Impact of Composts Maturity on Growth and Agronomic Parameters of Maize (<i>Zea mays</i>)

Several methods have been developed in the literature which allow the maturity of composts to be assessed before it is used in agriculture. The objective of this study is to assess the maturity of the composts produced at the platform of the NGO ENPRO in Lomé on the growth and agronomic parameters of maize (Zea mays L., var. IKENE). To do so, three types of compost (gargabe, fruit waste, animal litter) were made for at least 3 months. The chemical analysis, phytotoxicity and agronomic tests carried out made it possible to assess the maturity of these composts. Indeed, the evolution of the C/N ratio, of the electrical conductivity, the phytotoxicity tests and the growth parameters of the composts show that the composts N°1 and N°2 are mature at the end of the 3rd month of composting while the compost N°3 can only be considered mature at the end of the 5th month of composting. But, with a yield of 2.39 ± 0.28 t/ha and a mass of 1000 grains of 346 ± 4 g, the treatment at 5 t/ha of compost N°3, has the best agronomic parameters compared to other types of compost and treatment without organic amendment. These results also show that compost with a high electrical conductivity has an inhibitory effect on the growth of corn plants (Zea mays L., var. IKENE). Basic chemical analysis, phytotoxicity tests and height growth of maize (Zea mays L., var. IKENE) are relatively efficient methods for evaluating the maturity of composts.

Effects of Management Practices on Agronomic Parameters in Cocoa Agroecosystems at Peripheral Zone of Ebo Forest Reserve, Littoral Region, Cameroon

The study was carried out to assess the effect of management practices on agronomic parameters of cocoa agroecosystems in the peripheral zone of Ebo Forest Reserve. Purposive random sampling was conducted to establish experimental plots on the farms of willing farmers. Demonstration plots were established and agronomic parameters were monitored for “farmers’ practice (FP) and integrated crop pest and disease management (ICPM) practice” using indicators of Cocoa agro-ecosystem analysis (AESA). The FP and ICPM treatments were replicated in ten sites. From AESA records of agronomic parameters, the “observe, learn, decide and act” (OLDA) model was implemented in the ICPM treatments only. The effects of management practices were analyzed using a two-way analysis of variance (ANOVA), and treatment means compared using Turkey’s T-test at 5% probability. Results of ANOVA between the two Management practices showed that over 50% of the response variables were statistically significant. Means separated through GLM ANOVA with Tukey pairwise comparisons at α = 0.05 showed that 14 (53.8%) out of 26 response variables monitored were statistically significant between the two management practices. Pruning, shade management, phytosanitary harvest, rational use of pesticides, farm sanitation, pod harvesting, breaking, fermentation of beans and drying were regular in the ICPM treatment and time-bound in the FP treatment. The average total production varied from 385.83 kg/ha in FP treatment to 572.8 kg/ha in the ICPM treatment, still below the average standard of 1000 kg/ha. The OLDA model applied in ICPM treatment following AESA is a relevant tool to enhance sustainability in the management of cocoa agroecosystems. Farmers should be sensitized and trained on appropriate farm management techniques and enhance access to extension services as well as make available improved and grafted planting materials to ensure appropriate productivity levels.

Yield Estimation Model of Citrus Based on Spectral Data and Agronomic Parameters

With the development of precision agriculture, the research that applies Remote Sensing technology, especially hyperspectral remote sensing, to realize crop management, monitoring and yield estimation, has been concerned. Nowadays, the growth-monitoring and yield-estimating methods in rice, wheat and other annual crops develop rapidly with some achievements having already been put into service. But the yield estimation research on perennial economic crops is few. Taking peren- nial citrus trees as the research object, using ASD spectrometer to collect citrus canopy spectral, this article studied and analyzed the citrus of veget＆tion index and its relationship on yield, synthetically considered the influence of the agriculture pa- rameters on crop yield, and finally constructed the citrus yield estimation model based on the spectral data and agronomic parameters. Through the Significance Test and Samples＇ Test, olutained that the model＇s fitting degree was R=0.631, F= 13.201, P〈0.01 and the error rate of estimating accuracy was controlled in the range 3%-16%, proving that the model has statistical signification and reliability. It concluded that hyperspectral acquired from citrus canopy has substantial potential for citrus yield estimation. This study is an application and exploration of Hyperspectral Remote Sensing technology in the citrus yield estimation.

