CDI RWANDA POST HARVEST REPORT FOR SEASON A 2016

Transcription

1 CDI RWANDA POST HARVEST REPORT FOR SEASON A

2 MAY 2016, KIGALI RWANDA Table of Contents Pages List of ACRONYMS Introduction and project background Post-harvest results findings of Soybeans and Maize for season A Results from Soybeans Demo plots Soybeans crop varieties Germination Rates Performance of different soya seeds varieties Performance of various soybean crop varieties as per spacing techniques Soybean productivity/performance per District Results from Maize Demo plots Maize crop varieties Germination Rates Performance of different maize seeds varieties Performance of various maize crop varieties as per spacing techniques Maize productivity/performance per District Conclusion and Recommendations List of ACRONYMS # AGRA Alliance for Green Revolution in Africa 1 CDI Clinton Development Initiative 2 HA Hectare 3 M Meter 4 MT Metric Tons 5 RAB Rwanda Agriculture Board 2

3 1. Introduction and project background The AGRA funded Clinton Development Initiative programme (Phase II) in the Eastern Province aims at increasing smallholder farmer incomes, productivity, and food and nutritional security focusing on soil fertility. The projects interventions are along the soybean and maize value chain encouraging use improved seed varieties. This projects encourages small holder farmers to use appropriate seeds and follow agronomic practices that will help increase productivity. It is in this line that CDI Rwanda implemented 27 demo plots in season B 2015 where the soybean productivity report was developed and recommendations were to continue two performing soy seeds crop varieties. From this context, 60 demo plots were implemented in 5 districts located in Eastern Province that include Gatsibo, Kayonza, Kirehe, Nyatagatare and Rwamagana. During season A 2016, the 60 demo plots implemented were used to training 18,000 farmers on using smart agriculture techniques to increase soybean and maize productivity. The selected master farmers were trained and facilitated to use different soybean and maize crop varieties. For soybean SB 24 and Sequel were planted while for maize varieties Pan 53 and ZM 607 were used. This post-harvest report for season A 2016 takes into consideration various parameters that include performance of different soybean and maize varieties, and spacing based on recorded data from five districts. The report also do a comparison how 27 master farmers performed in season B 2015 and season A Therefore the report present the results by answering the following questions; Of the two soya crop varieties, which one recorded the highest germination rate? Of the two spacing treatments applied for soybeans, which one was the better? performed 3

4 Which soybean crop variety performed better in terms of yields? Of the two maize crop varieties, which one recorded the highest germination rate? Of the two maize spacing treatments, which one performed better? Which maize crop variety performed better l in terms of yield? 2. Post-harvest results findings of Soybeans and Maize for season A 2016 During season A 2016, 60 demonstration plots for soybeans and maize were implemented by 60 master farmers, represented by 17 women and 43 men. The results are presented into two sections that include soybeans and maize 2.1.Results from Soybeans Demo plots Soybeans crop varieties Germination Rates Germination is key factor to determinate a good crop variety as it gives chances to realize a good yield. In season A 2016, germination rates were recorded for the two soybeans varieties (SB 24 and Sequel) and the results are shown in Figure 1 below: Figure 1: Germinations rates for soybeans crop varieties Germination Rates

5 From the results presented in Figure 1, the overall germination rates for SB24 and Sequel are 87.1% and respectively with the same maximum of 99%. A noticeable differences among these two crop varieties can be seen at minimum level where SB 24 is 65% against 72% of Sequel. Given that the average level difference is not significant, it can be concluded that SB 24 and Sequel have the same germination rates. As per RAB recommendation the accepted minimum germination rate is 80% and most of CDI tested soybean seeds are germination at rates that are greater to 80%. The two farmers that recorded a low level of germinations of 65% and 72% for SB 24 and Sequel respectively; they faced a serious of problem of rain shortage in their sectors given that their lands are located at uphill that did not received enough rainfall on time. According to the discussions that CDI Rwanda had with farmers and field officers; the two farmers ( Rwabagabo Sylidio and Hakuzimana Fidel ) located in Murama and Kabara sectors respectively in Kayonza district; first planted soybean which failed to germinate due to not having rainfall and they planted again for second time which resulted to germination rates that are below 80%. In this report; the analysis went far and did exploration if the germination rate can be influenced by the experience of farmers to grow soybean and clustered record of germination rates by doing comparison between farmers that planted soybean in season B 2015 and new registered farmers in season A The figure Figure 2: Soy Germination rates as per farmers period of entrance in CDI SHF programme 5

