Improve Crop Yield Research Articles

Optimizing crop monitoring: mapping cultivation stages and types with sentinel-1/2 and random forest algorithm

ABSTRACT Crop-type mapping is essential for agricultural monitoring, improving crop yield models, and supporting sustainable land management. Studying crop phenology, which includes the timing from germination to maturity, is equally important for precise agricultural practices. However, maps detailing crop phenology are scarce. This study addresses this gap by mapping both crop types and cultivation time, offering valuable insights for agriculture applications. The research integrates Sentinel-1/2 data, NDVI phenology curves, and machine learning (ML) algorithms through Google Earth Engine to map crops in El-Behera Governorate, Egypt. By stratifying the region into different soil types, it accounts for various agro-environmental conditions. Field visits in July 2022 provided crop-type information, and Sentinel-2 NDVI curves were used to determine cultivation time. The random forest (RF) classifier, known for its accuracy, was employed, achieving an overall accuracy (OA) of 97.4% for crop type and 95.6% for cultivation time, with high Kappa coefficients. Feature importance analysis highlighted the significance of specific spectral bands, particularly in the Red Edge region, for classification accuracy. Hyperparameter tuning across different zones demonstrated the need for customized tuning. This study enhances understanding of agro-environmental variability’s impact on crop classification and shows the potential of the RF algorithm in advancing crop mapping, suggesting further studies on how shifts in cultivation time could affect crop yield.

CRISPR/Cas system-mediated base editing in crops: recent developments and future prospects.

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (CRISPR/Cas9) genome-editing system has altered plant research by allowing for targeted genome alteration, and they are emerging as powerful tools for evaluating plant gene function and improving crop yield. Even though CRISPR/Cas9 cleavage and subsequent repair are effective ways to precisely replace genes and change base pairs in plants, the dominance of the non-homologous end-joining pathway (NHEJ) and homology-directed repair's (HDR) poor effectiveness in plant cells have restricted their use. Base editing is gaining popularity as a potential alternative to HDR or NHEJ-mediated replacement, allowing for precise changes in the plant genome via programmed conversion of a single base to another without the need for a donor repair template or double-stranded breaks. In this review, we primarily present the mechanisms of base-editing system, including their distinct types such as DNA base editors (cytidine base editor and adenine base editor) and RNA base editors discovered so far. Next, we outline the current potential applications of the base-editing system for crop improvements. Finally, we discuss the limitations and potential future directions of the base-editing system in terms of improving crop quality. We hope that this review will enable the researcher to gain knowledge about base-editing tools and their potential applications in crop improvement.

An optimal global biochar application strategy based on matching biochar and soil properties to reduce global cropland greenhouse gas emissions: findings from a global meta-analysis and density functional theory calculation

Biochar has been extensively utilized to amend soil and mitigate greenhouse gas (GHG) emissions from croplands. However, the effectiveness of biochar application in reducing cropland GHG emissions remains uncertain due to variations in soil properties and environmental conditions across regions. In this study, the impact of biochar surface functional groups on soil GHG emissions was investigated using molecular model calculation. Machine learning (ML) technology was applied to predict the responses of soil GHG emissions and crop yields under different biochar feedstocks and application rates, aiming to determine the optimum biochar application strategies based on specific soil properties and environmental conditions on a global scale. The findings suggest that the functional groups play an essential role in determining biochar surface activity and the soil’s capacity for adsorbing GHGs. ML was an effective method in predicting the changes in soil GHG emissions and crop yield following biochar application. Moreover, poor-fertility soils exhibited greater changes in GHG emissions compared to fertile soil. Implementing an optimized global strategy for biochar application may result in a substantial reduction of 684.25 Tg year−1 CO2 equivalent (equivalent to 7.87% of global cropland GHG emissions) while simultaneously improving crop yields. This study improves our understanding of the interaction between biochar surface properties and soil GHG, confirming the potential of global biochar application strategies in mitigating cropland GHG emissions and addressing global climate degradation. Further research efforts are required to optimize such strategies.Graphical

Effect of Potassium Fertigation Levels on Jalapeno Pepper Growth in Red Bole Soil under Polyhouse Conditions