Relations Between Red Edge Characteristics and Agronomic Parameters of Crops

The hyperspectral reflectance of the canopy and the leaves on the main stemfor six varieties, two each of rice corn, and cotton crops, were measured at different growth stageswith an ASD FieldSpec Pro FR^(TM) to analyze red edge characteristics forleaf area indices (LAI),aboveground biomass, as well as the chlorophyll, carotenoid, and nitrogen content, emphasizingcomparative differences on the red edge parameters. The results showed a 'double peak' phenomenonfor the red edge of the canopy spectra but not for the leaves. There were 'increase' and 'decrease'change rules for the red edge position, lambda_r, the red edge slope, D lambda_r, and the red edgearea, S_r, of the canopy spectra for all 3 crops with a 'blue shift' for lambda_r of the leafspectra for all 3 crops as the development stages progressed. For rice, corn, and cotton the LAI andfresh leaf mass had highly significant correlations (P < 0.01) to the red edge parameters lambda_r,D lambda_r, and S_r of their canopy spectra. Additionally, for all crops the chlorophyll-a,chlorophyll-b, total chlorophyll, and carotenoid content of the leaves all had highly significant (P< 0.01) correlations to their lambda_r. For rice, the nitrogen content of the leaves in g kg^(-1)and phytomassfor a unit area of land in g m^(-2) also had a highly significant (P < 0.01)correlation to lambda_r, D lambda_r lambda_r, and S_r of the canopy spectra.

Response of upland rice agronomic parameters to variable water supply

Rice response to water application is necessary for increased productivity;hence,this study was aimed at establishing the agronomic responses of rice crop to differential water supplies.A two-year dry season experiment was conducted on the research farm of International Institute of Tropical Agriculture(IITA),Ibadan,Nigeria.Two upland rice varieties(NERICA 2 and NERICA 4)were planted on a 5 m×5 m plot in a randomized complete block design with four treatments and two replicates based on different water application.Irrigation scheduling was designed as 100%ET,75%ET,50%ET and 25%ET for the treatments weekly.Agronomic parameters such as plant height,root depth,canopy shading(CS),leaf area index(LAI),panicle and tiller configuration,biomass and grain yield in relation to crop water use were obtained and the results were subjected to statistical analysis.Average values of highest plant height(89.0 and 100.3 cm),deepest root depth(22.1 and 23.8 cm),panicle diameter(3.9 and 4.5 cm),panicle length(26.1 and 25.7 cm),LAI,3.27 and 3.95,CS,0.22 and 0.99 were obtained for both NERICA 2 and NERICA 4 respectively.Leaf width(1.3 and 1.4 cm),total tillers(14 and 12)and leaf length(36.9 and 38 cm)were also observed for the two varieties respectively.The highest total grain and biomass yields of 1.94 t/ha and 1.95 t/ha were observed in 100%ET treatment for NERICA 2 while the least values of 0.29 t/ha and 1.09 t/ha were observed in 25%ET treatment.As for NERICA 4,the highest values(1.90 t/ha and 2.27 t/ha)were from 100%ET and the least(0.38 t/ha and 2.29 t/ha)in 25%ET.The result of ANOVA showed significant differences in biomass and grain yield,LAI,CS,plant height and root depth among treatments(P<0.05)stressing the domineering influence of water in agronomic response of rice.

Influence of Harvest Periods on Cassava (Manihot esculenta Crantz) Agronomic Traits and Physiological Response to Post-Harvest Physiological Deterioration

Cassava (Manihot esculenta Crantz) is the third largest source of calories in tropical countries and the sixth most important food crop in the World. However, the short shelf life of its storage roots after harvest due to a rapid post-harvest physiological deterioration (PPD) makes the roots to be considered as a risky product to market. The objectives of this work were to investigate the influence of two harvest periods on cassava agronomic parameters and their physiological response to PPD. Three cassava cultivars 96/1414, I070593 and LMR were selected for the experiment and harvested at 10 and 12 months after planting (MAP). The response to PPD was assessed during storage at 0, 3, 8 and 15 days after harvest (DAH). Total proteins content, soluble sugars and starch, total polyphenols compounds, polyphenoloxidase and peroxidase activities were recorded during storage. Results showed large variation among the parameters at the two harvest periods across the cultivars. High number of tubers was recorded in all the cultivars at 12 MAP and a significant increase in storage roots length was observed in 96/1414 and LMR from 10 MAP to 12 MAP (25 ± 5.1 to 41.3 ± 5.9 and 22.6 ± 3.3 to 27.9 ± 4.8) respectively. A reduction of about 49% of tubers weight was observed in I070593 from 10 to 12 MAP while an increase of about 36% and 11% were recorded in LMR and 96/1414 respectively. Tubers from I070593 showed less susceptibility to PPD when harvested at 10 MAP compared to those from LMR and 96/1414 where less susceptibility to PPD were recorded at 12 MAP. An increase in soluble sugars content, total proteins content and peroxidase activity subsequently to a decrease in starch content were recorded during storage from 8 to 15 days after harvest especially at 10 MAP in I070593 and at 12 MAP in LMR and 96/1414. High content of total phenolic compounds and less activity of polyphenol oxidase were correlated to PPD susceptibility. This work opens a new insight issue of the consideration of the appropriate harvest time of the cultivars as a tool to better control the onset of postharvest physiological deterioration.

