Analyses of the Temporal Development and Yield Losses due to Sheath Blight of Rice (Rhizoctonia solani AG1.1a)

Sheath blight of rice, caused by Rhizoctonia solani AG 1. 1a, has become the most important disease and caused serious yield losses in some major rice-growing regions in China in recent years. In the present study, field plot experiment was conducted to examine the relationships between disease intensity and inoculum density （ID）, the seasonal disease epidemic dynamics, and yield reductions due to disease damages. Results from the experiment demonstrated that the areas under progress curves of disease severity and those of percent rice tillers diseased were positively and closely related to the relative initial ID of the pathogen. The inoculum density-disease （IDD） relationships were simulated and the impractical linear models were obtained. Both logistic and Gompertz functions could be used to simulate the disease progress dynamics in time, but the progress curves of the disease severity were modeled better by the Gompertz than by logistic function. However, the Richards function was found to be the best in simulating the disease progress curves when a most appropriate value was chosen for the shape parameter m by using the computer software Epitimulator. Sheath blight infection decreased rice yield very significantly and a yield reduction of 40% was recorded in rice crop with the highest inoculum density. Rice yield was linearly and negatively correlated with the disease severity and the percent tillers affected. The simulated models for all these relationships were computed through executing Epitimulator software and were presented in this paper.

Detect and attribute the extreme maize yield losses based on spatio-temporal deep learning

Providing accurate crop yield estimations at large spatial scales and understanding yield losses under extreme climate stress is an urgent challenge for sustaining global food security.While the data-driven deep learning approach has shown great capacity in predicting yield patterns,its capacity to detect and attribute the impacts of climatic extremes on yields remains unknown.In this study,we developed a deep neural network based multi-task learning framework to estimate variations of maize yield at the county level over the US Corn Belt from 2006 to 2018,with a special focus on the extreme yield loss in 2012.We found that our deep learning model hindcasted the yield variations with good accuracy for 2006-2018(R^(2)=0.81)and well reproduced the extreme yield anomalies in 2012(R^(2)=0.79).Further attribution analysis indicated that extreme heat stress was the major cause for yield loss,contributing to 72.5%of the yield loss,followed by anomalies of vapor pressure deficit(17.6%)and precipitation(10.8%).Our deep learning model was also able to estimate the accumulated impact of climatic factors on maize yield and identify that the silking phase was the most critical stage shaping the yield response to extreme climate stress in 2012.Our results provide a new framework of spatio-temporal deep learning to assess and attribute the crop yield response to climate variations in the data rich era.

Estimating the Yield Loss of Winter Wheat from Drought in the United States Southern Plains Region as Influenced by El Niño-Southern Oscillation (ENSO)

Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.

Heavy soil drying during mid-to-late grain filling stage of the main crop to reduce yield loss of the ratoon crop in a mechanized rice ratooning system

Yield loss(Y_(Loss)) in the ratoon crop due to crushing damage to left stubble from mechanical harvesting of the main crop is a constraint for wide adoption of mechanized rice ratooning technology.Soil drying before the harvest of the main crop has been proposed to overcome this problem.The objective of this study was to determine the effect of soil drying during the mid-to-late grain filling stage of the main crop on grain yield of the ratoon crop in a mechanized rice ratooning system.Field experiments were conducted to compare Y_(Loss) between light(LD) and heavy(HD) soil drying treatments in Hubei province,central China in 2017 and 2018.Y_(Loss) was calculated as the percentage of yield reduction in the ratoon crop with the main crop harvested mechanically,relative to the grain yield of the ratoon crop with the main crop harvested manually.In comparison with LD,soil hardness was increased by 42.8%-84.7% in HD at the 5-20 cm soil depth at maturity of the main crop.Soil hardness at 5 and 10 cm depths reached respectively 4.05 and 7.07 kg cm^(-2) in HD.Soil drying treatment did not significantly affect the grain yield of the main crop.Under mechanical harvesting of the main crop,HD increased the grain yield of the ratoon crop by 9.4% relative to LD.Consequently,Y_(Loss) was only 3.4% in HD,in contrast to 16.3% in LD.The differences in grain yield and Y_(Loos) between the two soil drying treatments were explained mainly by panicles m^(-2),which was increased significantly by HD in the track zone of the ratoon crop compared with LD.These results suggest that heavy soil drying practice during the mid-to-late grain filling stage of the main crop is effective for reducing Y_(Loss) of the ratoon crop in a mechanized rice ratooning system.

