yield increases in response to SOC change could be ascribed to associated changes in soil physical properties. Our analysis suggests that the extra storage capacity of water, which increased by up to 15 mm in the topsoil for each unit percentage increase in SOC, was the main driver for the observed yield responses. We conclude that measures for increasing SOC in soils most likely are an effective adaptation strategy for reducing the risk of crop damage during dry spells, which probably are becoming more frequent in the future due to climate change, even in relatively humid climates as in Sweden.

The Impact of Salinity on Crop Yields and the Confrontational Behavior of Transcriptional Regulators, Nanoparticles, and Antioxidant Defensive Mechanisms under Stressful Conditions: A Review.

One of the most significant environmental challenges to crop growth and yield worldwide is soil salinization. Salinity lowers soil solution water potential, causes ionic disequilibrium and specific ion effects, and increases reactive oxygen species (ROS) buildup, causing several physiological and biochemical issues in plants. Plants have developed biological and molecular methods to combat salt stress. Salt-signaling mechanisms regulated by phytohormones may provide additional defense in salty conditions. That discovery helped identify the molecular pathways that underlie zinc-oxide nanoparticle (ZnO-NP)-based salt tolerance in certain plants. It emphasized the need to study processes like transcriptional regulation that govern plants' many physiological responses to such harsh conditions. ZnO-NPs have shown the capability to reduce salinity stress by working with transcription factors (TFs) like AP2/EREBP, WRKYs, NACs, and bZIPs that are released or triggered to stimulate plant cell osmotic pressure-regulating hormones and chemicals. In addition, ZnO-NPs have been shown to reduce the expression of stress markers such as malondialdehyde (MDA) and hydrogen peroxide (H2O2) while also affecting transcriptional factors. Those systems helped maintain protein integrity, selective permeability, photosynthesis, and other physiological processes in salt-stressed plants. This review examined how salt stress affects crop yield and suggested that ZnO-NPs could reduce plant salinity stress instead of osmolytes and plant hormones.

Multi-source information fusion-driven corn yield prediction using the Random Forest from the perspective of Agricultural and Forestry Economic Management

The objective of this study is to promptly and accurately allocate resources, scientifically guide grain distribution, and enhance the precision of crop yield prediction (CYP), particularly for corn, along with ensuring application stability. The digital camera is selected to capture the digital image of a 60 m × 10 m experimental cornfield. Subsequently, the obtained data on corn yield and statistical growth serve as inputs for the multi-source information fusion (MSIF). The study proposes an MSIF-based CYP Random Forest model by amalgamating the fluctuating corn yield dataset. In relation to the spatial variability of the experimental cornfield, the fitting degree and prediction ability of the proposed MSIF-based CYP Random Forest are analyzed, with statistics collected from 1-hectare, 10-hectare, 20-hectare, 30-hectare, and 50-hectare experimental cornfields. Results indicate that the proposed MSIF-based CYP Random Forest model outperforms control models such as support vector machine (SVM) and Long Short-Term Memory (LSTM), achieving the highest prediction accuracy of 89.30%, surpassing SVM and LSTM by approximately 13.44%. Meanwhile, as the experimental field size increases, the proposed model demonstrates higher prediction accuracy, reaching a maximum of 98.71%. This study is anticipated to offer early warnings of potential factors affecting crop yields and to further advocate for the adoption of MSIF-based CYP. These findings hold significant research implications for personnel involved in Agricultural and Forestry Economic Management within the context of developing agricultural economy.

The influence of climatic and environmental variables on sunflower planting season suitability in Tanzania

