Effect of No Tillage and Conventional Tillage on Wheat Grain Yield Variability: A Review

Conservation Agriculture(CA)covers more than 205 million hectares in the world.This made it possible to face and mitigate the challenges of climate change,reducing soil erosion and providing multiple ecosystem services.The first elementary factor influenced is the yield evaluation.It has a direct effect on farmers’choices for sustainable production.The present article records a review focused on wheat yield average positive change compared between conventional tillage(CT)and no tillage(NT)systems.The international database collected showed that NT is adaptable everywhere.The results of wheat yield differentiation showed the influence of crop rotation depending on stations located in different climatic zones.In more than 40 years of research,specialists have succeeded in demonstrating the importance of crop productivity like wheat.The whole integrates also experimentations where the initiation starts more than ten years.

Variation of Physical and Chemical Properties of Soils under Different Cropping Systems in the Watershed of Kpocomey, Southern Benin

Soils degradation is one of the constraints in food security achievement in Benin. This study aimed at assessing the effect of cropping systems and slope on soil physical and chemical properties in the watershed of Kpacomey located in the Aplahoué district. Soil samples were collected from three parallel transects along the slope. Sampling was carried out under different treatments combining cropping systems (Maize-Cassava, pure Palm grove, Palm grove-Maize-Cassava and Teak Plantation) along with slope levels (low slope, medium slope and high slope degree). The impact of cropping systems and slope on soil properties was assessed by determining the physical and chemical parameters. The cropping systems significantly (p < 0.05) influenced soil bulk density, root biomass, soil acidity and soil organic matter. The lowest soil bulk density (1.38 g/cm3) was recorded under the Palm grove-Maize-Cassava cropping system while the highest (1.47 g/cm3) was obtained with pure Palm grove cropping system. Root biomass was more abundant (0.28%) with the pure Palm grove cropping system. However, root biomass was significantly (p < 0.05) influenced by slope. Soil crusting resulted in no significant influence (p > 0.05) on the effect of cropping systems and slope. Moreover, cropping systems resulted in significant effects (p < 0.05). Soil organic matter and soil-assimilated phosphorus content were significantly influenced by the effect of the slope. These findings indicated that cropping systems and slope are significant drivers in soil degradation in the Kpacomey watershed and bringing out cropping systems that best aim at soil conservation.

Study of Radio-Sensitivity of Strawberry Runners <i>cv. Fortuna</i>under Moroccan Conditions

In recent years, strawberry is being successfully cultivated in Loukkos perimeter of Morocco and a wide range of varieties are being grown. The strawberry crop also generates 3 million working days per year. In fact, all plants are imported and prices are exorbitant. Varietal improvement is essential if a new impetus is to be given to the morocco strawberry. We have accordingly started a mutation breeding program by bud irradiation. Strawberry runners of cv. Fortuna were exposed to increasing doses of acute gamma rays. The physiological effects induced by irradiation were evaluated from cutting survival and growth. It has been determined that the doses of gamma and the varieties used are significant on the number of surviving plants and plant growth parameters. It was determined that low doses gamma irradiation respectively affected plant height, leaf length, leaf width and the number of leaves. These results allowed us, in the first instance, to fix the optimal dose range for cutting irradiated at 62 Grays.

Evaluation of the Compaction of a No-Till Vertisol Field Using Methods of Cone Index and Pedotransfer Function in Semi-arid Context of Morocco