Resistance Analysis of 25 Corn Varieties to Stalk Rot and Evaluation of Yield Loss

Due to the meteorological factors, Henan Province had a large-scale outbreak of corn stalk rot in 2014, and the incidence status of 25 varieties was investigated. According to the relevant resistance identification standards, Xundan.509 was classified as resistance variety; Yudan606, Jinsai38 and Xundan3136 were classified as moderate resistance ones, while the other 21 varieties were highly susceptible varieties. Using the yield loss rate of 5% as the critical value of disease tolerance standard, XundanS09, Yudan606, Jinsai38, Xundan3136, Huaiyu5288, QiaoyuS, XY046, Zhengyu10, Lile66, WeikeT02 and Xundan29 were classified into tolerance varieties of corn stalk rot. The concept between disease resistance and disease tolerance was distinguished. The diseased plant rate was used as the classification basis of disease resistance and the yield loss rate was used as the evaluation standard of disease tolerance. The relationship between both was showed by a Venn diagram.

Disease Grading Criterion and Assessment of Yield Loss Caused by Maize Rough Dwarf Disease

[Objective] The paper was to study the disease grading criterion and assess the yield loss caused by maize rough dwarf disease. [Method] The ear lengths and yields of each healthy and infected plant of 5 cultivars were measured during 2009 and 2010. The severity grading criterion was deduced according to the ear length ratios. [Result]When the ratios were 0.92-1.00, 0.67-0.91, 0.41-0.66, 0.10-0.40 and 0, its corresponding disease grading criterions were 0, 1, 3, 5 and 7, respectively. The severity grading criterion was closely correlated to the yield loss. By analyzing the data of disease indexes and yield loss rates of 27 cultivars with DPS （Data Processing System）, the regression equations were established respectively. According to the comparison with each other, the Weibull Model was proved to have the highest fitting degree. Validating with the disease indexes of 27 cultivars in 2010, the equation supported the feasibility of the equation to predict the yield loss caused by maize rough dwarf disease. [Conclusion] The paper provided theoretical basis for further study on maize rough dwarf disease.

Effect of Six-fourth Generation Cnaphalocrocis medinalis (Guenée) on Rice yield and Control Index

[Objective] The study aimed to find out effects of six-fourth generation Cnaphalocrocis medinalis （Guenée） on rice production in Yangzhou district and its control index. [Method] Through artificial control of insects in field, four different insect volume gradients were set, the effects of different C. medinalis amounts on leaf roll rate and yield loss of Wuyunjing No.23 were determined. [Result] The results showed that within the range of 0-20 head/hill, as the amounts of insect increased, rice yield decreased, leaf roll rate and rice yield loss rate increased. According to 3% economic permit loss rate, the control index of C. medinalis on Wuyunjing No.23 was 173 head/hill. [Conclusion] The study would provide theoretical basis for effective controlling of six-fourth generation C. medinalis in Yangzhou district.

A Method for Estimation of Wheat Yield Loss Caused by Drought in Northwestern China

To develop a suitable method for monitoring wheat yield loss caused by drought for dry farming areas in northwestern China, daily ET0 and ETC were calculated using KC and FAO- PM from 1961 to 2000, and wheat evapotranspiration with an interval of 10 days was estimated with soil water balance equation for the mountainous areas in southern Ningxia, China. Actual water consumption and water requirements of wheat during growing season was calculated using soil water balance equation by correcting leakage of soil water and run-off of precipitation every year. A model for estimation of yield loss by drought was established based on crop growth-water consumption function and yield potential. The results show that it is an effective method for monitoring drought and estimating yield loss. This method is suitable for monitoring drought and estimating yield loss of wheat in dry farming areas in northwestern China.