Crop survival and growth requires identification of correlations between appropriate suitable planting season and relevant climatic and environmental characteristics. Climatic and environmental conditions may cause water and heat stress at critical stages of crop development and thus affecting planting suitability. Consequently, this may affect crop yield and productivity. This study assesses the influence of climate and environmental variables on rain-fed sunflower planting season suitability in Tanzania. Data on rainfall, temperature, slope, elevation, soil and land use/or cover were accessed from publicly available sources using Google Earth Engine. This is a cloud-based geospatial computing platform for remote sensed datasets. Tanzania sunflower production calendar of 2022 was adopted to mark the start and end limits of planting across the country. The default climate and environmental parameters from FAO database were used. In addition, Pearson correlation was used to evaluate the relationship between rainfall, temperature over Normalized Difference Vegetation Index (NDVI) from 2000 to 2020 at five-year interval for January-April and June–September, for high and poor suitability season. The results showed that planting suitability of sunflower in Tanzania is driven more by rainfall than temperature. It was revealed that intra-annual planting suitability increases gradually from short to long- rain season and diminishes towards dry season of the year. January-April planting season window showing highest suitability (41.65%), whereas June–September indicating lowest suitability (0.05%). Though, not statistically significant, rainfall and NDVI were positively correlated with r = 0.65 and 0.75 whereas negative correlation existed between temperature and NDVI with r = -− 0.6 and − 0.77. We recommend sunflower subsector interventions that consider appropriate intra-regional and seasonal diversity as an important adaptive mechanism to ensure high sunflower yields.

Comprehensive phytohormone metabolomic and transcriptomic analysis of tobacco (Nicotiana tabacum) infected by tomato spotted wilt virus (TSWV)

Tomato spotted wilt virus (TSWV) is ranked among the top 10 most destructive viruses globally. It results in abnormal leaf growth, stunting, and even death, significantly affecting crop yield and quality. Phytohormones play a crucial role in regulating plant-virus interactions. However, there is still limited research on the effect of TSWV on phytohormone levels, particularly growth hormones and genes involved in the phytohormone pathway. In our study, we combined phytohormone metabolomics and transcriptomics to examine the impact of TSWV infection on phytohormone content and gene expression profile. Metabolomic results showed that 41 metabolites, including major phytohormones and their precursors and derivatives were significantly altered after 14 days of TSWV inoculation tobacco plants cvK326, with 31 being significantly increased and 10 significantly reduced. Specifically, the levels of abscisic acid (ABA) and jasmonoyl-isoleucine (JA-Ile) were significantly reduced. The levels of indole-3-acetic acid (IAA) have remained unchanged. However, the levels of cytokinin isopentenyladenine (iP) and salicylic acid (SA) significantly increased. The transcriptome analysis revealed 2,746 genes with significant changes in expression. Out of these, 1,072 genes were significantly downregulated, while 1,674 genes were significantly upregulated. Among them, genes involved in ABA synthesis and signaling pathways, such as 9-cis-epoxycarotenoid dioxygenase (NCED), protein phosphatase 2C (PP2C), serine/threonine-protein kinase (SnRK2), and abscisic acid responsive element binding factor (ABF), exhibited significant downregulation. Additionally, expression of the lipoxygenase gene LOX, Jasmonate ZIM domain-containing protein gene JAZ, and transcription factor gene MYC were significantly down-regulated. In the cytokinin pathway, while there were no significant changes in the expression of the cytokinin synthesis genes, a significant downregulation of transcriptionally active factor type-B response regulators (type-B RRs) was observed. In terms of SA synthesis and signaling pathways, the isochorismate synthase gene ICS1 and the pathogenesis-related gene PR1 were significantly upregulated. These results can strengthen the theoretical foundation for understanding the interaction between TSWV and tobacco and provide new insights for the future prevention and control of TSWV.

Magnaporthe oryzae effector AvrPik-D targets a transcription factor WG7 to suppress rice immunity

Rice blast, caused by the fungal pathogen Magnaporthe oryzae, is one of the most devastating diseases for rice crops, significantly affecting crop yield and quality. During the infection process, M. oryzae secretes effector proteins that help in hijacking the host's immune responses to establish infection. However, little is known about the interaction between the effector protein AvrPik-D and the host protein Pikh, and how AvrPik-D increases disease severity to promote infection. In this study, we show that the M. oryzae effector AvrPik-D interacts with the zinc finger-type transcription factor WG7 in the nucleus and promotes its transcriptional activity. Genetic removal (knockout) of the gene WG7 in transgenic rice enhances resistance to M. oryzae and also results in an increased burst of reactive oxygen species after treatments with chitin. In addition, the hormone level of SA and JA, is increased and decreased respectively in WG7 KO plants, indicating that WG7 may negatively mediate resistance through salicylic acid pathway. Conversely, WG7 overexpression lines reduce resistance to M. oryzae. However, WG7 is not required for the Pikh-mediated resistance against rice blast. In conclusion, our results revealed that the M. oryzae effector AvrPik-D targets and promotes transcriptional activity of WG7 to suppress rice innate immunity to facilitate infection.