This study evaluated compaction level of a 15-year old no-till vertisol field crop(40.91%clay,44.16%loam and 14.93%sand)having organic matter contents of 2.23%and 2.91%in 0-10 cm and 10-20 cm profiles,respectively.The bulk density ranged from 1.30 g/cm^3 to 1.80 g/cm^3 in the field boundaries,and from 1.01 g/cm^3 to 1.40 g/cm^3 in its center.The field showed a gradient of limestone from 3%to 13%.Measurements were done to evaluate soil strength(cone index)and soil plasticity(Atterberg limits).The soil strength showed different levels of compaction from 4.5 MPa to 16 MPa to distinct five spatial clusters in the field.The soil compactness was related to limestone gradient according the correlation found between the soil strength and limestone levels.The soil plasticity test showed occurrence of plastic limits when the moisture content decreased from 26%to 15%within 5 d interval.The Atterberg limits showed the importance of respecting intervention delays to avoid soil compaction due to its plasticity.A pedotransfer function was developed using soil parameters of texture,organic matter,bulk density,cohesion,internal friction angle and moisture content to compute its precompression stress.Results showed importance of compaction in the field extremities due to importance of machines/tools traffic without avoiding cropping interventions during soil plasticity state.The soil strength(as measured value)was correlated to precompression stress(as estimated values)to show the importance of using pedotransfer function as significant method to evaluate indirectly compactness or susceptibility to compaction of the studied vertisol.

Biocontamination Risk of <i>Staphylococcus aureus</i>in Dairy Manufacturing Presence of Two Types of UHT Milk

The biofilm formation on equipment surfaces in dairy manufacturing is a major concern for industry and consumers alike, which may affect the safety and quality of dairy products. In order to identify the bio-contamination risk of materials commonly used in dairy manufacturing, adhesion of Staphylococcus aureus on glass coated by two kinds of UHT milk (whole milk and skimmed milk) was investigated. It is known that adhesion is mainly governed by surface physicochemical properties, for that, the effect of milk components on physicochemical properties of glass and bacterial surfaces were exanimated through contact angle measurements. MATLAB software was used to evaluate the ability of S. aureus adhesion on glass. The hydrophobic quantitative and electron acceptor characteristics of the glass appear to increase with the presence of fat in milk, while its electron donor property decreases with this component. The percentage of occupied surface of untreated glass was more important than in treated surfaces for 50% of the strains studied. As well, the percentage of occupied surface by bacterial strains in untreated glass by skimmed milk is generally more important compared to the whole milk. Therefore, the risk of bio-contamination of untreated glass is more favorable for bacteria cultured in skimmed milk compared to these in whole milk but the bio-contamination risk on covered glass by milk is not milk dependent and is strain dependent.

Spatial and statistical assessment of nitrate contamination in groundwater:Case of Sais Basin, Morocco

The objective of this study is to evaluate the nitrate contamination in the plioquaternary aquifer of Sais Basin based on a statistical approach. A total of 98 samples were collected in the cultivated area during the spring and autumn period of 2018. The results show that 55% and 57% of the samples in spring and autumn respectively exceed the threshold fixed by WHO(50 mg/L). However, nitrate concentrations do not show seasonal and spatial variation(p>0.05). The results of the correlation matrix, principal component analysis(PCA), and hierarchical cluster analysis(HCA) suggest that nitrate pollution is related to anthropogenic source. Moreover, multiple linear regression results show that NO3 is more positively explained in the spring period by Ca and SO4 and negatively explained by pH and HCO3. Regarding the autumn period, nitrate pollution is positively explained by Ca and negatively by pH. This study proposes a useful statistical platform for assessing nitrate pollution in groundwater.

Assessment of the Spatial Uncertainty of Nitrates in the Aquifers of the Campania Plain (Italy)

We present a non-parametric hydro-geostatistical approach for mapping design nitrate hazard in groundwater. The approach is robust towards the uncertainty of the parametric models used to map groundwater pollution. In particular, probability kriging (PK) estimates the probability that the true value of a pollutant exceeds a set of threshold values using a binary response variable (probability indicator). Such soft description of the pollutant can mitigate the uncertainty in pollutant concentration mapping. PK was used for assessing nitrate migration hazard across the Campania Plain groundwater (Southern Italy) as exceeding typical critical values set to 25 and 50 mg.L-1. Cross-validation indicated that the PK is more suitable than ordinary kriging (OK), which yields large uncertainty in absolute values prediction of nitrate concentration. This means that spatial variability is critical for contaminant transport because critical contaminants concentration could be exceeded due to preferential flows allowing the pollutant to migrate rapidly through the caveats aquifer. Accordingly with PK application, about 250 km2 (40% of the total600 km2 of the Campania Plain) were classified as very sensitive areas (western zone) to maximum permissible concentration of nitrates (>50 mg.L-1). When the probability to exceed 25 mg.L-1 was considered, the contaminated surface increased to 70% of the total area.