6 From the figure 2 above, the post-harvest data shows that the germination rates do not depend on experiences of farmers to grow soybean as the mean, median, maximum and minimum figures are almost the same for both farmers that worked with CDI Rwanda for season B 2015 and new farmers selected in season A It means that the techniques in which farmers were trained by CDI staff can be quickly adapted by farmers. In addition, overall germination rates for both seasons B 2015 and season A 2016 are almost the same at 88.35% and 88.76% respectively. Only a significant differences is at minimum level where the germination rates are at 56% and 65% for season B 2015 and season A The low germination rates in figure 2 above can be again be explained by the lack of enough rainfall on time; as these records come from Fidel and Silidio located Kabara and Murama sectors in Kayonza districts where these two sectors had a rain fall problem in season B Performance of different soya seeds varieties The main purpose of implementing demo plots for Season A 2016 was to examine the performance of different soya seed varieties in term of productivity. Two varieties were planted due because they had performed better in the previous season B 2015 (with average yields of 2.34 and 2.09 MT/Ha for SB24 and Sequel respectively. Figure 2 below gives the detailed results. Figure 3: Soybean crop varieties Productivity per MT/HA Productivity per MT/HA Minimum Maximum Median Mean SEQUEL SB 24 6

7 From Figure 2 above, the average yields for SB 24 and Sequel are 2.5 and 2.6 MT/HA respectively. By comparing results from season B 2015 and season A 2016, SB 24 increased by 0.16 MT/HA and Sequel, 0.51 MT/HA. From the statics analysis done by using Person correlation between germination rate and productivity, the results confirms a strong significant correlation of 0.01 level. Therefore, CDI Rwanda should use and promote soybeans crops with high germination rates inline of getting high soy yields. CDI RWANDA TERAM did a further discussions with better and poor performing farmers to documents what enabled to the best performing and challenges faced by farmers who did not record a high productivity. The key learning is that the top performing farmers are either cultivating in swaump land or had good rain fall in the last seasons as it is indicated in the following quotes from discussions conducted with farmers: Hategekimana Anaclet with productivity of 3.1 MT/HA productivity said that; the soybean was grown on time and the area had a very good rainfall throughout cropping cycle and my land is very productive as we started using it in 1998 as the area used to be used only for cow farming I also recommended techniques as per CDI straining and all these helped me to get high yield Bavuriki Hassan with productivity of 3 MT/HA reported that ; My land is located in marush land and the farmers received enough rainfall and we did regular monitoring of our crops, weeding on time, applying manure and mineral fertilizers and irrigated our land during a short period where there was no enough rain fall Nzitabakuze Sylvestre with productivity 3.02 MT/HA said that the key enablers for soybean performance in my land are; I planted very well and the germination rate was very high. My land is located marush land with availability of water for irrigation, I did irrigation during the time of lack of rainfall; did a closer follow up and did weeding on time and used good seeds 7

