Straw return increases crop production by improving soil organic carbon sequestration and soil aggregation in a long-term wheat-cotton cropping system

Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.

Co-incorporating green manure and crop straw increases crop productivity and improves soil quality with low greenhouse-gas emissions in a crop rotation

In a nine-year field experiment in a wheat-maize-sunflower cropping system in Hetao Irrigation Area,Inner Mongolia,China,organic amendments applied as straw,manure,green manure,and the combination of green manure and straw increased wheat and maize yield,soil aggregate stability,and soil microbial activity in comparison with chemical fertilizer,without changing greenhouse gas emission intensity.

Assessment of Crop Yield in China Simulated by Thirteen Global Gridded Crop Models

Global gridded crop models(GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national-and provincial-scale evaluation of the simulations by13 GGCMs [12 from the GGCM Intercomparison(GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops(wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national-and provincial-scale crop yield prediction in China.

Coordinated responses of leaf and nodule traits contribute to the accumulation of N in relay intercropped soybean

Maize(Zea mays L.)-soybean(Glycine max L.Merr.)relay intercropping provides a way to enhance land productivity.However,the late-planted soybean suffers from shading by the maize.After maize harvest,how the recovery growth influences the leaf and nodule traits remains unclear.A three-year field experiment was conducted to evaluate the effects of genotypes,i.e.,supernodulating(nts1007),Nandou 12(ND12),and Guixia 3(GX3),and crop configurations,i.e.,the interspecific row spacing of 45(I45),60(I60),75 cm(I75),and sole soybean(SS),on soybean recovery growth and N fixation.The results showed that intercropping reduced the soybean total leaf area(LA)by reducing both the leaf number(LN)and unit leaflet area(LUA),and it reduced the nodule dry weight(NW)by reducing both the nodule number(NN)and nodule diameter(ND)compared with the SS.The correlation and principal component analysis(PCA)indicated a co-variability of the leaf and nodule traits in response to the genotype and crop configuration interactions.During the recovery growth stages,the compensatory growth promoted soybean growth to reduce the gaps of leaf and nodule traits between intercropping and SS.The relative growth rates of ureide(RGR_U)and nitrogen(RGR_N)accumulation were higher in intercropping than in SS.Intercropping achieved more significant sucrose and starch contents compared with SS.ND12 and GX3 showed more robust compensatory growth than nts1007 in intercropping.Although the recovery growth of relay intercropping soybean improved biomass and nitrogen accumulation,ND12 gained a more significant partial land equivalent ratio(pLER)than GX3.The I60 treatment achieved more robust compensation effects on biomass and N accumulation than the other configurations.Meanwhile,I60 showed a higher nodule sucrose content and greater shoot ureide and N accumulation than SS.Finally,intercropping ND12 with maize using an interspecific row spacing of 60 cm was optimal for both yield advantage and N accumulation.

Several Cotton Rotation and Intercropping Systems in Cotton Planting Area of Eastern Henan Province

In recent years,the area dedicated to cotton cultivation in eastern Henan Province has experienced a continuous decline.Developing efficient multi-cropping systems for cotton and increasing the multiple cropping index represent effective strategies to stabilize the cotton planting area and enhance the income of cotton farmers.This paper presents an overview of intercropping systems and the benefits associated with cotton rotation and intercropping practices.Specifically,it discusses the"early maturing cotton-wheat"rotation system,the"cotton-watermelon"intercropping system,the"cotton-Dutch bean"intercropping system,and the"early maturing cotton-peanut-garlic"intercropping system.

Satellite Multi-Temporal Data and Cropping Pattern Approach for Green Gram Crop Management in the Lower Midland Zone IV and V in Kenya

Creation of a spectral signature reflectance data, which aids in the identification of the crops is important in determining size and location crop fields. Therefore, we developed a spectral signature reflectance for the vegetative stage of the green gram (Vigna. radiata L.) over 5 years (2020, 2018, 2017, 2015, and 2013) for agroecological zone IV and V in Kenya. The years chosen were those whose satellite resolution data was available for the vegetative stage of crop growth in the short rain season (October, November, December (OND)). We used Landsat 8 OLI satellite imagery in this study. Cropping pattern data for the study area were evaluated by calculating the Top of Atmosphere reflectance. Farms geo-referencing, along with field data collection, was undertaken to extract Top of Atmosphere reflectance for bands 2, 3, 4 and 7. We also carried a spectral similarity assessment on the various cropping patterns. The spectral reflectance ranged from 0.07696 - 0.09632, 0.07466 - 0.09467, 0.0704047 - 0.12188,0.19822 - 0.24387, 0.19269 - 0.26900, and 0.11354 - 0.20815 for bands 2, 3, 4, 5, 6, and 7 for green gram, respectively. The results showed a dissimilarity among the various cropping patterns. The lowest dissimilarity index was 0.027 for the maize (Zea mays L.) bean (Phaseolus vulgaris) versus the maize-pigeon pea (Cajanus cajan) crop, while the highest dissimilarity index was 0.443 for the maize bean versus the maize bean and cowpea cropping patterns. High crop dissimilarities experienced across the cropping pattern through these spectral reflectance values confirm that the green gram was potentially identifiable. The results can be used in crop type identification in agroecological lower midland zone IV and V for mung bean management. This study therefore suggests that use of reflectance data in remote sensing of agricultural ecosystems would aid in planning, management, and crop allocation to different ecozones.

