Sorghum Agronomic Performance and Soil Chemical and Microbiological Properties as In uenced by Burkina Faso Phosphate Rock-Enriched Composts

Adama Sagnon Japan International Research Center for Agricultural Sciences Shinya Iwasaki Japan International Research Center for Agricultural Sciences Ezechiel Bionimian Tibiri Japan International Research Center for Agricultural Sciences Nongma Armel Zongo Japan International Research Center for Agricultural Sciences Emmanuel Compaore Japan International Research Center for Agricultural Sciences Isidore Juste O. Bonkoungou Japan International Research Center for Agricultural Sciences Satoshi Nakamura Japan International Research Center for Agricultural Sciences Mamadou Traore Japan International Research Center for Agricultural Sciences Nicolas Barro Japan International Research Center for Agricultural Sciences Fidele Tiendrebeogo Japan International Research Center for Agricultural Sciences Papa Saliou Sarr (  saliou@affrc.go.jp ) Japan International Research Center for Agricultural Sciences https://orcid.org/0000-0002-4478-4463


Introduction
Sub-Saharan Africa is experiencing strong demographic growth, and its population is expected to increase from 1.026 billion in 2017 to 3.078 billion in 2100 (Vollset et al. 2020). This signi cant population growth undoubtedly requires increasing agricultural production to achieve food security. However, there are several factors constraining sustainable crop production in the region, including the scarcity of soils in major nutrients, especially phosphorus (Lompo et al. 2018). Although use of chemical fertilizers is widely accepted to be necessary to improve soil nutritional quality and agricultural yields, the low level of nancial income of the farming population in sub-Saharan Africa is a hindrance to their use (Gemenet et al. 2016). In addition, the excessive use of inorganic fertilizers in some parts of the world is more and more questioned in recent years, due to the negative effect on soil biological properties, severe environmental disturbances and lower agricultural yields in the long run ( Therefore, the use of environment-friendly fertilizers that can restore the agronomic properties of croplands without constraining sustainable agriculture is a necessity. In this perspective, the easy-to-access resources such as agricultural residues, livestock by-products, and locally sourced phosphate rocks have been long studied as alternative solutions to improve soil properties and enhance plant growth and productivity (Ouédraogo et al. 2001). They improve the soil nutrient budget while shaping soil microbial populations (Shang et al. 2020). Salem et al. (2012) pointed out the effect of composts in improving the biological and physicochemical soil properties and their protective status of plants from pathogens. However, most often, the amount of nutrients available in composts are insu cient to cover the nutritional needs of plants. Phosphate rock (PR), an essential material existing in large deposits in several African countries, including Burkina Faso, is included in soil fertilization strategies via a direct application or is added to composts during the composting process to improve the compost phosphorus content. Nakamura et al. (2013) found that sub-Saharan African PRs effectively achieve high performance in lowland rice, following direct application, regardless of the PR reactivity and the location investigated. However, under water-limited conditions such as upland cultivation of rice or other crops, the effects of the initial PR direct application may be depressed, although it may enhance the total P of soil and have a residual effect in subsequent cultivations (Nakamura et al. 2016;Nakamura et al. 2020). Since smallholder farmers are interested in producing high yields in rst year of cultivation and are not interested in waiting several years to bene t from the residual effects of direct PR application, it is essential to improve the agronomic effectiveness of PR using different technologies. Among these, Biswas and Narayanasamy (2006) suggested using PR as a phosphate source supplement to obtain a compost rich in plant-available phosphorus. Sarr et al. (2020) showed that co-composting sorghum straw residues with Burkina rock phosphate and rhizosphere soil (a source of bene cial microorganisms) signi cantly increases the available phosphate pool. These authors elucidated the mechanisms of PR solubilization during composting and identi ed phosphatesolubilizing fungi and microbes harboring the alkaline phosphatase gene as the leading players. Phosphate-solubilizing microorganisms are essential actors in the phosphate availability from organic and inorganic compounds in the soil (Souchie et al. 2006; Anand et al. 2016). They include bacteria, actinomycetes, fungi, and some algae (Ingle and Padole 2017), which use various mechanisms to make phosphate available to plants. Acidi cation of the medium through organic acid release and the production of acid phosphatases respectively to solubilize inorganic phosphates and mineralize organic phosphates was described as the primary process used by soil microorganisms (Anand et al. 2016).