A field experiment was conducted at Instructional Farm Polyhouse, Dr. Sharadchandra Pawar College of Agriculture, Baramati during June 2023 to September 2023. The study aimed to investigate the Influence of Graded levels of Potassium Fertigation on Growth of Jalapeno Pepper Grown in Red Bole Soil Under Polyhouse. The experiment was laid out in Randomized Block Design (RBD) with four replications. The treatments were five, viz., T1- Control, T2- Recommended dose of fertilizer, T3- Recommended dose of nitrogen and phosphorus (RDNP) + 125% Recommended dose of potassium (RDK), T4- Recommended dose of nitrogen and phosphorus (RDNP) + 150% Recommended dose of potassium (RDK) and T5- Recommended dose of nitrogen and phosphorus (RDNP) + 175% Recommended dose of potassium (RDK). Data were taken on growth contributing characters and the collected data were statistically analyzed for evaluation of the treatment effects. Data on growth parameters, including plant height, leaf area and chlorophyll content, were recorded at 20, 35, 50 and 65 days after transplanting (DAT) and analyzed statistically. The results indicated that the maximum plant height (95.65 cm), leaf area (61.61 dm²) and chlorophyll content (58.83) at 65 DAT were significantly higher in treatment T5 (RDNP + 175% RDK). This study concludes that the application of RDNP + 175% RDK via fertigation from 10 DAT to 60 DAT is optimal for the growth of Jalapeno pepper in red bole soil under polyhouse conditions, highlighting its potential for improving crop yield and quality.

Weighted Gene Co-Expression Network Analysis Uncovers Critical Genes and Pathways Involved in Soybean Response to Soybean Mosaic Virus

Background: Soybean mosaic virus (SMV) is a globally prevalent and detrimental virus that belongs to the Potyvirus genus. Pathogenic viruses of this genus are typically linear in shape, with dimensions ranging between 630 and 750 nm, and are composed of single-stranded RNA and proteins. We have developed an SMV-resistant soybean line, Dongnong 93-046, which has no significant changes in disease resistance identification in the adult plants and has neat grains with no obvious brown or black markings. To explore the defense mechanisms of soybean against SMV, we performed comparative transcriptomic sequencing of the leaves between the Dongnong 93-046 inoculated with SMV at 8 h (T) and the non-inoculated control (C) on the HiSeq2000 platform. In addition, we performed non-targeted metabolomic sequencing of leaves from the treatment and control groups. Results: We identified a total of 41,189 differentially expressed genes (DEGs). A total of 9809 differentially expressed genes (DEGs) met the criteria of |Log2FC (Fold Change)| ≥ 1 and adjusted p-value ≤ 0.001. Among the 41,189 DEGs identified, 9196 exhibited FPKM values greater than 10. KEGG pathway enrichment analysis of the 9809 DEGs revealed significant enrichment of genes involved in resistance-related pathways such as plant–pathogen interaction, linoleic acid metabolism, mitogen-activated protein kinase (MAPK) signaling pathway, and plant hormone signaling transduction. Functional analysis using MapMan software identified multiple DEGs that were associated with pathways such as jasmonate synthesis and phenylpropanoid biosynthesis. Weighted gene co-expression network analysis (WGCNA) using the differential metabolites and the 9196 DEGs revealed a strong correlation between gene clusters within the Turquoise module and the content of jasmonate-related metabolites. Further functional enrichment analysis of the 894 genes within the gene clusters showed a significant and repeated enrichment of pathways related to plant–pathogen interaction, linoleic acid metabolism, and plant hormone signaling transduction. Subsequent focused pathway analysis identified key genes involved in plant hormone signaling transduction pathways, such as the jasmonate ZIM domain protein Glyma.16G010000, the gene Glyma.01G235600 encoding the essential diterpene reductase required for jasmonate synthesis in the jasmonate biosynthesis pathway, and the transcription factor Glyma.02G232600 involved in the plant–pathogen interaction pathway, among others. This study provides a theoretical framework for understanding the resistance mechanism of soybean cultivar Dongnong 93-046 against the SMV N1 strain, offers potential gene resources for breeding soybean varieties with resistance to SMV, and paves the way for new strategies to control SMV infection, enhance resistance, and improve crop yield and quality.