Microplastic Can Decrease Enzyme Activities and Microbes in Soil

An in vitro study was conducted to investigate the impacts of microplastics on enzyme activities and soil bacteria. The study included four different treatments of microplastics including a control. Different levels of microplastics were applied to the soil ranging from 0% to 5%, to assess the impacts of microplastics on soil enzymes and subsequent soil bacteria. After 30 days of incubation, the soil samples were collected and growth parameters of bacteria were assessed. Activities of β-glucosidase, urease and dehydrogenase enzymes were also determined. Our results showed that the presence of microplastics in the soil significantly reduced bacterial population together with bacterial strains. The activities of β-glucosidase, urease and dehydrogenase enzymes were reduced significantly to approximately 32%, 40% and 50% in microplastics treated soils respectively. Concentration of microplastic has a role to play towards this direction;the higher the concentration of microplastic the greater is the impact on enzymes and soil bacteria. The present study on the microbial soil health vis-à-vis microplastic application indicates that the material can have negative effect on the soil bacterial population of and thus ultimately may jeopardize soil health and crop production.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

A dual-RPA based lateral flow strip for sensitive,on-site detection of CP4-EPSPS and Cry1Ab/Ac genes in genetically modified crops

Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.

Crops模型在农业灌溉上的应用研究

灌溉是农业灌溉管理中非常重要的问题之一,传统的人工灌溉不仅浪费人力又工作效率不高。基于Crops模型的灌溉装置拟对农田中土壤环境、大气湿度和病虫害情况进行采样研究,掌握农田中的土壤环境以及空气湿度的变化规律,获得不同情况下的相关数据,在对相关数据进行分析的基础上,采用温度湿度传感器对一定范围内的各项指标进行分析,为田地里的农作物精准灌溉提供相关数据。Irrigation is one of the very important issues in agricultural irrigation management, and traditional manual irrigation not only wastes manpower but also has low work efficiency. The irrigation device based on the Crops model intends to sample and study the soil environment, atmospheric humidity and pests and diseases in the farmland, grasp the change law of the soil environment and air humidity in the farmland, obtain the relevant data under different conditions, and on the basis of the analysis of the relevant data, the temperature and humidity sensor is used to analyze the indicators within a certain range, so as to provide relevant data for the precise irrigation of crops in the field.

The multiple roles of crop structural change in productivity,nutrition and environment in China:A decomposition analysis

China's crop structure has undergone significant changes in the last two decades since 2000,with an increase in the share of cereals,vegetables,and fruit,squeezing out other crops.As a result,land productivity,nutrient supply,and carbon emissions have changed.How to reallocate limited farmland among crops to achieve the multiple goals of agrifood systems becomes an important issue.This study explores the sources of land productivity and nutrition supply growth and carbon emissions reduction,and identifies the multiple roles of crop structural change from 2003 to 2020 based on a decomposition analysis.The results reveal that the growth within crops is still the primary driver in land productivity and nutrition supply and the reduction in carbon emissions.However,structural change also plays various roles at different periods.From 2003 to 2010,crop structural change increased the total calorie supply but lowered land productivity and contributed at least 70%of the total growth of carbon emissions.The crop structure was relatively stable,and their effects were modest from 2010 to 2015.From 2015 to 2020,the crop structural change began to play a greater role and generate synergistic effects in improving land productivity,micronutrient supply,and reducing carbon emissions,contributing to approximately a quarter of the growth of land productivity and 30%of total carbon emissions reduction.These results suggest that strategies for crop structural change should comprehensively consider its multiple impacts,aiming to achieve co-benefits while minimizing trade-offs.