8 From the above farmers quotes, the better performing farmers reported that they lands received enough rain fall and those with land located in much land did irrigation to complement a short period of not having rainfall. Other key elements that are common with farmers that participated in discussions are the use of recommended techniques which include closer follow up, weeding on time and use appropriate seeds and spacing. The same discussions were carried out with farmers that did not recorded a high productivity rates and the quotes below explain key challenges that hinders them to reach a good yield; Mukagatera Anatahalie with 1.85 MT/HA productivity said that; I planted first soybeans in my plot and after germination, all the crops were totally dry and then I planted for second time and tried my best to do small scale irrigation and this why it gave me low yield resulted from delay in receiving enough rainfall. Mujamawamariya Eugenie with productivity yield of 1.56 in one of her plot said that: I received rainfall and applied fertilizers but my land in this plots is not fertile as the land has red color. Hakuzimana Fidel with productivity level of 1.67 MT/HA of soybeans said that I first planted soybean which failed to germinate due to not having rainfall and I planted again for second time in which I realized a low yield due to lack of enough rainfall From the information above collected during the discussions with farmers; the key hindrance that caused a low productivity level compared to others, is the rainfall shortage as they land received irregular rainfall and the did not irrigation facilities. Therefore, in general the 8

9 irregularity and shortage of rain fall can be considered as key cause for low productivity, especially, lands that are located at uphill Performance of various soybean crop varieties as per spacing techniques One of the factors that influence performance level of any crop variety is agronomic practices and plant spacing, among many, was selected and tested.. Two spacing measurements (40x 10 m and 50 x 25 m) were used. Table 1 below gives the detailed results. Table 1: Productivity as per various spacing Techniques Soybean Varieties Statistics MT/HA per spacing of 40x10 m MT/HA per spacing of 50x25 m SB 24 Mean Median Maximum Minimum SEQUEL Mean Median Maximum Minimum Table 1 above indicates that SB 24 and Sequel for 50 x 25 m spacing is performed better with average yield of 2.6 metric tons/ha which is greater than 2.36 and 2.34 metric tons per hectare for SB 24 and Sequel for spacing of 40 x 10 m respectively. Therefore, it can be concluded that the best spacing techniques that will give a good yield/ productivity is 50 x 25 m and this is also recommend by RAB. Note that for the minimum levels of 1.32 MT/HA and 1.83 MT/HA respectively for sequel were recorded in Rwamagana where one farmer had flood in one of his plots. While the minimum levels or SB 24 of 1.56 MT/HA was in Kayonza where one farmer had a rain fall shortage and 1.8 MT/HA was recorded in Gatsibo from another farmer who faced flood. 9

10 From the results above, it can be concluded that the way soybeans crops are treated and climate conditions have a big influence on determining the productivity level Soybean productivity/performance per District As CDI Rwanda is implementing demo plots in five districts (Kayonza, Gatsibo, Kirehe, Nyagatare and Rwamagana) of Eastern province of Rwanda, it is important to analyses s performance of each crop in each District. Figure 3 shows the detailed results: Figure 4 Soybean productivity in MT/HA per district Figure 3 shows that the overall soybean yield per hectare 2.5 tons/ha for both Kayonza and Gatsibo while Kirehe and Nyagatare districts realized 2.2 and 2.3 metric tons per hectare respectively. Rwamagana district performed better than other four districts at an average yield 10

11 of s 2.6 tons /ha. The differences in productivity amongst the four districts can be explained by the rainfall variability with Kirehe and Nyagatare having received the least amount of rainfall. This was confirmed by farmers that have lands located at up hills where they faced a challenge of not receiving rainfall on time. The post-harvest data analysis went further to explore if farmers experience of entering in CDI program has a significant influence on the productivity level. The figure below shows the detailed results. Figure 5: Soybean Productivity in MT/HA per farmer s period of entrance in CDI programme The results presented above indicates that farmers that worked with CDI in season B 2015 have relatively recorded a high yield compared to new farmers that started working with small holder farmers project in season A This is evidences by the fact that minimum, mean and median of productivity levels for existing farmers are relatively high compared to the levels of new farmers. The table below gives a detailed statistics test for productivity levels among existing farmers and new farmers: 11