Analyzing predictors of pearl millet supply chain using an artificial neural network

Purpose The internal (farmer-controlled) and external (non-farmer-controlled) factors affect crop yield. However, not a single study has identified and analyzed yield predictors in India using effective predictive models. Thus, this study aims to investigate how internal and external predictors impact pearl millet yield and Stover yield. Design/methodology/approach Descriptive analytics and artificial neural network are used to investigate the impact of predictors on pearl millet yield and Stover yield. From descriptive analytics, 473 valid responses were collected from semi-arid zone, and the predictors were categorized into internal and external factors. Multi-layer perceptron-neural network (MLP-NN) model was used in Statistical Package for the Social Sciences version 25 to model them. Findings The MLP-NN model reveals that rainfall has the highest normalized importance, followed by irrigation frequency, crop rotation frequency, fertilizers type and temperature. The model has an acceptable goodness of fit because the training and testing methods have average root mean square errors of 0.25 and 0.28, respectively. Also, the model has R2 values of 0.863 and 0.704, respectively, for both pearl millet and Stover yield. Research limitations/implications To the best of the authors’ knowledge, the current study is first of its kind related to impact of predictors of both internal and external factors on pearl millet yield and Stover yield. Originality/value The literature reveals that most studies have estimated crop yield using limited parameters and forecasting approaches. However, this research will examine the impact of various predictors such as internal and external of both yields. The outcomes of the study will help policymakers in developing strategies for stakeholders. The current work will improve pearl millet yield literature.

Quantifying potential trade-offs and win-wins between arthropod diversity and yield on cropland under agri-environment schemes–A meta-analysis

In Europe, agri-environment schemes (AES) are a key instrument to combat the ongoing decline of farmland biodiversity. AES aim is to support biodiversity and maintain ecosystem services, such as pollination or pest control. To what extent AES affect crop yield is still poorly understood. We performed a systematic review, including hierarchical meta-analyses, to investigate potential trade-offs and win-wins between the effectiveness of AES for arthropod diversity and agricultural yield on European croplands. Altogether, we found 26 studies with a total of 125 data points that fulfilled our study inclusion criteria. From each study, we extracted data on biodiversity (arthropod species richness and abundance) and yield for fields with AES management and control fields without AES. The majority of the studies reported significantly higher species richness and abundance of arthropods (especially wild pollinators) in fields with AES (31 % increase), but yields were at the same time significantly lower on fields with AES compared to control fields (21 % decrease). Aside from the opportunity costs, AES that promote out-of-production elements (e.g. wildflower strips), supported biodiversity (29–32 % increase) without significantly compromising yield (2–5 % increase). Farmers can get an even higher yield in these situations than in current conventional agricultural production systems without AES. Thus, our study is useful to identify AES demonstrating benefits for arthropod biodiversity with negligible or relatively low costs regarding yield losses. Further optimization of the design and management of AES is needed to improve their effectiveness in promoting both biodiversity and minimizing crop yield losses.

Respons Tanaman Sawi Hijau (Brassica juncea L.) Pada Pemberian Pupuk Organik Cair Eceng Gondok (Eichhornia crassipes) Dan Pupuk Anorganik

This study aims to determinate the effect of the interaction between water hyacinth (Eichhornia crassipes) liquid organic fertilizer on mustard greens (Brassica juncea) fertilizer that affects the yield of mustard greens and determine the dose of inorganic fertilizer that affects crop yield mustard greens. This research was conducted in the village of Motoling, Kec. Motoling, south Minahasa Regency, North Sulawesi. The design of this study used a factorial randomized block design (RBD) with factor I, namely the dose of water hyacinth liquid organic fertilizer, and factor II, namely the dose of inorganic fertilizer. The variables observed were: plant height, number of leaves, leaf lenght, leaf width and wet weight. The results showed that the interaction between water hyacinth liquid organic fertilizer and inorganic fertilizers had an effect on the fresh weight of mustard green plants and had no effect on plant height, number of leaves, leaf length dan leaf width of mustard green plants.