GIS and Bhuvan Data as Tools for Agricultural Development and Economic Empowerment in Pune District

This paper examines the use of Geographic Information Systems (GIS) and Bhuvan data to enhance agricultural development and drive economic empowerment in Pune District, Maharashtra, India. GIS technology has been instrumental in optimizing water management, land utilization, and crop management. Likewise, Bhuvan data plays a critical role in monitoring crop growth, identifying diseases, and evaluating land use patterns. These advancements contribute to improved crop yields and increased profits for farmers. The paper highlights the significant impact of GIS and Bhuvan data in promoting agricultural progress in Pune district and suggests that these tools could be effectively implemented in other regions to achieve similar benefits.

Monitoring Crop Condition at Gield Scales and at a Daily Time Step Using Synthetic Aperture Radar (SAR)

Operations that rely on optically-based Normalized Difference Vegetation Index (NDVI) to track crop productivity, are negatively impacted by cloud cover. In this research, parameters from Synthetic Aperture Radar (SAR) imagery were calibrated to NDVI with the targeted outcome to integrate SAR into Canadian crop monitoring services. Data from fully polarimetric RADARSAT-2 and dual-polarization Sentinel-1B imagery were calibrated to Sentinel-2 NDVI. Random Forest Regression (RFR) and Least Squares Boosting (LSBoost) were tested to calibrate SAR to NDVI (SARcal-NDVI) for six crops (corn, canola, soybeans, wheat, oats and barley). RADARSAT-2 provided the best fit with R2 exceeding 0.84 for canola, 0.87 for wheat and 0.90 for corn and soybeans. Correlations were lower for oats (R2 of 0.72–0.77) and barley (R2 of 0.43–0.64) due to a limited number of fields. Although a global model yielded lower correlations (R2 of 0.80), this model would be easier to implement into operations. Total power, the first and second eigenvalues and VH backscatter were important in reducing model error. The SARcal-NDVI and Growing Degree Days were then integrated into a Crop Structure Dynamic Model to produce daily estimates of crop condition, at field scales. The next step is to test if these daily estimates of crop condition can improve crop yield forecasting for the Canadian agriculture sector.

How biochar curbs the negative impacts of plastic mulching on soil enzymes and microorganisms while elevating crop yields in ridge-furrow systems

Ridge-furrow tillage is an important tillage and yield enhancement method used in dry farming areas; however, the spatial characteristics of the soil microenvironment under ridge-furrow tillage and the response of crop yields to mulching and biochar addition are not known. In this study, we conducted a three-year field experiment in which mulch and biochar, alone or combined, were introduced into ridge-furrow tillage system to explore their interactive effects on soil enzyme activities, bacterial communities, functional genes, and crop yields. The findings reveal significant spatial differences in soil physicochemical composition, enzyme activity, microbial communities, and functional genes under ridge-furrow tillage, which are further exacerbated by the addition of mulching and biochar. Under the premise of ridge-furrow tillage, both mulching and biochar addition reduce the α diversity of bacterial communities. Mulching simplifies the bacterial network, while biochar addition has the opposite effect. Mulching and biochar addition increase the relative abundance of carbon, nitrogen, and phosphorus functional genes and accelerate nutrient cycling, especially on the ridges. Mulching significantly improves crop yield but is detrimental to alkaline phosphatase activity and the abundance of the gene function. The addition of biochar mitigates the harm of mulching and further increases alfalfa yield. These findings not only provide scientific support for optimizing ridge-furrow tillage but also deepen our comprehensive understanding of the soil biochemical environment after the addition of mulching and biochar, further revealing their positive effects on yield formation.

UV-B irradiation promotes anthocyanin biosynthesis in the leaves of Lycium ruthenicum Murray.

Anthocyanins are the most valuable pigments in Lycium ruthenicum Murray (L.ruthenicum). Although ultraviolet-B (UV-B) irradiation is a key environmental factor influencing anthocyanin biosynthesis in L. ruthenicum, the deep molecular mechanism remains unclear. Herein, we examined the changes in the total anthocyanin content and transcriptomic characteristics of L. ruthenicum leaves following UV-B irradiation treatment. The results showed a twofold increase in anthocyanin content in the leaves of L. ruthenicum after the treatment. The transcriptome analysis showed that the expression of 24 structural genes identified in the anthocyanin synthesis pathway was up-regulated. In particular, F3'H (Unigene0009145) and C4H (Unigene0046607) exhibit notable up-regulation, suggesting their potential roles in anthocyanin synthesis. Protein interaction network results revealed that MYB1 (Unigene0047706) had the highest connectivity, followed by bHLH (Unigene0014085). Additionally, UVR8 (Unigene0067978) and COP1 (Unigene0008780) were found to be highly involved in UV-B signal transduction. These findings provide new insights into the genetic and biochemical mechanisms that regulate anthocyanin production, and could guide agricultural practices to reduce environmental impacts and improve crop yield and quality.