In the present study, we evaluated the agronomic performance of composts produced without and with the supplement of Burkina Faso Phosphate rock (BPR) and BPR plus sorghum rhizosphere soil compared with the direct application of PR and other organo-mineral materials such as sorghum straw and chemical fertilizers. Their effect on sorghum yields and soil biological and physicochemical properties were investigated. The study of soil biological properties included quantifying at different cultivation periods, the abundance of the bacterial phosphate-solubilizing glucose dehydrogenase (gcd) gene (Suleman et al. 2018), and pyrroloquinoline quinone (pqq) gene that encodes the cofactor pyrroloquinoline quinone (Sarr et al. 2020). In addition to these microbial genes, arbuscular mycorrhizal fungi (AMF), alkaline phosphatase (phoD), phosphonatase (phnX) and acid phosphatase (aphA) genes responsible for the mineralization of organic phosphate (Liu et al. 2018) were quanti ed.

Study site
The experiment was carried out at the Center of Agricultural Research and Training of Saria (12°16 'N, 2°09'W, 300 m altitude) located in the center-west region of Burkina Faso in West Africa. In Burkina Faso, Bationo and Mukwunye (1991) reported on nutrient depletion (especially nitrogen and phosphorous) and water and wind erosion, as the main factors in soil degradation and limitation of crop production. The experiment was conducted from July to November 2019, while the rainy season spread from the wettest months July, August, and September. The rainfall for the 2019-2020 cropping season was 911.9 mm of water in 70 rain days (CREAF/Saria meteorological data, 2019). The soil type in Saria is a Lixisol (WRB 2006) characterized by a low soil fertility, low water holding capacity, and a soil surface crust causing low water in ltration (Zougmoré 2003). Detailed soil information is available in Ikazaki et al. (2018).

Experimental design and sorghum cultivation
The experimental design consisted of a completely randomized Fisher block with seven treatments and ve replicates. The seven treatments consisted of the three types of compost (Compost, P-Compost, and P-Compost-Soil) implemented by Sarr et al. (2020), a negative control with N (60 kg N ha -1 ) and K (30 kg K 2 O ha -1 ) application but without P (NK or CT), sorghum straw (SS), Burkina phosphate Rock (BPR), and NPK as an absolute positive control. In brief, sorghum straw residues were supplemented with BPR during composting to make the P-compost (P-Comp). Pcompost-soil (P-Comp-Soil) was made by adding BPR and sorghum rhizosphere soil to the sorghum straw residues during the fabrication process. Sarr et al. (2020) reported that the P-Comp-Soil contained 13% higher labile-P than the P-Comp. In the present study, the application rate of the organic materials (SS, Comp, P-Comp, P-Comp-Soil) was 1.34 t ha -1 . The NPK treatment corresponded to 60, 90, and 30 kg ha -1 of nitrogen, phosphorus, and potassium, provided by urea, Triple Super Phosphate (TSP), and KCl, respectively. We designed the eld trial to supply the same amount of total P, total N, and K in all the treatments, except the negative control without P application. When the amount of N, P, or K provided by the organic material was inferior to rates in the NPK treatment, we added urea or BPR or KCl to adjust to the exact proportions of the NPK treatment. The only difference between the BPR and NPK treatments was the source of P, which was BPR and TSP, respectively. The singularity of this experiment was that the different treatments, except the negative control, supplied the same amount of total P, but the amount of available phosphorus differed from treatment to treatment. In this situation, any difference in yield would undoubtedly be attributed to the difference in available phosphorus in treatments. The rate of available P was higher in the chemical fertilizer NPK and P-Comp-Soil than in the other treatments in which total P was adjusted using BPR that contains 12.05% phosphorus corresponding to 36.87% PO 4 (Nakamura et al.

2015).
After plowing, treatments were spread on their corresponding plots (4 m x 6 m), which were 1.5 m apart inside blocks and in-between blocks, and sorghum (Kapelga variety) was sown at 80 cm x 40 cm spacing on 16 July 2019, followed by a reseeding of non-germinated hills on 26 July 2019. Seedlings were thinned to two individual plants per hill, the weeds regularly removed, and insect attacks were monitored and controlled during the cultivation period.