Influence of Watering Solution and Phenotype on the Growth of <i>in Vitro</i>Propagated Pineapple (Smooth Cayenne Cultivar) Plantlets during Acclimatization

Pineapple is the first fruit crop cultivated in south Benin that greatly contributes for food and nutritional security and farmers’ income. But the lack of homogenous planting material constitutes the major constraint for improving pineapple yield. In vitro micropropagation is now used in the production of homogenous and free disease planting materials of pineapple. However, the acclimatization to natural condition of pineapple plantlets is an important step in planting material production of this crop. Here, we determined the intrinsic and extrinsic factors which influence the behavior of plantlets during the acclimatization process. For this purpose, plantlets from different categories were selected, trimmed and planted on a horticultural substrate made up of potting soil, white sawdust and compost previously sterilized. The plantlets were then incubated in under acclimatization greenhouse with average temperature of 29˚C and 70.2% of humidity. A batch of plantlets was subjected to two different watering solutions: Shive and Robbins solution and NPK 14-6-5 foliar fertilizer. The results obtained initially showed high rate (100%) of survival and growth of the plantlets watered with Shive and Robbins solution against 50% of the plantlets watered with the foliar fertilizer solution. In addition, the plantlets with spread pores exhibiting the characteristics of which the number of leaves varies between 9 and 11, the weight between 1.2 and 1.5 g, the size of 4.5 to 5.5 cm, and a good junction between the aerial part and the root system were those which were successfully grown in acclimatization phase under greenhouse, unlike plantlets with erected pores having lower success rate. This study goes a long way in providing good procedures of acclimatization of homogenous and free disease planting material of pineapple to the famers.

Dynamics of Land Use in the Basin of Ancient Lagoons (Toho, Todougba, Ahouangan, Dati, Djonou) in South Benin from 1990 to 2020 and Their Current Vulnerability to Pollution

The management of living resources and space requires continuous assessments in order to adjust deviations as necessary for sustainable use. It is in this context that the present study was conducted and aims on the one hand to assess the dynamics of land use in the basin of the five-finger lagoons and on the other hand to assess the degree of their vulnerability to organic pollution. Thus, the satellite images were collected in free access on the site http://earthexplorer.usgs.gov/ of the USGS (US Geological Survey) of NASA. Image correction was performed with ENVI 5.1 software and classification was performed with ArcGIS 10.8 software. The degree of vulnerability was evaluated through the weighting of different parameters (slope, land use, type of pass, runoff, and density of the hydrobiological network) by the multi-criteria method of Saaty (Analytic Hierarchy Process Methods) and the application of mapping. It is found that for the dynamics of land use, forests, savannahs and plantations have experienced a significant reduction in their area (respectively 98.9%, 99.60% and 77.10%) between 1990 and 2020. As for settlements, water bodies and swamps, they have increased in area to different proportions. The soils are more denuded (Tc = 1264%). This makes the living space vulnerable and therefore facilitates the transfer of pollutants to the aquatic environment. The evaluation of the degree of vulnerability to pollution of the lagoons of the basin showed that the Toho-and Todougba lagoons are under a very high degree of vulnerability (73% - 100%) and do not augur well for the living resources. The other lagoons, notably the Dathi and Djonou lagoons, are also under stress from the pressures of surrounding activities. It is therefore important to assess the level of pollution of the Toho and Todougba lagoons through pollution indices in order to make decisions that will allow their sustainable use, especially for aquaculture.