Exploring the use of POLY4 for the improvement of productivity, peanut quality, and soil properties in Southern India.

Polyhalite-based POLY4, a multi-nutrient source containing potassium, calcium, magnesium, and sulphur, is increasingly recognised for its potential to improve crop yields and soil health in agricultural systems. It is also been considered as a feasible approach for addressing the deficiency in potassium, calcium, and sulphur within a single application source. The present study aimed to investigate the impact of polyhalite-based POLY4 application, either as a complete or partial substitute for traditional potassium fertiliser and gypsum supplement, on the improvement of peanut (Arachis hypogaea) growth and soil quality. An extensive field study was conducted from 2021 and 2022, employing ten distinct nutrient management treatments with three replications in a randomised complete block design. The findings of the study indicated that the application of polyhalite (POLY4) in conjunction with only NP fertilisers resulted in a higher yield advantage (approximately 150-200 kg ha-1) than in plots treated with NPK + gypsum (at 500 kg ha-1) and control plots. The application of polyhalite-based fertiliser (POLY4) at a rate that was 100% equivalent to K along with NP fertilisers resulted in a significant increase in pod yield (5.3-12.8%) over NPK + gypsum and control plots. Thus, the increased crop yield led to an increase in gross returns of 4.88% and in net returns of 4.28% with the application of POLY4 (100%) + NP fertilisers over other treatments. Likewise, variable rates of conventional fertilisers along with POLY4 (100% recommended) + NP + gypsum at 310 kg/ha significantly increased the linoleic acid content (38.5%), oleic acid content, and oil content (48.1%) by reducing palmitic acid (11.96%) content in the groundnut seed. Interestingly, POLY4 use at the 50% recommended rate also resulted in yields that were comparable with those obtained with 100% NPK. Therefore, applying POLY4, a polyhalite fertiliser, in either a 100% or 50% equivalent of essential K can be an effective way of increasing the production of peanut crops and promoting agricultural sustainability.

Optimization of water and nitrogen management in wheat cultivation affected by biochar application − Insights into resource utilization and economic benefits

In the context of global climate change and natural resource scarcity, agricultural production is facing multiple challenges in improving crop yields and optimizing natural resource use. It is of great practical significance to optimize agricultural practices to achieve sustainable agricultural development. In this study, a two-year winter wheat field experiment was conducted in the Guanzhong Plain, Shaanxi, China, from 2020 to 2022 to assess the effects of biochar, irrigation, and N fertilizer rates on the yield, water-nitrogen use efficiency, and economic benefits of winter wheat. Specifically, biochar was applied to winter wheat at 30 t ha−1 in combination with two irrigation application rates, including regular irrigation (I100; actual evapotranspiration) and deficit irrigation (I80; 0.8 actual evapotranspiration), and three different N fertilizer rates at 210 (NH; conventional applied N rate by local farmers), 160 (NM; moderate N rate), and 110 kg ha−1 (NL; low N rate). The control groups in this study consisted of experimental plots under the NM and N0 (no N) without biochar application. The aboveground dry matter mass (ADM), yield, and net ecosystem economic budget (NEEB) of winter wheat showed increasing trends with increasing N application rates without significant differences between the NH and NM treatments. On the other hand, the water use efficiency (WUE), agronomic N fertilizer use efficiency (aNUE), and N fertilizer recovery efficiency (NRE) showed increasing-decreasing trends with increasing N fertilizer rates, reaching the highest values under the NM treatment scenario. The biochar addition significantly increased the winter wheat yield and WUE (P<0.05). On the other hand, the I80 treatment resulted in higher WUE and irrigation water use efficiency (IWUE) than those under I100 by 5.63 and 13.52 %, respectively. TOPSIS results indicated that the combined I80B1NM treatment was the optimal winter wheat management practice, maintaining high productivity while improving resource use efficiency and economic benefits. The results of the present study provide an important scientific basis and guidance for ensuring efficient and high-quality agricultural products in the Guanzhong Plain and other regions in China with similar climatic characteristics.

De-etiolation is Almost Colour Blind: the Study of Photosynthesis Awakening Under Blue and Red Light.