Soil sampling and harvest of sorghum plants
We collected rhizosphere soil samples for chemical and microbiological analysis on the 52 nd , 93 rd , and the 115 th day after sowing. Three sorghum plants randomly selected from the plot edges were destructively pulled out and carefully shaken to remove the loose soil not tightly attached to the roots. The soil well adhering to the roots (rhizosphere soil) was carefully recovered on paper by hand while wearing sterile gloves, which were changed when moving between plots. A soil aliquot per sample was directly put in 50 ml falcon tubes and stored in an icebox until transportation to the laboratory, where it is kept at -20°C until DNA extraction and molecular analysis. The remaining soil part was air-dried and later used for physicochemical analysis. Sorghum was harvested on the 115 th day after sowing in a yield area containing 21 plant hills. The sorghum biomass was air-dried for two weeks under the sun, and a sub-sample was oven-dried at 75°C for 48 h to calculate the moisture content and determine the dry biomass production per plot. At harvest, the weight of the air-dried grains per plot was recorded after dehulling the ears. A sub-sample of grains was oven-dried in the same way as the sorghum biomass to obtain the oven-dry grain production per plot. Finally, all dry yields were converted to t ha -1 . The number of total ears per yield area and that of ears with no grain were also counted at harvest Chemical analysis of soil samples The dried rhizosphere soil samples were sieved with a 2-mm mesh and used for physicochemical analysis at the Soil-Plant Laboratory of the Japan International Research Center for Agricultural Sciences (JIRCAS), Tsukuba, Japan. The pH was measured at a 1:2 soil-to-distilled water slurry by a compact pH meter LAQUAtwin-pH-22 (Horiba Scienti c, Japan). The dry combustion method was used to determine total carbon and total nitrogen using an NC analyzer (Sumigraph NC-220; Sumika Chemical Analysis Service, Ltd., Japan). Exchangeable cations were extracted with a 1 M ammonium acetate solution. Cation concentrations were determined by the Inductively Coupled Plasma Optical-Emission Spectroscopy (ICP-OES) using the ICPE-9000 (Shimadzu Inc. Tokyo, Japan). Soil available phosphorus was extracted using a Bray-2 extracting solution (Bray and Kurtz 1945), and the concentration of P in the ltrate were determined using the colorimetric method described by Murphy and Riley (1962) with a UV-1800 spectrophotometer (Shimadzu, Japan).

Extraction of soil DNA
Soil previously kept at -20°C was left at room temperature for approximately one hour to melt the attached ice. Following that, 0.25 g of soil sample was used for total DNA extraction using the DNeasy PowerSoil Pro Kit (QIAGEN, Germany) according to the manufacturer's instructions with a slight modi cation. In step ve (5), we used an automatic homogeniser (TissueLyser II, QIAGEN, Germany) instead of a rotary shaker. DNA concentration was assessed using Qubit HS before and used for further molecular analysis. After placing about 0.5 g of soil in a hot plate at 100°C for three (3) hours, the soil moisture percentage was determined by the formula: Determination of the abundance of soil bacteria, fungi, arbuscular mycorrhizal fungi, and several microbial genes involved in P solubilization or mineralization by qPCR The extracted sorghum rhizosphere soil DNA was used to quantify the abundance of total bacteria (16S rRNA), fungi (ITS), arbuscular mycorrhizal fungi (AMF), and several genes related to phosphate solubilization, following qPCR methods, plasmid standards, and primers described by Sarr et al. (2020). P-solubilizing genes included glucose dehydrogenase (gcd) (Chen et al., 2015) and the pyrroloquinoline quinone (pqqE) (Choi et al. 2008), acting as a cofactor of gcd to synthesize organic acids responsible for the solubilization of inorganic phosphate. The other microbial genes are those involved in the mineralization of organic phosphates, such as acid phosphatase (aphA), alkaline phosphatase (phoD), phosphonatase (phnX), enterobactin-mediating siderophore (entA), and phosphate speci c transporter (pstS) (Bergkemper et al. 2016). However, in this study, AMF was ampli ed using AML1 (5'-ATCAACTTTCGATGGTAGGATAGA-3') and AML2 (5'-GAACCCAAACACTTTGGTTTCC-

Statistical analysis
The soil chemical and microbiological data obtained from three sampling periods (52 nd , 93 rd , and the 115 th day after sowing) were subjected to a two-way analysis of variance (ANOVA) to evaluate the impact of treatments and sample collection periods on these parameters. These statistical analyses were all performed using CropStat ver. 7.2 software (IRRI, Philippines). When no signi cant interaction was found between treatments and sampling days, the average value of the given treatment at the three sampling dates was considered (n = 9). In case of a signi cant interaction between the treatment and the sampling day (p < 0.05), the data obtained from each sampling day were analyzed separately following one-way ANOVA. A signi cant interaction indicates that the treatment would behave differently for a given variable from one sampling period to another. When a signi cant effect is observed, the differences between treatments were tested using Fisher's LSD (Least Signi cant Difference). When the number of treatments was superior or equal to six, we compared the means using the DMRT (Duncan Multiple Range Test).
Principal Component Analysis (PCA) was performed using the "stats" package of R version 4.0.0 (R Core Team, 2020) to study the general relationships between sorghum yield components and soil chemical and microbiological parameters of the three sampling periods. Before running PCA, the data of the ve replicates of each variable were averaged, and the resulting data set was standardized. Calculated principal components were visualized in the PC1/PC2, and PC1/PC3 (components with the highest scores) planes using the R packages ggplot2 (Wickham 2016) and ggbiplot (Vu 2011). In addition, Spearman's rank correlations (rs) relating yield components and soil properties were obtained using PAST v.2.17 (Hammer et al. 2001). Yield components included sorghum dry grain yields (DGY), dry biomass yields (DBY). Soil chemical characteristics included total carbon (TC), total nitrogen (TN) soil acidity (pH), C/N, available Bray2-P, the sum of exchangeable cations (Mg, Ca, Na, K); soil microbiological properties included bacteria (16S rRNA), fungi (ITS), and several other microbial genes (gcd, aphA, phoD, entA, pstS, AMF, phnX, and pqqE).