Nitrogen rhizodeposition from corn and soybean,and its contribution to the subsequent wheat crops

Nitrogen(N)is a key factor in the positive response of cereal crops that follow leguminous crops when compared to gramineous crops in rotations,with the nonrecyclable rhizosphere-derived N playing an important role.However,quantitative assessments of differences in the N derived from rhizodeposition(NdfR)between legumes and gramineous crops are lacking,and comparative studies on their contributions to the subsequent cereals are scarce.In this study,we conducted a meta-analysis of NdfR from leguminous and gramineous crops based on 34 observations published worldwide.In addition,pot experiments were conducted to study the differences in the NdfR amounts,distributions and subsequent effects of two major wheat(Triticum aestivum L.)-preceding crops,corn(Zea mays L.)and soybean(Glycine max L.),by the cotton wick-labelling method in the main wheat-producing areas of China.The meta-analysis results showed that the NdfR of legumes was significantly greater by 138.93%compared to gramineous crops.In our pot experiment,the NdfR values from corn and soybean were 502.32 and 944.12 mg/pot,respectively,and soybean was also significantly higher than corn,accounting for 76.91 and 84.15%of the total belowground nitrogen of the plants,respectively.Moreover,in different soil particle sizes,NdfR was mainly enriched in the large macro-aggregates(>2 mm),followed by the small macro-aggregates(2–0.25 mm).The amount and proportion of NdfR in the macro-aggregates(>0.25 mm)of soybean were 3.48 and 1.66 times higher than those of corn,respectively,indicating the high utilization potential of soybean NdfR.Regarding the N accumulation of subsequent wheat,the contribution of soybean NdfR to wheat was approximately 3 times that of corn,accounting for 8.37 and 4.04%of the total N uptake of wheat,respectively.In conclusion,soybean NdfR is superior to corn in terms of the quantity and distribution ratio of soil macro-aggregates.In future field production,legume NdfR should be included in the nitrogen pool that can be absorbed and utilized by subsequent crops,and the role and potential of leguminous plants as nitrogen source providers in crop rotation systems should be fully utilized.

Characteristics of the microbial communities regulate soil multi-functionality under different cover crop amendments in Ultisol

The use of cover crops is a promising strategy for influencing the soil microbial consortium,which is essential for the delivery of multiple soil functions(i.e.,soil multifunctionality).Nonetheless,relatively little is known about the role of the soil microbial consortium in mediating soil multifunctionality under different cover crop amendments in dryland Ultisols.Here,we assessed the multifunctionality of soils subjected to four cover crop amendments(control,non-amended treatment;RD,radish monoculture;HV,hairy vetch monoculture;and RDHV,radish-hairy vetch mixture),and we investigated the contributions of soil microbial richness,network complexity,and ecological clusters to soil multifunctionality.Our results demonstrated that cover crops whose chemical composition differed from that of the main plant crop promoted higher multifunctionality,and the radish-hairy vetch mixture rendered the highest enhancement.We obtained evidence that changes in soil microbial richness and network complexity triggered by the cover crops were associated with higher soil multifunctionality.Specifically,specialized microbes in a key ecological cluster(ecological cluster 2)of the soil microbial network were particularly important for maintaining soil multifunctionality.Our results highlight the importance of cover crop-induced variations in functionally important taxa for promoting the soil multifunctionality of dryland Ultisols.

Optimization of inter-seasonal nitrogen allocation increases yield and resource-use efficiency in a water-limited wheat-maize cropping system in the North China Plain

Winter wheat–summer maize cropping system in the North China Plain often experiences droughtinduced yield reduction in the wheat season and rainwater and nitrogen(N)fertilizer losses in the maize season.This study aimed to identify an optimal interseasonal water-and N-management strategy to alleviate these losses.Four ratios of allocation of 360 kg N ha^(-1)between the wheat and maize seasons under one-time presowing root-zone irrigation(W0)and additional jointing and anthesis irrigation(W2)in wheat and one irrigation after maize sowing were set as follows:N1(120:240),N2(180:180),N3(240:120)and N4(300:60).The results showed that under W0,the N3 treatment produced the highest annual yield,crop water productivity(WPC),and nitrogen partial factor productivity(PFPN).Increased N allocation in wheat under W0 improved wheat yield without affecting maize yield,as surplus nitrate after wheat harvest was retained in the topsoil layers and available for the subsequent maize.Under W2,annual yield was largest in the N2 treatment.The risk of nitrate leaching increased in W2 when N application rate in wheat exceeded that of the N2 treatment,especially in the wet year.Compared to W2N2,the W0N3 maintained 95.2%grain yield over two years.The WPCwas higher in the W0 treatment than in the W2 treatment.Therefore,following limited total N rate,an appropriate fertilizer N transfer from maize to wheat season had the potential of a“triple win”for high annual yield,WPCand PFPN in a water-limited wheat–maize cropping system.