The synthesis and assembly of functioning photosynthetic complexes in chloroplasts developing from etioplasts during the de-etiolation of angiosperm seedlings are imperative for the plant's autotrophic lifestyle. This study compared de-etiolation process under monochromatic red or blue light of equal photon flux density during a 24-hour illumination period of etiolated Arabidopsis seedlings. The aim was to elucidate the impact of these light wavelength on the etioplast-to-chloroplast transformation and the initiation of light-dependent photosynthetic reactions. Both treatments lead to the formation of functional young chloroplasts; however, the etioplast-to-chloroplast transition and the assembly of photosynthetic complexes occurred unevenly, with individual steps tuned by red or blue light. Ultrastructural analysis suggested faster prolamellar bodies disassembly under blue light, while low temperature fluorescence studies indicated a slower transformation of protochlorophyllide to chlorophyllide, and chlorophyll a, under these conditions. Red light further promoted the synthesis of chlorophyll b and LHCII antenna proteins. However, the efficiency of antennae in dissipating excess absorbed energy was higher for seedlings de-etiolated under blue light; the maximum quantum yield of the photosystem II reached 0.81 after 24-hour de-etiolation, equivalent to mature plants. Blue light seemed to enhance the development of well-functioning photosystems (I and II) and antennae. These findings are important for gaining a deeper understanding of photoreceptor regulation of de-etiolation and for utilizing selected light regimes to improve crop yield.

Spatial Variation of Microclimatic Parameters Inside a Polyhouse with Fog Cooling System

The importance of protected cultivation is increasing day by day due to its capability of producing crop all round the year and increase in the crop productivity. This advantage of protected cultivation can be efficiently achieved by adapting the polyhouse cultivation. To obtain the maximum crop productivity inside a polyhouse, it is necessary to understand the variability of microclimate inside it. The present study aims to understand the spatial variability of microclimate inside a naturally ventilated polyhouse installed with fog cooling system during summer season. The main aim of the study is to understand the effect of fogging system in spatial variability of microclimate. For the study, the data of microclimatic parameters were collected daily from April to June at four different time intervals 8.30 AM, 12.30 PM, 4.30 PM and 8.30 PM. The data recorded was then analyzed in Golden Surfer Software to generate contour plots of weekly averages of microclimate parameters. The analysis revealed that the temperature and relative humidity varied across the polyhouse depending upon the wind velocity and its distribution pattern. The light intensity varied based upon the orientation of polyhouse and the position of sun. Carbon dioxide concentration varied based on temperature, light intensity, crop transpiration and respiration. It can be concluded that, inside a naturally ventilated polyhouse, the microclimate varied both spatially and temporally with fogging system also due to wind effect. Thus, having accurate understanding of the microclimate inside a polyhouse helps to maintain optimal conditions for plant growth and thus improve crop yield and productivity.

Hydrogel Embedding Enables Enhanced Leaf Deposition and Bioavailability of Fe-Based Engineered Nanoparticles.

Nanofertilizers comprising engineered nanoparticles (ENPs) have great potential in sustainable agriculture due to their strong capabilities of improving crop yields. As an effective fertilization strategy, foliar spraying could lead to broken and splashed ENP droplets, resulting in inaccurate leaf targeting and potential environmental contamination. Herein, we propose embedding Fe-based ENPs into a supramolecular hydrogel to effectively enhance the deposition amount on leaves and thus the bioavailability. The proper rheological properties of the hydrogel droplets and their robust interaction with soybean leaf simultaneously reduce the droplet rebound and fragmentation, especially under elevated impact speeds, resulting in up to 168.9% more droplet deposition compared to the ENP suspension. Computational fluid dynamics simulation analysis suggests that the contact angle is a key sensitive factor influencing the dynamic deposition behavior of the hydrogel droplet. A 15% reduction in the contact angle results in a 14% reduction of the highest bouncing height. The incorporation of ENPs enhances the viscous dissipation rate by 7.4% in comparison with pure hydrogel droplets. The hydrogel embedding also causes a 1.5-fold increase in ENP uptake compared to that of the ENP suspension. The hydrogel embedding delivers a reduction of 80% in the ENP application amount, compared to ENP suspensions, while achieving a 28% increase in the fresh weight of soybean seedlings. This work provides an effective method to enhance the deposition of ENPs during foliar application.