Productivity of cotton and sorghum in an agroforestry system of shea trees(Vitellaria paradoxa gaertn)in northern Benin

This study evaluates the productivity of cotton and sorghum in a shea-based agroforestry system in northernBenin. Tomboutou and Gounarou villages were respectively selected in the shea parklands of Bembèrèkè and Kandi. Within each parkland and village, three classes of tree crown diameter for shea trees (4 -8 m, 8 -10 mand <10 m), were defined after the inventory phase. In each class of crown diameter, three trees intercropped with cotton and sorghum were randomly selected among the 18 to 21 farms in each of the two village territories. The crops were planted in accordance with the technical procedures recommended by the national agricultural extension service. The following data was collected for sorghum and cotton on1 m2area under the crown and outside the crown, in the four cardinal directions of each sample tree: crop height, fresh biomass per crop and buds per cotton plant. Data analysis revealed a very significant difference in the variables (height of sorghum and cotton, biomass of cotton and sorghum, number cotton buds) between the areas under the crown and those outside the crown (P < 0.01). The productivity variables for sorghum, i.e., average plant height and average biomass, dropped by 9.75% and 29.31%, respectively, when planted under the crown. Cotton under the crown was 6.58% shorter compared to plants outside the crown. Average bud production and average fresh biomass for cotton plants was 13.06% and 36.06% less, respectively, when planted under the crown of shea trees.

Alternate phenotype–genotype selection for developing superior high-yielding irrigated rice lines

Increase grain yield potential is one of the most important objectives of any cereal crop breeding program. To efficiently develop superior rice lines by the introgression of favorable alleles for yield and yield component traits, a strategy of alternate phenotype–genotype selection was used. The present study aimed to(i) investigate the allelic diversity of loci associated with major yield-component traits and(ii) phenotype and genotype advanced populations derived from crosses between NERICA-L-20 and Giza178 for yield component traits using agro-morphological descriptors and GRi SP polymorphic markers to select superior high-yielding rice lines. A total of 100 F2:3 progeny were selected from 1000 F2 plants and genotyped with 16 polymorphic markers linked to four major yield-component traits. Four promising F2:3 lines(ARS 563–14, ARS 563–62, ARS 563–286, and ARS 563–41)bearing combinations of desirable alleles were selected. A selected set of 20 F2:4 lines showed moderate to high heritability for all target traits. Fourteen F2:5 lines derived from ARS 563–14 and 17 F2:5 from ARS 563–286 families were evaluated in preliminary trials to estimate yield gain. The three top lines, ARS 563–286–16-1-1, ARS 563–286–5-1-1, and ARS563–14–10-1-1, showed an increase of more than 10% grain yield over the best check, Sahel108, which is widely cultivated in the Senegal River valley. The 16 markers linked to the target yield component traits can be used to fast-track breeding programs targeting rice productivity.

Dissipation of chlorpyrifos, pendimethalin, and thiophanate-methyl pesticides in compost based-versus peat-moss based-biomixture of biobeds

Biobed is a smart bioremediation system used to treat point-source pesticide contamination.Biomixture is the main component of biobeds,and pesticide dissipation is affected by its composition.This study aimed to compare the effectiveness of compost-based(C)versus peat-moss-based(P)biomixtures of biobeds on tested pesticide dissipation.Three concentrations(25,50,and 75 mg/kg)of chlorpyrifos,pendimethalin,and thiophanate methyl were added separately and as a mix to both biomixtures C and P.Our data showed the effect of biomixture type on the dissipation of the tested pesticides.For chlorpyrifos,its dissipation rate in biomixture P was more rapid than that in biomixture C.This result was confirmed by the mineralization kinetic experiment,since 25%of the initial ^(14)C-chlorpyrifos concentration accumulated in the form ^(14)CO_(2) in biomixture P compared to only 14%in biomixture C.In addition,the chlorpyrifos dissipation rate was influenced by the initial concentration when applied individually in biomixture P.In contrast,biomixture C was more effective at pendimethalin dissipation than biomixture P,since>76%of pendimethalin was dissipated in biomixture C versus 67%in biomixture P at the same incubation time.For thiophanate-methyl,the abilities of both biomixtures C and P were similar and less efficient than those of the other tested pesticides.The addition of the three tested pesticides to biomixture C only had a positive effect on both chlorpyrifos and thiophanate-methyl dissipation,while pendimethalin dissipation was similar when applied separately or as a mix.Microbial activity was stimulated by the addition of separately or mixed pesticides to biomixtures C and P as measured by dehydrogenase activity.