The microbial community,nutrient supply and crop yields differ along a potassium fertilizer gradient under wheat-maize double-cropping systems

Soil microorganisms play critical roles in ecosystem function.However,the relative impact of the potassium(K)fertilizer gradient on the microbial community in wheat-maize double-cropping systems remains unclear.In this long-term field experiment(2008-2019),we researched bacterial and fungal diversity,composition,and community assemblage in the soil along a K fertilizer gradient in the wheat season(K0,no K fertilizer;K1,45 kg ha^(-1) K_(2)O;K_(2),90 kg ha^(-1)K_(2)O;K3,135 kg ha^(-1)K_(2)O)and in the maize season(K0,no K fertilizer;K_(1),150 kg ha^(-1) K_(2)O;K_(2),300 kg ha^(-1)K_(2)O;K_(3),450 kg ha^(-1)K_(2)O)using bacterial 16S rRNA and fungal internally transcribed spacer(ITS)data.We observed that environmental variables,such as mean annual soil temperature(MAT)and precipitation,available K,ammonium,nitrate,and organic matter,impacted the soil bacterial and fungal communities,and their impacts varied with fertilizer treatments and crop species.Furthermore,the relative abundance of bacteria involved in soil nutrient transformation(phylum Actinobacteria and class Alphaproteobacteria)in the wheat season was significantly increased compared to the maize season,and the optimal K fertilizer dosage(K2 treatment)boosted the relative bacterial abundance of soil nutrient transformation(genus Lactobacillus)and soil denitrification(phylum Proteobacteria)bacteria in the wheat season.The abundance of the soil bacterial community promoting root growth and nutrient absorption(genus Herbaspirillum)in the maize season was improved compared to the wheat season,and the K2 treatment enhanced the bacterial abundance of soil nutrient transformation(genus MND1)and soil nitrogen cycling(genus Nitrospira)genera in the maize season.The results indicated that the bacterial and fungal communities in the double-cropping system exhibited variable sensitivities and assembly mechanisms along a K fertilizer gradient,and microhabitats explained the largest amount of the variation in crop yields,and improved wheat?maize yields by 11.2-22.6 and 9.2-23.8%with K addition,respectively.These modes are shaped contemporaneously by the different meteorological factors and soil nutrient changes in the K fertilizer gradients.

Advances in Understanding Cadmium Stress and Breeding of Cadmium-Tolerant Crops

Cadmium(Cd) pollution has emerged as a critical global environmental concern, due to its significant toxicity, environmental persistence, and the pervasiveness of contamination. Significantly, the bioaccumulation of Cd in agricultural crops constitutes a primary vector for its entry into the human diet. This issue warrants urgent attention from both the scientific community and policymakers to develop and implement effective mitigation strategies. This review delves into the physiological impacts of Cd stress on plants, including the suppression of photosynthetic activity, amplification of oxidative stress, and disruptions in mineral nutrient homeostasis. Additionally, the resistance mechanisms deployed by plants in response to Cd stress have been explored, and the prospective contributions of molecular breeding strategies in augmenting crop tolerance to Cd and minimizing its bioaccumulation have been assessed. By integrating and analyzing these findings, we seek to inform future research trajectories and proffer strategic approaches to enhance agricultural sustainability, safeguard human health, and protect environmental integrity.

Trends in the global commercialization of genetically modified crops in 2023

The commercialization of genetically modified(GM)crops has increased food production,improved crop quality,reduced pesticide use,promoted changes in agricultural production methods,and become an important new production strategy for dealing with insect pests and weeds while reducing the cultivated land area.This article provides a comprehensive examination of the global distribution of GM crops in 2023.It discusses the internal factors that are driving their adoption,such as the increasing number of GM crops and the growing variety of commodities.This article also provides information support and application guidance for the new developments in global agricultural science and technology.

Adding Value to Crop Production Systems by Integrating Forage Cover Crop Grazing

In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance was compared in the spring following autumn establishment as for age cover crops after soybean [Glycine max (L.) Merr.] grain harvest. Replicated pastures (0.4 ha) were no-till seeded in three consecutive years into soybean stubble in autumn, fertilized, and grazed the following spring near Ithaca, NE, USA. Each pasture (n = 3) was continuously stocked in spring with four yearling steers (380 ± 38 kg) for 17, 32, and 28 d in 2005, 2006, and 2007, respectively. In 2005, average daily gain (ADG) for steers grazing triticale exceeded the ADG for wheat by 0.31 kghd-1d-1. In 2006, wheat ADG exceeded that for triticale by 0.12 kghd-1d-1. In 2007, steers grazing wheat lost weight, while steers grazing triticale gained 0.20 kghd-1d-1. Based on the 3-year average animal gains valued at $1.32 kg-1, mean net return ($ ha-1 yr-1) was $62.15 for triticale and $22.55 for wheat. Since these grazed cover crops provide ecosystem services in addition to forage, grazing could be viewed as a mechanism for recovering costs and adds additional value to the system. Based on this 3-year grazing trial, triticale was superior to wheat and likely will provide the most stable beef yearling performance across years with variable weather for the western Cornbelt USA.