Results
Sorghum yields Table 1 shows the total dry biomass and grain yields of sorghum. Total biomass and grain yields obtained in the NPK and P-Comp-Soil treatments were not signi cantly different. They gave signi cantly higher yields than the other treatments, except that there was no signi cant difference between P-Comp-soil and the Control for biomass yields and between P-Comp-Soil, P-Comp, and Control for grain yields. In general, Sorghum Straw, Comp, P-Comp, and BPR treatments in uenced less the sorghum yields. The percentage of good ears (ears well-lled with grains) were signi cantly higher in the NPK, P-Comp-Soil, P-Comp, and Comp treatments, with slightly higher values in NPK and P-Comp-Soil. The NPK treatment gave 4.43 t ha -1 of total dry biomass, 0.86 t ha -1 of dry grain, while 72.51% of ears were lled with grains. For the P-Comp-Soil treatment, these values were 3.87 t ha -1 , 0.82 t ha -1 , and 72.23%, respectively.

Chemical properties of the rhizosphere soil
The two-way ANOVA applied to the sampling days and treatments showed no signi cant interaction between these two variables for soil TN, TC, and the sum of exchangeable cations (data not shown). Therefore, the mean values of these three parameters across the three sampling days were considered and are shown in Table 2. Signi cant differences among treatments were observed in TN and the sum of exchangeable cations. Compared to the Control, Sorghum Straw, and BPR treatments, the soil contained a signi cantly higher total nitrogen when fertilized with the P-Comp-Soil, P-Comp, and Comp treatments. However, the nitrogen content in the soil amended with Comp and P-Comp was similar to the NPK treatment. Also, the soil fertilized with P-Comp-Soil contained signi cantly higher exchangeable cations (1.08 cmolc kg -1 dry soil), while the Control and BPR treatments led to the lowest contents with 0.88 soil and 0.87 cmolc kg -1 dry soil, respectively. Table 2 also shows that TN and TC were signi cantly higher at the early sorghum growth stage (52 nd day) and decreased with the cultivation's progress.
A signi cant interaction existed between the sampling days and the treatments for the pH, C/N, and available P (data not shown). Thus, these parameters were analyzed separately for each sampling day following one-way ANOVA (Table 3). For the pH, signi cant differences were found between treatments at the 52 nd and 93 rd days and not at harvest (115 th day). Although the soil was, in general, slightly acidic, the acidity was signi cantly less under P-Comp-Soil, P-Comp, Comp, and Sorghum Straw treatments compared to Control and NPK on the 52 nd day. At this period, the pH of the BPR treatment (pH = 5.43) was signi cantly lower than that of P-Comp-Soil (pH = 5.60) but was the same as that of P-Comp, Comp, and Sorghum Straw. In contrast, the soil amended with the BPR treatment was signi cantly less acidic (pH = 5.90) than the remaining six treatments on the 93 rd day. At this second soil sampling day, the pH of the soil fertilized with NPK was signi cantly lower than that of Sorghum Straw and BPR treatments. The difference among treatments for the C/N ratio was only signi cant on the 93 rd day, where C/N (9.52) was signi cantly higher in the Sorghum Straw treatment than all remaining six treatments.
The soil available P (Bray2-P) content followed contrasting patterns on the three sampling periods (Table 3). On the 52 nd day, it was signi cantly higher in NPK (32.81 mg kg -1 dry soil) and Sorghum Straw (28.49 mg kg -1 dry soil) than the other treatments. However, it was not signi cantly different between the Sorghum Straw and the BPR (26.98 mg kg -1 dry soil) treatment. The Control and the P-Comp treatments recovered fewer amounts of available P at this period with 9.39 and 12.06 mg kg -1 dry soil, respectively. In contrast, the pattern changed on the 93 rd day when Comp, Sorghum Straw, and BPR-treated soil contained signi cantly higher P with 34.20, 31.89, and 30.32 mg kg -1 dry soil. Sorghum Straw and BPR-treated soil showed similar levels of available P to the NPK treatment with 26.27 mg kg -1 dry soil, while the Control still contained signi cantly less available P. On the 115 th day, the soils treated with Sorghum Straw, Comp, and BPR showed signi cantly higher P levels corresponding to 35.50, 34.03, and 30.23 mg kg -1 dry soil, almost like the 93 rd day. There was no signi cant difference in available P between BPR and NPK and NPK, P-Comp-Soil, and P-Comp. We observed an increasing trend in soil P throughout the cultivation period in the Sorghum Straw, Comp, P-Comp, BPR, and a decrease in NPK and P-Comp-Soil treatments, although we did not perform statistical analysis.