Study on Analysis Model of Millet Yield Loss Caused by Weeds in Summer Season Millet Field

Weed management in summer season foxtall millet field was studied by evaluating weed damage and exploring competition between weeds and foxtail millet, and a few fitting models were simulated and compared by employing field plot experiment and nonlinear regression analysis. The results showed that the millet yield losses and weed density were extremely significantly correlated. Among the tested models, the determination coefficient （ R2 ） of hyperbolic model was 0.997 12, and minimum residual sum of squares was 16.174, which was considered the optimal model to simulate the competition relation between weeds and millet. The predicted equation was Y = d/（ 1. 733 ＋ 0. 018d） ; the interspecific competitiveness of weeds was 0. 577 0 and the intraspecific competitiveness was 0.010 3 ; the maximum loss rate of millet yield was 55.56%. This study had established an analysis model with high gcodness-of-fit and practical prediction which could help weed management in summer season millet field.

Biochemical Genetic Mechanism and QTLs of Early Maturing without Yield Loss in Short-season Upland Cotton(Gossypium hirsutum L.)

The short season cotton(SSC) was important Upland plant ecotype(Gossypium hirsutum L.).The growth of SSC was very short that is 105 ～ 110 days(after planting). SSC could increase

Wheat Yield Response to Foliar Fungicide Application against Leaf Rust Caused by Puccinia triticina

A study was conducted on reducing the yield loss of wheat due to leaf rust caused by Puccinia triticina with foliar application of fungicides during the 2014-2015 and 2015-2016 growing seasons at the Wheat Research Institute in Faisalabad, Pakistan. Three fungicides： Folicur （tebuconazole） at 300 mL/ha, Nativo （tebuconazole ＋ trifloxystrobin） at 300 g/ha and Tilt （propiconazole） at 500 mL/ha were applied single or two times to Morocco and Sehar-06 wheat varieties used in the trial. The trial plots were first sprayed at the Zadok＇s scale （ZS） 3 stage and second sprayed between ZS 4.3 and 5.4 stages. The greenness of the trial crop was measured using GreenSeeker. Foliar application of fungicides significantly reduced the loss of grain yield and 1,000-grain weight （TGW） of wheat due to leaf rust in comparison to the control without fungicides application. Of the three fungicides, two times spray of Nativo reduced the grain yield loss of leaf rust susceptible mega wheat variety Sehar-06 by 45%-56% and the loss of TGW by 42%, also giving the highest marginal return in the trial. Single application of Nativo was equally effective as two times spray of Folicur in reducing the loss of wheat grain yield. Two times spray of Folicur was found to be the second choice of fungicide for reducing the yield loss of wheat. The research identified suitable fungicides for reducing the yield loss of wheat due to leaf rust and also generated important scientific knowledge required to manage a sudden outbreak of leaf rust to ensure food security.

Perception and Management Strategies of the Fall Armyworm, Spodoptera frugiperda J.E. Smith (1797) (Lepidoptera: Noctuidae) on Maize, Millet and Sorghum by Farmers in Western Burkina Faso

Since it was first detected in Africa in early 2016, the fall armyworm (FAW), Spodoptera frugiperda Smith (Lepidoptera: Noctuidae), has spread to over 50 African countries, including Burkina Faso. This insect pest attacks important cereals, such as maize, millet and sorghum, which are the staple food in Burkina Faso. Since the invasion of the FAW in Africa, data on farmers’ knowledge and their perceptions of this insect’s pest are scarce and fragmented in Burkina Faso. Although this issue has been already addressed in some African countries, farmers’ perceptions of this invasive insect pest may differ from one country to another. This reality justifies our study, the main objective of which is to assess the perception and level of knowledge of farmers on this new invasive insect pest and the consequences of its damage to cereal production in western Burkina Faso. To do this, a stratified survey was conducted among 355 farmers in two important agricultural regions of Burkina Faso, namely the Hauts-Bassins and the Cascades. At the end of these surveys, it was found that the age of the people surveyed varied from 18 to 80 years. People between the ages of 41 and 50 and 31 and 40 were the most numerous, with 31.27% and 30.14% of the target population, respectively. In addition, the majority of the farmers were male, 94.08% of them being men and 5.92% being women. More than half (50.42%) of this population was non-literate. Almost all of the farmers surveyed (97.46%) said they had heard of S. frugiperda and 80.85% of them said they could identify the insect pest. The date of appearance of the FAW was variously perceived by the farmers of the study area. According to these cereals growers, the years 2016, 2017, 2018, and 2019 were to be remembered in terms of the insect pest’s appearance. While for sorghum and millet the change in yields from 2010 to 2019 seemed slight, it was quite remarkable for maize according to the farmers. The average maize yield in 2016 and 2017 was 1.95 and 1.83 t/ha, respectively. These values will increase slightly in 2018 and 2019 with 2.08 and 2.39 t/ha, respectively. In the field, several management methods were used by the farmers to control the insect pest’s attacks. These include chemical, cultural, and physical control. Insecticide spray frequencies ranged from 1 to 4 and even more depending on the duration of the maize cycle.