CactiViT:Image-based smartphone application and transformer network for diagnosis of cactus cochineal

The cactus is a plant that grows in many rural areas,widely used as a hedge,and has multiple benefits through the manufacture of various cosmetics and other products.However,this crop has been suffering for some time from the attack of the carmine scaleDactylopius opuntia(Hemiptera:Dactylopiidae).The infestation can spread rapidly if not treated in the early stage.Current solutions consist of regular field checks by the naked eyes carried out by experts.The major difficulty is the lack of experts to check all fields,especially in remote areas.In addition,this requires time and resources.Hence the need for a system that can categorize the health level of cacti remotely.To date,deep learning models used to categorize plant diseases from images have not addressed the mealy bug infestation of cacti because computer vision has not sufficiently addressed this disease.Since there is no public dataset and smartphones are commonly used as tools to take pictures,it might then be conceivable for farmers to use them to categorize the infection level of their crops.In this work,we developed a system called CactiVIT that instantly determines the health status of cacti using the Visual image Transformer(ViT)model.We also provided a new image dataset of cochineal infested cacti.1 Finally,we developed a mobile application that delivers the classification results directly to farmers about the infestation in their fields by showing the probabilities related to each class.This study compares the existing models on the new dataset and presents the results obtained.The VIT-B-16 model reveals an approved performance in the literature and in our experiments,in which it achieved 88.73%overall accuracy with an average of+2.61%compared to other convolutional neural network(CNN)models that we evaluated under similar conditions.

Plant Phenomics:Emerging Transdisciplinary Science

Humankind is facing an unprecedented challenge to produce enough food for the coming decades because of population growth and increase in the average demand per capita,changes in climate conditions,and limitations in arable land area,as well as pressure on the water and resources.Two main avenues should be concurrently taken to increase crop productivity:improving genetics to get more efficient and resilient crops and developing optimal crop management practices.The description and understanding of crop functioning will therefore be instrumental both for genetic improvement and crop management.It will help to associate functional traits with the genome which will accelerate genetic progress by having more efficient techniques to design ideotypes adapted to particular pedoclimatic and crop management conditions and create them from the available genetic diversity.

Do model choice and sample ratios separately or simultaneously influence soil organic matter prediction?

This study was performed to examine the separate and simultaneous influence of predictive models’choice alongside sample ratios selection in soil organic matter(SOM).The research was carried out in northern Morocco,characterized by relatively cold weather and diverse geological conditions.The dataset herein used accounted for 1591 soil samples,which were randomly split into the following ratios:10%(∼150 sample ratio),20%(∼250 sample ratio),35%(∼450 sample ratio),50%(∼600 sample ratio)and 95%(∼1200 sample ratio).Models herein involved were ordinary kriging(OK),regression kriging(RK),multiple linear regression(MLR),random forest(RF),quantile regression forest(QRF),Gaussian process regression(GPR)and an ensemble model.The findings in the study showed that the accuracy of SOM prediction is sensitive to both predictive models and sample ratios.OK combined with 95%sample ratio performed equally to RF in conjunction with all the sample ratios,as the latter did not show much sensitivity to sample ratios.ANOVA results revealed that RF with a∼10%sample ratio could also be optimum for predicting SOM in the study area.In conclusion,the findings herein reported could be instrumental for producing cost-effective detailed and accurate spatial estimation of SOM in other sites.Furthermore,they could serve as a baseline study for future research in the region or elsewhere.Therefore,we recommend conducting series of simulation of all possible combinations between various predictive models and sample ratios as a preliminary step in soil organic matter prediction.