Comparison of CWSI and T_(s)-T_(a)-VIs in moisture monitoring of dryland crops(sorghum and maize)based on UAV remote sensing

Monitoring agricultural drought using remote sensing data is crucial for precision irrigation in modern agriculture.Utilizing unmanned aerial vehicle(UAV)remote sensing,we explored the applicability of an empirical crop water stress index(CWSI)based on canopy temperature and three-dimensional drought indices(TDDI)constructed from surface temperature(T_(s)),air temperature(T_(a))and five vegetation indices(VIs)for monitoring the moisture status of dryland crops.Three machine learning algorithms(random forest regression(RFR),support vector regression,and partial least squares regression)were used to compare the performance of the drought indices for vegetation moisture content(VMC)estimation in sorghum and maize.The main results of the study were as follows:(1)Comparative analysis of the drought indices revealed that T_(s)-T_(a)-normalized difference vegetation index(TDDIn)and T_(s)-T_(a)-enhanced vegetation index(TDDIe)were more strongly correlated with VMC compared with the other indices.The indices exhibited varying sensitivities to VMC under different irrigation regimes;the strongest correlation observed was for the TDDIe index with maize under the fully irrigated treatment(r=-0.93).(2)Regarding spatial and temporal characteristics,the TDDIn,TDDIe and CWSI indices showed minimal differences Over the experimental period,with coefficients of variation were 0.25,0.18 and 0.24,respectively.All three indices were capable of effectively characterizing the moisture distribution in dryland maize and sorghum crops,but the TDDI indices more accurately monitored the spatial distribution of crop moisture after a rainfall or irrigation event.(3)For prediction of the moisture content of single crops,RFR models based on TDDIn and TDDIe estimated VMC most accurately(R^(2)>0.7),and the TDDIn-based model predicted VMC with the highest accuracy when considering multiple-crop samples,with R^(2)and RMSE of 0.62 and 14.26%,respectively.Thus,TDDI proved more effective than the CWSI in estimating crop water content.

The influences of canopy temperature measuring on the derived crop water stress index

Crop water stress index(CWSI)is widely used for efficient irrigation management.Precise canopy temperature(T_(c))measurement is necessary to derive a reliable CWSI.The objective of this research was to investigate the influences of atmospheric conditions,settled height,view angle of infrared thermography,and investigating time of temperature measuring on the performance of the CWSI.Three irrigation treatments were used to create different soil water conditions during the 2020-2021 and 2021-2022 winter wheat-growing seasons.The CWSI was calculated using the CWSI-E(an empirical approach)and CWSI-T(a theoretical approach)based on the T_(c).Weather conditions were recorded continuously throughout the experimental period.The results showed that atmospheric conditions influenced the estimation of the CWSI;when the vapor pressure deficit(VPD)was>2000 Pa,the estimated CWSI was related to soil water conditions.The height of the installed infrared thermograph influenced the T_(c)values,and the differences among the T_(c)values measured at height of 3,5,and 10 m was smaller in the afternoon than in the morning.However,the lens of the thermometer facing south recorded a higher T_(c)than those facing east or north,especially at a low height,indicating that the direction of the thermometer had a significant influence on T_(c).There was a large variation in CWSI derived at different times of the day,and the midday measurements(12:00-15:00)were the most reliable for estimating CWSI.Negative linear relationships were found between the transpiration rate and CWSI-E(R^(2)of 0.3646-0.5725)and CWSI-T(R^(2)of 0.5407-0.7213).The relations between fraction of available soil water(FASW)with CWSI-T was higher than that with CWSI-E,indicating CWSI-T was more accurate for predicting crop water status.In addition,The R^(2)between CWSI-T and FASW at 14:00 was higher than that at other times,indicating that 14:00 was the optimal time for using the CWSI for crop water status monitoring.Relative higher yield of winter wheat was obtained with average seasonal values of CWSI-E and CWSI-T around 0.23 and 0.25-0.26,respectively.The CWSI-E values were more easily influenced by meteorological factors and the timing of the measurements,and using the theoretical approach to derive the CWSI was recommended for precise irrigation water management.