12 Table 2: Statistics testing between existing and new farmers performance Statistics Existing farmers New farmers for season A Chi-square P value < 0.05 Level of significant 2016 Mean Not significant Median Not significant Minimum Not significant The results in table 2 above, indicates that existing farmers recorded a relatively high level of productivity of soybean MT/HA compared to the new farmers as the statistic tests indicate nonsignificant differences at probability value of < In addition, it was necessary to do comparison of SB 24 and Sequel productivity level Per MT/HA between season B 2015 and season A The table below gives the results of statistics test by using chi-square. Table 3: Crops Varieties statistics test between season B 2015 and season A 2016 Crop variety Average productivity for season B 2015 Average productivity for season A 2016 Chi-square P value < 0.05 Level of significant SB No significant 12

13 Sequel Significant From the table 3 above, only sequel variety shows a significant increase of productivity of MT/HA by comparing 2015 season B performance and season A 2016 performance. Even though, sequel recorded a significant increase, CDI Rwanda are commended to use both sequel and SB 24 as these two soybean varieties are still both performing well Results from Maize Demo plots Maize crop varieties Germination Rates Germination rates for PAN 53 AND ZIM 607 were recorded for maize varieties for season A 2016 and Figure 6 below shows the detailed results. Figure 6: Maize Varieties germination rates Maize varieties Germinationrates Mean Median Max Min ZM 607 Pan

14 From figure 4, the l average germination rate for maize ZM 607 (99%) is 99% and e Pan 53, 89.5%. However, the maximum and minimum ranges are not significant pan 53 are 98% and 67% respectively against the ones for ZM 607 of 99% and 69 % respectively Performance of different maize seeds varieties The productivity of PAN 53 and ZIM 607 were tested in the demo plots for season A Figure 5 gives the summarized results; Figure 7: Maize varieties productivity in MT/HA Though ZM 607 performed very well in term of germination (according to Figure 4 above), the results from figure 5 show that Pan 53 performed significantly better l than ZM607 with an average yield of 6.61 MT/HA while ZM607 only yielded 4.1 M/HA. The median, maximum and minimum statistics confirm the same situation where Pan 53 reached 6.7, 8.72 and 4.36 MT/ha for median, maximum and minim levels of productivity against 3.9, 5.7 and 2.8 of MT/HA for ZM 607. The difference in performance for Pan 53 and ZM 607 maize varies can be explained by the fact that Pan 53 is hybrid while ZM 607 is local seeds. Therefore, to obtain high maize yields, farmers are encouraged to use Pan 53 seeds for next season planting and the current RAB subsidy is 75% (1, 655 Rwf) of 1 kg of seeds of maize ;while a farmer pays 25% of the total price which is 295 Rwf. 14

15 Performance of various maize crop varieties as per spacing techniques Maize productivity is also influenced by plant spacing. Two spacing treatments were tested (70x 10 m and 75 x 25 m) Table 2 below gives the detailed results. Table 4: Maize Productivity per crop spacing Productivity vs treatment Mean Median Maximum Minimum 75X25 m spacing x 30 m spacing From the table 2 above, the two spacing TREATMENTS performed at almost the same level with yields of 6.6 and 6.3 metric tons per hectare. The maximum levels were 8.72 and 8.4 MT/HA respectively Maize productivity/performance per District The maize demo plots were implemented in five districts of Eastern Province (Gatsibo, Kayonza, Kirehe, Nyagatare and Rwamagana) and this section analyses performance per district. The figure 6 shows detailed results on soybean productivity for Kayonza, Gastibo, Kirehe, Nyagatare and Rwamagana districts respectively. 15