Benefitting productivity and the environment: Current and future maize cropping systems improve yield while reducing nitrate load.

Increases in cereal crop yield per area have increased global food security. "Era" studies compare historical and modern crop varieties in controlled experimental settings and are routinely used to understand how advances in crop genetics and management affect crop yield. However, to date, no era study has explored how advances in maize (Zea mays L.) genetics and management (i.e., cropping systems) have affected environmental outcomes. Here, we developed a cropping systems era study in Iowa, USA, to examine how yield and nitrate losses have changed from "Old" systems common in the 1990s to "Current" systems common in the 2010s, and to "Future" systems projected to be common in the 2030s. We tested the following hypothesis: If maize yield and nitrogen use efficiency have improved over previous decades, Current and Future maize systems will have benefits to water quality compared to Old systems. We show that not only have maize yield and nitrogen use efficiency (kg grain kg-1 N), on average, improved over time but also yield-scaled nitrate load + soil nitrate was reduced by 74% and 91% from Old to Current and Future systems, respectively. Continuing these trajectories of improvement will be critical to meet the needs of a growing and more affluent population while reducing deleterious effects of agricultural systems on ecosystem services.

Effects of Foliar Selenium Application on Oxidative Damage and Photosynthetic Properties of Greenhouse Tomato under Drought Stress.

Both drought stress and exogenous selenium (Se) cause changes in plant physiological characteristics, which are key factors affecting crop yield. Although Se is known to be drought-resistant for crops, its internal physiological regulatory mechanisms are not clear. This study analyzed the effects of selenium application (SeA) on antioxidant enzyme activities, osmoregulatory substance contents, and photosynthetic characteristics of greenhouse tomatoes under drought stress and related physiological mechanisms. The results showed that drought stress induced oxidative damage in cells and significantly increased the content of the membrane lipidation product malondialdehyde (MDA) and the osmoregulatory substance proline (p < 0.001) compared with the adequate water supply. The proline content of severe drought stress (W1) was 9.7 times higher than that of the adequate water supply (W3), and foliar SeA increased glutathione peroxidase (GSH-PX) activity, and SeA induced different enzymatic reactions in cells under different drought stresses; catalase (CAT) was induced under severe drought stress (p < 0.01) and was significantly increased by 32.1% compared with the clear water control, CAT. Peroxidase (POD) was induced under adequate water supply conditions (p < 0.01), which was significantly increased by 15.2%, and SeA attenuated cell membrane lipidation, which reduced MDA content by an average of 21.5% compared with the clear water control, and also promoted photosynthesis in the crop. Meanwhile, through the entropy weighting method analysis (TOPSIS) of the indexes, the highest comprehensive evaluation score was obtained for the S5W3, followed by the S2.5W3 treatment. Therefore, this study emphasized the importance of SeA to reduce oxidative damage and enhance photosynthesis under drought stress.

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

High concentrations of air pollutants could affect crop yield directly via influencing crop physiology and indirectly via regulating climate conditions. How multiple air pollutants affect crop yields directly and indirectly remains elusive in the North China Plain (NCP), which is the hotspot of air pollution and crop production. Here, we construct data-driven models to quantify the indirect effects of four major air pollutants on the yields of winter wheat and summer maize through modulating climate variations in the NCP during 2005–2020. Our results show that wheat has a greater negative sensitivity to absorbing aerosol optical thickness (AAOD), ozone concentration (O3), sulfur dioxide concentration (SO2) and nitrogen dioxide concentration (NO2) than maize. The indirect effects of AAOD, O3 and SO2 in November and O3 in April control wheat yield variation, while the indirect effects of AAOD and O3 in June, O3 and SO2 in July, O3 and NO2 in August, and O3 in September dominate maize yield variation. Our results emphasize the indirect effects of air pollutants on crop yield via regulating climate variations, which has great implications for improving our understanding of air pollution-climate-crop interactions and guiding targeted adaptation and mitigation efforts.