Abundance of microbial genes in the rhizosphere soil The two-way ANOVA showed signi cant interactions (data not shown) between sampling days and treatments for the abundance of the soil microbial genes gcd, AMF, and pstS. Therefore, we described these genes on each sampling day following one-way ANOVA, and the results are reported in Table 4. A signi cant difference among treatments for the gcd gene was observed only on the 52 nd day. At this period, the soil amended with P-Comp-Soil contained a signi cantly higher abundance of the gcd gene than the other treatments. The soil of the remaining treatments hosted a similar abundance of gcd except that NPK had a signi cantly lower abundance of the gene than the control.
On the 52 nd day, the soil that received P-Comp contained higher copy numbers of AMF than the group formed by the Control, Sorghum Straw, BPR, and NPK treatments, which showed the least AMF abundance. However, there was no signi cant difference in soil AMF among P-Comp, P-Comp-Soil, and Comp. In contrast, Sorghum Straw-amended soil recovered signi cantly higher copy numbers of AMF on the 115 th day (harvest) than all other treatments. It was followed by Comp and P-Comp, while AMF was signi cantly less abundant under the Control, P-Comp-Soil, BPR, and NPK treatments. We also noticed an increase (about 3-fold) in AMF abundance in the soil at harvest compared to the 52 nd day.
The pstS gene was also signi cantly different among treatments on the 52 nd and 115 th days, similarly to AMF. It was signi cantly higher in soils treated with P-Comp-Soil and BPR on the 52 nd day than the other ve treatments that did not show differences. At harvest, the soil amendment with P-Comp led to a signi cantly higher abundance of the pstS gene than the remaining six treatments that showed no signi cant difference.
The two-way ANOVA was not signi cant between sampling days and treatments for phnX, phoD, ITS, 16S rRNA, entA, pqqE, and aphA genes (data not shown). Thus, the mean values of the three sampling periods were considered for each treatment ( Table 5). The treatments showed a signi cant (p < 0.05) effect for the abundance of phnX, ITS, 16S rRNA, and aphA genes in soil. It was highly signi cant (p < 0.01) for the pqqE gene. The three compost treatments (Comp. P-Comp, P-Comp-Soil) promoted the proliferation of microorganisms harboring the phosphonatase phnX gene more signi cantly than the other treatments. The abundance of phnX gene was signi cantly lower in the NPK treatment. Soil fungi (ITS) were signi cantly more abundant in the NPK treatment (4.85 10 7 copies g -1 dry soil) than in the other treatments. This treatment was followed by the P-Comp-Soil/Comp/BPR group. The Control soil contained the lowest abundance of fungi (3.37 10 7 copies g -1 dry soil), which was not signi cantly different from the Sorghum Straw treatment. In addition, the P-Comp-Soil treatment led to a signi cantly higher population of soil bacteria (5.17 10 8 copies of 16S rRNA g -1 dry soil) than the Control, BPR, and the NPK treatments. However, it did not show signi cant differences with the Sorghum Straw, Comp, and P-Comp treatments. The soil of these three treatments contained similar numbers of total bacteria to the Control and the NPK treatments. Pyrroloquinoline quinone gene (pqqE), a co-factor of the gcd gene involved in phosphate solubilization, was signi cantly more abundant in soils treated with Comp, P-Comp-Soil, and NPK. The BPR treatment generated the lowest population of soil microbes with the pqqE gene. Compared to the remaining six treatments, the P-Comp-Soil treatment signi cantly enhanced the copy numbers of the acid phosphatase gene (aphA) (4.98 10 5 copies g -1 dry soil). It was followed by the P-Comp treatment with 2.91 10 5 copies g -1 dry soil. Table 5 showed a highly signi cant effect (p < 0.01) of the sampling period for the abundances of phnX, phoD, and entA, and a signi cant effect (p < 0.05) for that of the pqqE gene in soil. The overall soil's phosphonatase phnX gene increased with the cultivation progress to be signi cantly higher at harvest (5.18 10 5 copies g -1 of dry soil). A similar trend was observed for the siderophore enterobactin gene (entA), although the overall abundance on the third sampling period (115 th day) was not signi cantly different from that on the rst sampling period (52 nd day). In contrast, the alkaline phosphatase gene (phoD) and the pqqE genes were signi cantly more abundant in soil on the 52 nd day than on the 93 rd and 115 th days. They decreased in number with the progress of the cultivation.