Assessment of Rice Cultivars in China for Field Resistance to Aphelenchoides besseyi

The effect ofAphelenchoides besseyi on 27 cultivars of rice （23japonica and 4 indica） was assessed in the field for two seasons during 2010 and 2011. The vigorous pathogenic nematodes culturing on Botrytis cinerea were used for this experiment. Inoculation was carried out at the tilling stage; the growth parameters and nematode population were recorded at the end of growth of rice plants. The results showed that the cultivars differed in their response to infection. Most of cultivars were lack of the characteristic symptom of white tip, which was seen less frequently than the other two symptoms, namely small grains and erect panicles; moreover, the expression of symptoms was probably hereditary. The infection lowered the values of all the measured biological parameters, namely length of the stem and of the panicle, the number of filled grains per panicle, and 100-grain weight, in all the cultivars. The final nematode population indicated that the threshold of economic damage had also been exceeded in 10 cultivars, and none of them was immune. Three japonica cultivars proved most vulnerable whereas Tetep, an indica type, showed a level of resistance potentially useful in controlling A. besseyi.

Rice Grain Damage by Combination and Sequence Infestations by the Rice Leaffolder, Cnaphalocrocis medinalis Guenee(Lepidoptera: Pyralidae), and the White-Backed Rice Planthopper, Sogatella furcifera Horváth(Hemiptera: Delphacidae)

The rice leaffolder （RLF）, Cnaphalocrocis medinalis Guenée （Lepidoptera：Pyralidae）, and the white-backed rice planthopper （WBPH）, Sogatella furcifera Horváth （Hemiptera： Delphacidae）, are major insect pests in China and several other Asian countries. These two pests commonly occur simultaneously or in a temporal sequence. Thus, the investigation of the effect of complex infestations or temporal sequence infestations by these pests on rice yield has a practical signiifcance for the control of these pests. The present study comprised experiments with the following four different variables in potted rice at the tillering stage：single pest species infestation, complex infestation, complete combination infestation and temporal sequence infestation （C. medinalis infestation prior to S. furcifera and S. furcifera infestation prior to C. medinalis）. The results showed that the four infestations resulted in a signiifcant decrease in 1 000-grain weight （1 000GW） and rate of yield loss （RYL） but an increase in blighted grain rate （BGR）, with a signiifcant positive correlation with the infestation density. However, the inlfuences of the complex infestation, complete combination infestation or sequence infestation on the 1 000GW, BGR and RYL were greater than those of the single pest species infestations but did not have addition effects, i.e., the effects of the complex infestation and combination infestation or sequence infestation on the 1 000GW, BGR and RYL were less than the additive effects of the two single pest species infestations at the same densities. In the condition of the same total infestation pressure, no signiifcant differences in the 1 000GW, BGR and RYL were found between C. medinalis infestation prior to S. furcifera and S. furcifera infestation prior to C. medinalis as well as between the sequence infestation and the complex infestation.