Method of intelligent agricultural pest image recognition based on machine vision algorithm

In recent years, people have paid increasing attention to smart agriculture. Its core technology is to combine information technology such as computer vision with agricultural production. In agricultural production, the occurrence of pests and diseases can seriously affect agricultural production. Therefore, in agricultural production, the diagnosis and identification of agricultural pests and diseases is the key to improve crop yield. Traditional machine vision methods often rely on feature extraction and classifier design, lack of strong learning and generalization ability, and can not effectively control crop diseases and pests in a timely manner. In order to solve this problem, this paper designs an agricultural pest recognition system based on machine vision algorithm of fuzzy recognition theory, and applies it to agricultural pest recognition. Compared with the traditional machine vision method, this method has obvious advantages, and can effectively improve the monitoring and early warning ability of crop diseases and pests. The experimental results show that the highest recognition rate of the machine vision optimization algorithm based on fuzzy recognition theory is 98.06%, and the lowest recognition error rate is 5.83%. It can be seen that the machine vision recognition algorithm based on fuzzy recognition theory has good recognition effect and can be used in agricultural pest recognition system to help farmers carry out agricultural production and reduce economic losses caused by diseases and pests.

Functional diversity of ground beetles improved aphid control but did not increase crop yields on European farms.

Land-use intensification is often associated with a decline in functional diversity, potentially undermining the provision of ecosystem services. However, how changes in traits affect ecosystem processes remains poorly understood. Variation in trait values among species in a community may drive ecosystem processes. Alternatively, the mass ratio hypothesis proposes that trait values of the dominant species in a local community are related to ecosystem processes. Using data from 159 farms in six European countries, we quantified the impact of local and landscape-level land-use intensity on ground beetles as pest control agents. We then assessed the extent to which functional diversity and community-weighted mean trait values relate to pest control and cereal yield. In addition, we assessed how the responses to land use and the effects of different species on pest control and yield varied with their traits to compare the relative impact of the traits studied. Functional diversity of ground beetles improved aphid removal, but did not translate into higher crop yields. Pest control of aphids was enhanced by a higher proportion of smaller, mobile ground beetles with a preference for the vegetation layer. Smaller, predatory ground beetles in communities improved crop yield. The magnitude of responses to land-use intensification and the effects on pest control and yield were more strongly influenced by body size than other traits. Our study provides evidence that reduced management intensity can improve pest control by supporting small-sized, macropterous ground beetles. In contrast to the claims of ecological intensification, our joint analysis of the direct effects of land use on yield and indirect effects via functional diversity of ground beetles and pest control suggests that ecosystem services by ground beetles cannot compensate for the yield gap due to a reduction in land-use intensity.

The Relationship between the Density of Winter Canola Stand and Weed Vegetation

Canola (Brassica napus L.) is an important oilseed crop that provides essential vegetable oil but faces significant competition from weeds that are influenced by various agronomic practices and environmental conditions. This study examines the complex interactions between canola stand density and weed intensity over three growing seasons, identifying a total of 27 weed species. It is important to establish a connection between the density of winter canola stands, the intensity of weeding and the response of individual weed species in real conditions. The case study was executed on plots located in the Přerov district (Olomouc region, Czech Republic). The assessment was carried out during two periods—autumn in October and spring in April. Canola plants (plant density) were counted in each evaluated area, weed species were identified, and the number of plants for each weed species was determined. Half of the plots were covered with foil before herbicide application to prevent these areas from being treated with herbicides. We used redundancy analysis (RDA) to evaluate the relationships between canola density and weed dynamics, both with and without herbicide treatment. The results show the ability of canola to compete with weeds; however, that is factored by the density of the canola stand. In dense stands (over 60 plants/m²), canola is able to suppress Galium aparine L., Geranium pusillum L., Lamium purpureum L., Papaver rhoeas L. and Chamomilla suaveolens (Pursh) Rydb. Nevertheless, there are weed species that grow well even in dense canola stands (Echinochloa crus-galli (L.) P. Beauv., Phragmites australis (Cav.) Steud., Tripleurospermum inodorum (L.) Sch. Bip. and Triticum aestivum L.). These findings highlight the potential for using canola stand density as a strategic component of integrated weed management to reduce herbicide reliance and address the growing challenge of herbicide-resistant weed populations. This research contributes significantly to our understanding of the dynamics of weed competition in canola systems and informs sustainable agricultural practices for improved crop yield and environmental stewardship.