Multivariate analysis: interactions of soil chemical and microbiological properties with sorghum yields Principal Component Analysis (PCA) was performed to understand the relationships between soil chemical and microbiological properties obtained during the three sampling periods and sorghum yields (dry biomass and dry grains) using the correlation matrix of Pearson. The factors loadings of different variables on PC1, PC2, PC3, PC4, PC5, and Eigenvalues (standard deviation, proportion variation, cumulative variation) were shown in Table S1. These rst ve components explained 81% of the observed variation. However, PC1, PC2, and PC3, which accounted for 65.8% of the variation, were discussed. The cumulative variation of PC1 (29.5%) and PC2 (22.7%) was 52.2% (Fig. 1a). PC1 and PC2 separated the variables into two groups. On the negative side of PC1, sorghum yields positively strongly correlated with total carbon (TC), acid phosphatase (aphA), alkaline phosphatase (phoD), total nitrogen (TN); and moderately with inorganic phosphorus-solubilizing microbes harboring the gcd and pqqE genes, phosphate speci c transporter pstS, exchangeable cations. These variables were strongly in uenced by the rst sampling period (52 nd day), and more by the P-Comp-Soil treatment during this period. The remaining variables clustered on the positive side of PC1 were highly in uenced by the third sampling period (115 th day). Bray-2 P strongly positively correlated with total fungi and moderately with soil pH, arbuscular mycorrhizal fungi (AMF), phosphonatase (phnX). The P-Comp-Soil treatment strongly in uenced the population soil AMF and phnX at harvest. When PC1 and PC2 are plotted, the second sampling (93 rd day) does not in uence the distribution of variables. The highest factor loading in PC1 was obtained for the variable pH (0.343). It was followed by AMF (0.283), phnX ( PC3 accounted for 13.6% of the variation, and when plotted with PC1 (29.5%), both components explained 43.1% of the observed variration (Fig.  1b). On the PC1/PC3 plan, the three sampling periods were separated. The second sampling, which was not expressive on PC1/PC2, strongly in uenced the dry biomass yield, dry grain yield, exchangeable cations, Bray-2 P, entA, and C/N, showing strong positive relationship of yield variables with exchangeable cations, with a strong positive in uence of the P-Comp-Soil and NPK treatments, and moderate of P-Comp. Bray-2 P, C/N, and entA negatively correlated with yield variables and were positively correlated among them with the in uence of BPR, sorghum straw, and Comp. The third sampling (115 th day) did not in uence the yield variables. However, total bacteria and fungi were positively related to P-Comp-Soil, while P-Comp, mainly in uenced the phnX, AMF, and the pH. Dry biomass yield and dry grain yield of sorghum showed loading factors of 0.538, 0.533, respectively, on PC3. They were followed by total fungi (0.390) and total bacteria (0.195).
The Spearman's correlation (Table S2) con rmed that sorghum biomass was moderately negatively correlated with entA, AMF, pH, and Bray2_P, and moderately positively correlated with total nitrogen, total carbon, and exchangeable cations. The grain yield was moderately negatively correlated with AMF, pH, and Bray2_P and positively correlated with total bacteria (16S rRNA), total nitrogen, total carbon, and exchangeable cations. Among the other existing interactions, we noticed that the abundance of soil bacteria was moderately positively correlated with AMF, pH, and exchangeable cations but weakly with C/N. The soil fungi moderately negatively correlated with pqqE and weakly negatively correlated with nitrogen and carbon. It correlated moderately positively with AMF, weakly with pH, and strongly with bacteria. The phosphonatase phnX gene strongly positively correlated with AMF and pH, moderately positively with total fungi and total bacteria, but moderately negatively correlated with phoD, and pqqE.

Discussion
This study evaluated sorghum production under different organo-mineral amendments and assessed their in uence on soil chemical and microbiological properties. Except for the control, all treatments were designed to contain the same amount of total P. Triple Super Phosphate supplied the required amount of P in the NPK treatment, while the applied rate of P-Comp-Soil (1.34 t ha −1 ) was enough to provide the necessary 90 kg P ha −1 . The content of total P was the same in all treatments (except the control), but the available P differed. Also, treatments had the same total concentrations of nitrogen and potassium.