Evaluation of Gray Leaf Spot Tolerant Genotypes from CIMMYT in the Highland Maize Production Eco-systems of Bhutan

Bhutan is a small landlocked country located in the eastern Himalayas. Over 69% of the population is engaged in agriculture. Rice, maize, wheat, barley, buckwheat and millets are the major cereal crops cultivated. Rice is the most preferred food crop of the Bhutanese. Maize is a primary food crop after rice and it ranks first among food crops in production. The cultivation ranges from less than 300 m asl （metres above sea level） nearly up to 2,800 m asl. In 2007, a new, extremely serious problem of GLS （gray leaf spot） in maize that was previously never reported in Bhutan was confirmed. This disease spread rapidly in the highland maize growing areas causing production losses of over 50% to 70%. All the maize varieties cultivated in the country were found to be highly susceptible to the disease. In order to contain this devastating disease, the national maize program drew short and long term strategies with the help of a CIMMYT Expert. As an immediate short term action to contain GLS, systemic fungicide Tilt 25 EC （active ingredient propiconazole） was supplied free of cost to the farmers. A longer term strategy pursued was the introduction, e＇valuation and selection of GLS tolerant genotypes for the highland ecosystem. Over 100 GLS tolerant genotypes vcere introduced from CIMMYT Colombia, Mexico, Zimbabwe and Nepal. These materials were initially evaluated in a disease hotspot sites and then further tested in multi-location trials in GLS affected areas across the country. Farmers were engaged for Participatory Variety Selection by organizing farmer＇s field days at the trial sites. Finally, in 2011 considering the need of GLS tolerant varieties for farmers, two GLS tolerant genotypes ICAV305 and S03TLYQAB05 were provisionally released. In the 2011 season, these two provisionally released genotypes were put under large scale demonstration in the GLS affected areas in nine districts across the country. In 2012, the two genotypes were formally released by the Technology Release Committee of the Ministry of Agriculture and Forest. Rapid seed increase of the new varieties was initiated through farmers from Community Based Seed Production groups and so far 75% seed replacement of GLS affected farmers has been accomplished.

Occurrence,Damage and Control Index of Rape Sclerotinia sclerotiorum in Mechanical Direct Seeding Fields

Real-time monitoring and investigation in fields showed that the disease starting period of Sclerotinia sclerotiorum in mechanical direct seeding fields was earlier. Disease conditions rose with the advancing growth stage, which grew more quickly during the early stage of anthesis, flower withering period and early si- lique mature period. Yield less rate increased with the increasing stem disease rate and disease index. Yield loss rate（ Y1 ） had extremely significant correlation with stem disease rate（X1 ）and disease index（X2 ）, and the related models were Y1 = 0. 544 330 2X1 -2. 316 1 （n = 14, r --0. 986 0 ＊ ＊ ）and YI = 0. 673 408 X2 - 1. 016 4 （ n = 14 ,r = 0.977 2 ~ ＊ ）, respectively. Disease control indexes for one time control against S. sclerotlorum in mechanical direct seeding fields were stem disease rate as 11.8% and disease index as 7.6, respectively. The control indexes for twice control against the disease were stem disease rate as 16.8% and disease index as 11.7. This paper provided a new scientific basis for preventing S. sclerotiorum in mechanical direct seeding fields.

Impact Factors on Fracturing Results of Coal Seams and Appropriate Countermeasures

Hydraulic fracturing is one of the efficient means for the abundant low-permeability CBM （coal-bed methane） reserves in China, however, due to the unique features of coal seams （i.e., low temperature, strong adsorption and abnormal development of natural fracture systems） as compared with the conventional reservoirs, the fractures propagate is difficult and the risk of damage to coal seam itself and the hydraulic fractures would be extremely high in the course of fracturing. As a result, losses would be suffered on the post-frac production of CBM wells.With the mean of numerical simulation, in this paper, the main factors have impact on the post-frac results as well as the extent to which the impact is brought were researched, and the technical solutions for the improvement of the fracturing performance was put forwards.

Ozone concentrations, flux and potential effect on yield during wheat growth in the NorthwestShandong Plain of China