16 Figure 8: Maize Productivity per district Maize productivity in MT/HA per district Rwamagana Nyagatare Kirehe Kayonza Gatsibo Minimum Maximum Median Mean Reading the figure 6 above, the overall average maize yields are almost the same for five districts at s 6.1, 6.6, 6,2 6.5 and 6.7 tons/ha for Gatsibo, Kayonza, Kirehe, Nyagatare and Rwamagana districts respectively. M maize production can be the same in all the four Districts. To understand why some farmers performed well while others recorded a low level of maize productivity per MT/HA; the table below summarizes some of the contributing and hindrances factors as per farmers discussions. Table 5: Factors and hindrances for maize productivity per MT/HA Quotes from best performing farmers related to contributing factors Kazubwenge Felicien with 8.7 MT/HA of maize said that, My farmers performed very well regardless of delay of rainfall as this land is located in center pivot area where, we have Quotes from poor performing farmers related to hindrances factors Kabayija Jean Bosco with 5 MT/HA of maize said that The poor performed plot in maize was due to the use of ZM607 variety which did 16

17 permanent irrigation system. not give a good yield. In addition, some of my maize produces were stolen before harvesting Barigira Rwibasira with 7.5 MT/HA of maize disclosed that I planted crops in line and respecting recommended spacing, applied fertilizers that include organic manure and mineral and added new manure to maintain rainfall and my land received sufficient rainfall that supported in having good yield Mukagatare Annociatha with 8 MT/HA of maize said that; I did a closely follow up of her crops and did weeding accordingly; my land is very productive as he applied mineral fertilizers and she added manure that include cow dung combined with other herbal manure; my land received rainfall on time and she planted on time and applied mulching and all these contributed to my good yield. Uwihanganye Francois with 8 MT/HA of maize said that my land received enough rain fall on time,i applied manure (combination of cow, goat and rabbit dungs, fertilizer and mineral fertilizer; and used recommended techniques Cyubahiro Charles with 3.83MT/HA of maize said that The low productivity of maize from my plot was recorded in the side where I used ZM variety that gave me a low yield compared to Pan 53; so this variety does not perform well Nyirakarinka Alliane with 3.31 MT/HA disclosed that said that they had short rainfall and also use ZM 607 which give low productivity compared to PN53 Uwihanganye Francois with 3.97MT/HA of maize said that I did performed well for soybeans and maize with pan 53 variety; however, the plot with ZM607 variety poorly performed. Therefore,ZM607 is not a good maize variety Mukandayisenga Didacienne with MT/HA of maize reported that; My land Received rain fall and I planted on time, used manure and mineral fertilizers, weeding on time and I used recommended techniques From farmers discussions data, it is clear that the best performing farmers in making a good maize productivity were mainly influenced by the availability of rainfall on time and also used PAN 53 maize variety. In other side, the plots that used ZM 607 had low yields and in some cases farmers had rain shortage problem. 17

18 2. Conclusion and Recommendations From the 2016 post-harvest data analysis the following key learning points are recorded: Germination rates for the two soybean crop varieties are almost the same for SB 24 and Sequel at 87.1% and 88.47% respectively. This confirms conclusions obtained in the 2015 analysis among the two soybeans crop varieties, SB 24 and Sequel are performing well and at almost the same level with yields of 2.5 and 2,6 tons/ha respectively. When compared to the last season analysis, Sequel scored a high increase of 0.51 MT/HA while SB 24 increased at 0.16 MT/HA; Soy crop spacing technique of using 50 x 25 m performed better than 40x10 m with yields of 2.6 and 2.36 TONS/HA respectively; ZM 607 maize variety recorded a high germination rate of 96% than 89% pan 53; however, Pan 53 performed very well by realizing a productivity of 6.61 MT/HA compared to 4.1 M/HA of ZM607; It has been learnt that spacing techniques applied for maize at performing at the same level; For both soybean and maize crops the five districts can perform well if rainfall is available and appropriate seeds are used; From the conclusion above, CDI Rwanda is recommended to: Continue promoting the use of SB 24 and Sequel as good performing soybean varieties and the recommended performing spacing of 50 x 25 m; Promote the use of pan 53 maize crop variety as it performed very well than ZM 607; Close supervision of master farmers that are implementing soybean seeds multiplication so that farmers can reach production phase for the coming season A 2017 highly needed; 18