Antifungal Potential of Beauveria bassiana on Solanum lycopersicum L. Infected with Fusarium oxysporum f. sp. lycopersici

The objective of this work was to evaluate the effect of Beauveria bassiana(Bb 1205)on controlling Fusarium oxysporum f.sp.lycopersici(Fol 17108)in tomato plants in greenhouse conditions.Inoculation of Bb 1205 was the most promising among the agronomic variables and expression of the activity of the enzymesβ-1,3-glucanases and chitinases.Inoculation of Bb 1205 occurred at a concentration of 1×108 conidia·mL−1,which was administered onto the leaves,directly into the soil and via injection.Infection with Fol 17108 occurred with 1×106 spores·mL−1,which were added directly to the soil.Spectrophotometry was used for measuring agronomic parameters,namely activity of chitinases andβ-1,3-glucanases in foliage and roots.When Bb 1205 was added to the soil,the chlorophyll index and aerial part length showed significant differences.In addition,it was determined that root length,fresh weight of foliage,flower,and fruit count increased 82 days after inoculation(dai).Chitinase activity induced by Bb 1205 in leaves and roots of tomato plants infected with Fol 17108 was observed when injected into the stem at 32 dai(41.8 and 11.6-fold,respectively).Inoculation on the foliage showed a 10-fold increase ofβ-1,3-glucanases in the roots after 82 dpi.As for leaves,a 3.8-fold increase was found when the stem was inoculated.In the different in vivo applications,Bb 1205 activated its defenses by expressing the chitinase enzymes andβ-1,3-glucanase,thus reducing the damage caused by Fol 17108,demonstrating increase plant growth thereafter.

Estimating Wheat Grain Protein Content Using Multi-Temporal Remote Sensing Data Based on Partial Least Squares Regression

Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperature, and precipitation will affect grain protein contents and these factors usually cannot be monitored accurately by remote sensing data from single image. In this research, the relationships between wheat protein content at maturity and wheat agronomic parameters at different growing stages were analyzed and multi-temporal images of Landsat TM were used to estimate grain protein content by partial least squares regression. Experiment data were acquired in the suburb of Beijing during a 2-yr experiment in the period from 2003 to 2004. Determination coefficient, average deviation of self-modeling, and deviation of cross- validation were employed to assess the estimation accuracy of wheat grain protein content. Their values were 0.88, 1.30%, 3.81% and 0.72, 5.22%, 12.36% for 2003 and 2004, respectively. The research laid an agronomic foundation for GPC （grain protein content） estimation by multi-temporal remote sensing. The results showed that it is feasible to estimate GPC of wheat from multi-temporal remote sensing data in large area.

Influence of the Year and Growing Area on Maize (Zea mays L.) Production in the Central and North-Central Zones of Côte d’Ivoire (Departments of Bouake and Katiola)

Several studies conducted in recent years in C&#244;te d’Ivoire reveal that agriculture is increasingly affected by the adverse effects of climate variability. The present study aims at evaluating the effect of the zone and the year of cultivation on the productivity of maize in the Central and North-Central zones of Cote d’Ivoire. It was carried out for two years (2020 and 2021). The experimental design used was a completely randomized block design with three replications. Observations were made on 12 agronomic parameters (plant size, internode size, collar diameter, number of leaves, number of internodes, cob insertion level, cob length, cob diameter, total kernels, cob dry weight, kernel dry weight, yield). The results showed that all agronomic traits of maize were significantly influenced by locality, except for the number of leaves. The highest values of the traits were observed in the locality of Bouaké. However, the year of cultivation did not influence the agronomic parameters of maize. This study will help to avoid yield decreases due to rainfall disturbances as a consequence of climate change.

Key variable for simulating critical nitrogen dilution curve of wheat:Leaf area ratio-driven approach

Nitrogen(N)dilution curves,a pivotal tool for N nutrition diagnosis,have been developed using different winter wheat(Triticum aestivum L.)tissues.However,few studies have attempted to establish critical nitrogen(N_(c))dilution curves based on the leaf area ratio(LAR)to improve the monitoring accuracy of N status.In this study,three field experiments using eight N treatments and four wheat varieties were conducted in Jiangsu Province of China from 2013 to 2016.The empirical relationship of LAR with shoot biomass(expressed as dry matter)was developed under different N conditions.The results showed that LAR was a reliable index,which reduced the effects of wheat varieties and years compared with the traditional indicators.The N nutrition index(NNI)based on the LAR approach(NNI-LAR)produced equivalent results to that based on shoot biomass.Moreover,the NNI-LAR better predicted accumulated N deficit and best estimated the relative yield compared with the other two indicator-based NNI models.Therefore,the LAR-based approach improved the prediction accuracy of N_(c),accumulated N deficit,and relative yield,and it would be an optimal choice to conveniently diagnose the N status of winter wheat under field conditions.