Ozone（O3） concentration and flux（Fo） were measured using the eddy covariance technique over a wheat field in the Northwest-Shandong Plain of China. The O3-induced wheat yield loss was estimated by utilizing O3exposure-response models. The results showed that：（1） During the growing season（7 March to 7 June, 2012）, the minimum（16.1 ppb V） and maximum（53.3 ppb V）mean O3 concentrations occurred at approximately 6：30 and 16：00, respectively. The mean and maximum of all measured O3 concentrations were 31.3 and 128.4 ppb V, respectively. The variation of O3 concentration was mainly affected by solar radiation and temperature.（2） The mean diurnal variation of deposition velocity（V d） can be divided into four phases, and the maximum occurred at noon（12：00）. Averaged V d during daytime（6：00–18：00） and nighttime（18：00–6：00） were 0.42 and 0.14 cm/sec, respectively. The maximum of measured V d was about1.5 cm/sec. The magnitude of V d was influenced by the wheat growing stage, and its variation was significantly correlated with both global radiation and friction velocity.（3） The maximum mean F o appeared at 14：00, and the maximum measured F o was-33.5 nmol/（m^2·sec）. Averaged F o during daytime and nighttime were-6.9 and-1.5 nmol/（m^2·sec）, respectively.（4） Using O3 exposure-response functions obtained from the USA, Europe, and China, the O3-induced wheat yield reduction in the district was estimated as 12.9% on average（5.5%–23.3%）. Large uncertainties were related to the statistical methods and environmental conditions involved in deriving the exposure-response functions.

Damage evaluation of soybean chilling injury based on Google Earth Engine(GEE)and crop modelling

Frequent chilling injury has serious impacts on national food security and in northeastern China heavily affects grain yields.Timely and accurate measures are desirable for assessing associated large-scale impacts and are prerequisites to disaster reduction.Therefore,we propose a novel means to efficiently assess the impacts of chilling injury on soybean.Specific chilling injury events were diagnosed in 1989,1995,2003,2009,and 2018 in Oroqen community.In total,512 combinations scenarios were established using the localized CROPGRO-Soybean model.Furthermore,we determined the maximum wide dynamic vegetation index(WDRVI)and corresponding date of critical windows of the early and late growing seasons using the GEE(Google Earth Engine)platform,then constructed 1600 cold vulnerability models on CDD(Cold Degree Days),the simulated LAI(Leaf Area Index)and yields from the CROPGRO-Soybean model.Finally,we calculated pixel yields losses according to the corresponding vulnerability models.The findings show that simulated historical yield losses in 1989,1995,2003 and 2009 were measured at 9.6%,29.8%,50.5%,and 15.7%,respectively,closely(all errors are within one standard deviation)reflecting actual losses(6.4%,39.2%,47.7%,and 13.2%,respectively).The above proposed method was applied to evaluate the yield loss for 2018 at the pixel scale.Specifically,a sentinel-2A image was used for 10-m high precision yield mapping,and the estimated losses were found to characterize the actual yield losses from 2018 cold events.The results highlight that the proposed method can efficiently and accurately assess the effects of chilling injury on soybean crops.

Effects of land management practices and land cover types on soil loss and crop productivity in Ethiopia:A review

Identifying land management practices(LMPs)that enhance on-site sediment management and crop productivity is crucial for the prevention,reduction,and restoration of land degradation and contributing to achieving land degradation neutrality(LDN).We reviewed studies in Ethiopia to assess the effects of LMPs on soil loss(84 studies)and crop productivity(34 studies)relative to control practice.Yield variability on conserved lands was assessed using 12,796 fixed plot data.Effects of LMP on soil loss were 0.5-55 t ha^(−1)y^(−1)compared to control practices yielding 50 to 140 t ha^(−1)y^(−1).More than 55%of soil loss records revealed soil loss less than the tolerable rate(10 t ha^(−1)).Area closure,perennial vegetation cover,agronomic practices,mechanical erosion control practices,annual cropland cover,and drainage groups of practices led to 74.0±18.3%,69.0±24.6%,66.2±30.5%,66.1±18.0%,63.5±20.0%,and 40±11,1%soil loss reduction,respectively.A yield increase of 25.2±15.0%,37.5±28.0%,and 75.4±85.0%was found from drainage,agronomy,and mechanical erosion control practices,respectively.The average yield loss by erosion on fields without appropriate land management practice and on conserved fields was 26.5±26.0%and 25±3.7%,respectively.The findings suggest that practices that entail a continuous presence of soil cover during the rainy season,perennial vegetation,retention of moisture,and barriers for sediment transport were most effective at decreasing soil loss and increasing productivity.This review provides evidence to identify the best LMP practices for wider adoption and inform decision-making on LMP investments towards achieving sustainable solutions to reverse land degradation.