The P-Comp-Soil treatment gave sorghum yields comparable to the chemical treatment NPK and signi cantly higher than the other treatments. P-Comp-Soil contained an initial higher amount of available P, justifying why BPR was not added to leverage to the required amount of 90 kg P ha −1 . Possibly, the ambient available P level in this treatment and the supply of a loop of P-solubilizing microbes, and exchangeable cations may have created an environment favorable for enhanced uptake of nutrients by sorghum, leading to better plant growth. Interestingly, P-Comp-Soil gave a signi cantly higher number of good ears ( lled with grains) compared with the NPK treatment. A similar result was reported by Asai et al. The Burkina phosphate rock used in this study contains about 34.39% CaO and 0.18% MgO (Nakamura et al. 2015). Therefore, the increased exchangeable cations in soils amended with P-Comp-Soil, particularly calcium and magnesium (data not shown), could be derived from the enhanced microbial-mediated phosphate solubilization during composting, concomitantly releasing more cations in the compost product and in soil. Sarr et al. (2020)  gcd with the support of the co-factor pqqE gene and the secretion of organic acids (not determined) to further enhance the soil phosphate solubilization. These early biogeochemical nutrient transformations are essential to provide the crop with nutrients for its establishment, which signi cantly in uences the yields at harvest. Fig. 1 con rmed that soil properties strongly in uence sorghum yields in the early growth stage. Wan et al. (2020) mainly associated the solubilization of Ca 3 (PO 4 ) 2 , FePO 4 , and AlPO 4 in soil by Acinetobacter pittii to the expression of the gcd gene, which releases organic acids, predominantly gluconic acid (Xiao et al. 2009;Zeng et al. 2016). In addition, P-Comp-Soil-treated soils showed a signi cantly higher abundance of the phosphate-speci c transporter (pstS) and acid phosphatase (aphA) genes, as well as a signi cant abundance of total bacteria and fungi. Acid phosphatases (aphA in this study), together with phosphonatases (phnX), alkaline phosphatases (phoD), and phytases (appA), encode organic phosphate mineralization enzymes (Liu et al. 2018;Tanuwidjaja et al. 2020). The organic phosphate forms are represented mainly by phytate (Sing and Satyanarayana 2011). Besides this dominant organic phosphorus form, secondary forms including phosphate monoesters, phosphate diesters, phosphate triesters, phospholipids, and nucleic acids also constitute organic phosphate stores (Rodrıǵuez and Fraga 1999). The mineralization of these organic materials releases plant-available nutrients (Jacoby et al. 2017). Conversely, organic fertilizers boost soil microbial activity by providing an energy source to microorganisms and enhance plant growth by providing a broad array of nutrients (Mokgolo et al. 2019;Wu et al. 2020). Interestingly, the available P level was lower in the P-Comp-Soil-treated soil at harvest, similarly to NPK and P-Comp. Such a result could be explained by a better P uptake in these treatments during cultivation. As reported above and con rmed by the PCA (Fig. 1), the P-Comp-Soil, which contained a higher abundance of several microbial genes, also led to the best sorghum growth. Sahib et al. (2020) also found a similar result that the richness of rhizobacterial species improves sorghum growth and nutrient synergism in nutrient-poor soil and that soil nutrient contents were generally lower at higher plant-associated rhizobacterial diversity. The signi cant increase of the microbial phosphate speci ctransporter (pstS) in the P-Comp-Soil-treated soil since the early growth stage (52nd day) (Fig. 1a) and in the P-Comp at harvest (115th day) supports a good P uptake and transport of available phosphorus in these treatments (Table 3). Rao and Torriani (1990) indicated that the phosphate import system in bacteria is activated when the external phosphate concentration is equal to or above 20 µM. Part of the phosphorus immobilized in microbial cells can be solubilized and reused by the living organism. . The present work found a higher abundance of AMF population in the rhizosphere soil of sorghum plants fertilized with P-Comp-Soil and P-Comp compared with the control, sorghum straw, Comp, BPR, and NPK treatments, especially during the early growth stage ( rst sampling). These AMF may be a mixture of AMF spores and germinated AMF mycelia and hyphae in connexion with the sorghum roots, creating a mycorrhizal network. Although we did not determine AMF spores' density, they are known to decrease during root growth and increase during root inactivity and senescence (Songachan et al. 2011). An intense mycorrhizal network during plant growth enhances the transfer of water and nutrients from the soil to the plant (Smith and Smith 2011). Therefore, the higher sorghum grain yield (0.82 t ha −1 ) and biomass (3.87 t ha −1 ) of the P-Comp-Soil treatment, comparable to that of the fertilizer NPK (Table 1), likely resulted in parts from an improved nutrient availability (phosphate, nitrogen, cations etc.) and uptake, facilitated by the activity of soil microorganisms (AMF and Psolubilizing microbes). However, the strong positive in uence on AMF in the third sampling period (harvest) when the soil was collected in almost dry condition (Fig. 1a, 1b) indicates that AMF at this period already was in spore condition and may no more be active in nutrient uptake and transfer to sorghum plant.