Spatiotemporal coupling dynamics and factors influencing soil organic carbon and crop yield in Chinese farmlands

Clarifying the correlation between soil organic carbon (SOC) and crop yield is key to achieving carbon neutrality and ensuring food security. However, owing to the lack of analysis based on large-scale farmland monitoring data and research on deep soil, relevant research has not yet reached a consensus. Here, we based on the monitoring data of 118 sample plots from 21 typical farmland and farmland compound ecosystem stations of the China Ecosystem Research Network (CERN) between 2004 and 2020, the temporal and spatial coupling associations between SOC content and crop yield in 0–20 cm and 0–100 cm soil layers and its factors influencing were determined. The findings revealed that between 2004 and 2020, SOC content in 0–20 cm soil layer, SOC content in 0–100 cm soil layer, and crop yield in typical farmland in China showed a fluctuating upward trend, the average annual growth rates were 0.59 %, 0.27 % and 1.07 %, respectively. The coupling relationship between SOC content and crop yield was not always good in different periods, which varies largely in different geographical divisions. Among the anthropogenic factors, exogenous carbon input can improve the coupling relationship between them by increasing the soil organic carbon content and crop yield, while the effect of less tillage and no tillage is limited. Among the natural factors, temperature, soil bulk density, and farmland type all have an impact on farmland SOC content and crop yield at different significance levels. Each variable had different effects on SOC content and crop yield in typical farmlands in different geographical regions. With deepening soil layer, influence of anthropogenic factors such as exogenous carbon input on SOC content decreases, but it still cannot be ignored. Based on these findings, the study recommends that exogenous carbon input play an important role in soil carbon sequestration and improving crop yield.

PrDA1-1 and its interacting proteins PrTCP1/PrTCP9 in flare tree peony affect yield by regulating seed weight and number

Tree peony is an emerging woody oilseed crop that has the potential to help meet the growing demand for edible oil and biofuel, and breeding high-yield varieties is the key to increasing production. The DA1 gene regulates seed weight and number and effectively improves crop yield; however, its function in tree peonies has not yet been reported. In this study, three PrDA1 genes were first identified in the whole genome of ‘Jing Hong’ flare tree peony (Paeonia rockii). PrDA1-1, which contains three types of conserved structural domains UIM (ubiquitin-interacting motif), LIM (Lin11, Isl- 1, and Mec-3), and DA-like, is homologous to AtDA1. PrDA1-1 was strongly expressed during both the early and late stages of seed development, and its constitutive expression in Arabidopsis reduced seed number but increased seed weight, which ultimately led to a decrease in yield. PrDA1-1 interacted with PrTCP1/PrTCP9 in yeast and plants, and the constitutive expression of PrTCP1/PrTCP9 in Arabidopsis increased seed weight and number, which resulted in high yield. We showed that PrDA1-1 and PrTCP1/PrTCP9 regulate seed weight and number to affect yield; these new genetic resources will help improve the seed yield of tree peonies..

Combining insitu rainwater harvesting and integrated nutrient management of organic manure improves soil moisture, fertility and crop yields in marginalized areas: A review

Soil moisture stress and infertility are major biophysical constraints which limit crop production and food security in marginalized areas. Marginal areas are mainly associated with low rainfall which is insufficient to support crops until maturity is reached. The use of insitu rainwater harvesting methods such as planting pits, tied ridges, mulching, Zai pits and half-moon can be a solution to reduce moisture stress. This alone cannot improve crop yields hence the need to use integrated nutrient management (INM) of animal manure, biofertilisers, mineral fertiliser and composts to improve soil fertility, structure and increase water retention ability. Combining rainwater harvesting with INM has the potential to mitigate effects of climate change, improve crop yields and meet food demand in marginal areas. Various nutrient sources used as INM can restore soil health, increase microbial population, nutrient mineralisation and improve soil quality. Use of biofertilisers in agriculture reduces soil toxicity, improve nutrient availability and create a conducive environment for crop growth and development. Integration of tied ridges with cattle manure and mineral fertiliser has the potential of increasing infiltration rates, reducing surface runoff and increase crop yields with 50-150% regardless of soil type. This chapter sought to come up review the effects of rainwater harvesting methods and INM on soil fertility, moisture stress and crop yields in marginalized areas.