Earthworm contributions to soil nitrogen supply in corn-soybean agroecosystems in Quebec, Canada

Accurately quantifying the soil nitrogen(N)supply in crop fields is essential for enabling environmentally sustainable and economically profitable crop production.It requires using field-based methods to account for the contribution of soil biota,including earthworms,to N mineralization in temperate agroecosystems.The direct contribution of earthworms to the soil N cycle is the N they release throughout their life and after death,and it can be estimated using the secondary production method.This study was conducted in 2014 and 2015 in two adjacent fields with annual corn-soybean rotation in Ste-Anne-de-Bellevue,Quebec,Canada.The cumulative biomass of Aporrectodea spp.in two no-till corn-soybean agroecosystems was determined,and the direct N flux from these earthworms was estimated during the corn and soybean phases of the rotation.Secondary production was estimated by sampling earthworms biweekly during April-June and September-November and inferring the change in earthworm biomass between sampling dates using a size frequency calculation.The N flux was calculated as the sum of the N released through excretion,during periods when earthworms were active,and from mortality.The secondary production of the Aporrectodea population was estimated to be 8-43 g ash-free dry weight m^(-2) year^(-1),and the N flux was 22-105 kg N ha^(-1 )year^(-1).The N flux was higher at the early vegetative growth stage,which is a period of high N demand for corn.These findings suggest that refining the N fertilization recommendation by accounting for soil N supplied by earthworms could potentially reduce fertilizer costs and environmental N losses.

Mapping soil nutrients via different covariates combinations:theory and an example from Morocco

Background:Mapping of soil nutrients using different covariates was carried out in northern Morocco.This study was undertaken in response to the region’s urgent requirement for an updated soil map.It aimed to test various covariates combinations for predicting the variability in soil properties using ordinary kriging and kriging with external drift.Methods:A total of 1819 soil samples were collected at a depth of 0–40 cm using the 1-km grid sampling method.Samples were screened for their pH,soil organic matter(SOM),potassium(K_(2)O),and phosphorus(P_(2)O_(5))using standard laboratory protocols.Terrain attributes(T)computed using a 30-m resolution digital elevation model,bioclimatic data(C),and vegetation indices(V)were used as covariates in the study.Each targeted soil property was modeled using covariates separately and then combined(e.g.,pH~T,pH~C,pH~V,and pH~T+C+V).k=tenfold cross-validation was applied to examine the performance of each employed model.The statistical parameter RMSE was used to determine the accuracy of different models.Results:The pH of the area is slightly above the neutral level with a corresponding 7.82%of SOM,290.34 ppm of K_(2)O,and 100.86 ppm of P_(2)O_(5).This was used for all the selected targeted soil properties.As a result,the studied soil properties showed a linear relationship with the selected covariates.pH,SOM,and K 2O presented a moderate spatial autocorrelation,while P2O5 revealed a strong autocorrelation.The cross-validation result revealed that soil pH(RMSE=0.281)and SOM(RMSE=9.505%)were best predicted by climatic variables.P_(2)O_(5)(RMSE=106.511 ppm)produced the best maps with climate,while K_(2)O(RMSE=209.764 ppm)yielded the best map with terrain attributes.Conclusions:The findings suggest that a combination of too many environmental covariates might not provide the actual variability of a targeted soil property.This demonstrates that specific covariates with close relationships with certain soil properties might perform better than the compilation of different environmental covariates,introducing errors due to randomness.In brief,the approach of the present study is new and can be inspiring to decision-makers in the region and other world areas as well.