The decrease in available P along the cultivation period in P-Comp-Soil and NPK soils, which gave the higher sorghum yields, partly explain the negative relationships between yields and available P (Bray-2 P) as shown by the PCA result (Fig. 1a, 1b). The strong relationship between Bray-2 P and the BPR, Sorghum Straw, and Comp treatments, especially during the second and third samplings (Fig. 1), showed that available P was still high at harvest in the soil amended with these treatments. In the Sorghum Straw, Comp, and BPR treatments, we added more Burkina Faso Phosphate Rock (BPR) during treatment application to reach the desired rate of 90 kg P ha −1 as in the chemical fertilizer (NPK) treatment. Although BPR has low agronomic effectiveness due to its weak solubility Fukuda et al. 2021), the soil treated with Sorghum Straw, Comp, and BPR contained a high amount of Bray2-P at harvest ( Table 3). The applied phosphate rock in these three treatments may have been gradually solubilized but absorbed poorly by sorghum roots, probably due to environmental factors such as soil concretion and limited soil moisture, justifying the lower yields obtained in these treatments compared to P-Comp-Soil and NPK. The sub-Saharan African PRs effectively achieved high performance in lowland rice, following direct application (Nakamura et al. 2013). We did not obtain a similar result in the present study on upland sorghum cultivation. It has been revealed a depressive effect of the initial PR direct application under water-limited conditions such as upland cultivation. However, the initial P in soils may be enhanced and PR application and be effective as a residual effect during subsequent cultivations (Nakamura et al. 2016), which may be the case in our sorghum straw, Comp, and BPR treatments. The Control and NPK treatments differed only by the absence of P application in control. In this situation, we observed a drop of biomass yields in control compared to NPK by 34% and a drop of grain yield by 27%, clearly showing the importance of phosphorus nutrition in the studied environment of Burkina Faso and sub-Saharan Africa in general. Also, the sorghum biomass and grain yield in the control dropped by 25% and 23%, respectively, compared with P-Comp-Soil, that contained a signi cantly higher available P level. Enhanced phospho-composting with microbial sources is an alternative to produce low-cost organo-mineral fertilizers that achieve higher sorghum yields during the rst season in upland cultivation systems. However, the strong positive spearman's correlations between sorghum biomass yield, total nitrogen, and total carbon (Table S2) indicated that other than P and exchangeable cations, nitrogen and carbon are other essential nutrients for sorghum growth in the studied environment. Moreover, the negative correlation between yields and pH revealed that a better sorghum production is achieved when the acidic soil pH tends to neutrality.

Conclusion
This study highlighted the importance of soil amendment in sub-Saharan Africa to support crop growth, given the overall low soil fertility in many croplands. In Burkina Faso, where access to chemical fertilizers is limited, we evaluated the combination of several organo-mineral fertilizers on sorghum production. Only P-Comp-Soil gave sorghum yields among the organic treatments like that of the chemical fertilizer NPK. This result is explained by the higher available P concentration in the Burkina Faso phosphate rock-enriched compost made by supplementing rhizosphere soil during the process. P-Comp-Soil also harbors higher abundances of microbial genes involved in the solubilization and phosphate mobilization (gcd, pqqE, phnX, aphA, AMF, pstS), total bacteria, and boosts microbial activities in soil upon application. Other than P, the multivariate analysis showed the essential contribution of nitrogen, carbon, and exchangeable cations in sorghum production, indicating the importance of organic amendment in sub-Saharan African soils. In addition, we understood through this study that the direct application of low-grade phosphate rocks might not be e cient in the upland cultivation systems in Africa, where water is generally limited. Instead, soils may be replenished with organomineral materials such as improved BPR-enriched composts, with the supplement of P-solubilizing microbial sources during the composting process. P-Comp-Soil fertilizers are of low cost and help restore soil chemical and microbiological fertility for better crop production.    Table 4 One-way ANOVA (treatment) of gcd, AMF, pstS genes over the three sample periods Control = without phosphate or compost addition, SS = sorghum straw, Comp = sorghum straw-based compost, P-Comp = sorghum straw-based compost + BPR, P-Comp-soil = compost made from sorghum straw, BPR and sorghum rhizosphere soil, BPR = Burkina phosphate rock, Trait Sign. = Signi cant Trait, parameter values assigned by different letters differ highly signi cantly (**) at p < 0.01 and signi cantly (*) at p < 0.05, ns = signi cant sound. SE = Standard error, Error df = Error degree of freedom, DMRT = Duncan's multiple range test, LSD = Least small difference, gcd = glucose dehydrogenase, AMF = Arbuscular mycorrhizal fungi, pstS = phosphate speci c transporter. Sign. = Signi cant Trait, parameter values assigned by different letters differ highly signi cantly (**) at p < 0.01 and signi cantly (*) at p < 0.05, ns = signi cant sound. SE = Standard error, Error df = Error degree of freedom, DMRT = Duncan's multiple range test, LSD = Least signi cant difference, phnX = phosphonatase, phoD = alkaline phosphatase, ITS = Internal transcribed spacer (total fungi), 16S rRNA (total bacteria), entA = enterobactin-mediated Siderophore, pqqE = pyrroloquinoline quinone, aphA = acid phosphatase.

Supplementary Files
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