This negative coefficient could capture the allocation of a higher value of resources for counties that have experienced low performance during that fiscal year, or cutbacks for a particular county that has performed well. As Foster and Rosenzweig found new technology takes a while to be adopted, and its full impact is observed over time. So, a combination of the two may explain the results we obtained. Therefore, consideration of only the current period expenditures on measuring the impact of UCCE research and outreach expenditures on productivity only tells part of the story. A more complete picture requires understanding how the current stock of research-based knowledge impacts productivity. The current knowledge stock is the sum of old and new knowledge produced through expenditures on R&D and outreach, thereby providing a more complete understanding of the long-term impact of UCCE expenditure on county productivity.22 The trend we observe in the UCCE extension expenditure coefficients as the rate of depreciation grows from 0 to 100 percent presents an increase up to 50 percent depreciation and then a decline. At that range, we observe either insignificant coefficients or negative coefficients.One possible interpretation is that the more frequent the replacement of knowledge the higher the impact of funds spent on knowledge creation and dissemination. This is up to a given point at which the effectiveness of the knowledge stock decreases/drops. When knowledge replacement is 100 percent, meaning every year all knowledge becomes obsolete and needs to be replaced, the UCCE system is not efficient, leading to a negative coefficient of its expenditures stock.Empirical results in Table 2 inform how UCCE impacts average county-level productivity. However, we now want to test how the impact of UCCE expenditure on productivity varies across counties. Heterogeneous impact across counties can result from various reasons. In particular, differences in the resource base in the various counties,microgreen fodder system and the composition of the crops grown, can lead to differences in extension productivity.

From a policy perspective, this analysis is an important contribution to the literature, because it allows evaluating policies that affect certain localities that face different climatic or soil fertility. To achieve this, we have made some modifications to our original model. The main empirical model remains unchanged, but we include interaction terms between dummy variables representing each county and its UCCE expenditures into the old model. Regression coefficients for 23 counties are reported in Table 3 for knowledge depreciation rates ranging from 0 to 20 percent, and it includes only the estimates of the coefficients for the counties that interacted with the UCCE expenditures.The first row in Table 3 reports the impact of UCCE in Alameda County on total value of sales, which is negative for all used knowledge depreciation rates, and is statistically insignificant.Fresno County records the highest positive coefficient of UCCE expenditures stock. It varies from $25 to $191, depending on total value of sales per acre, for knowledge depreciation rates ranging between 0 and 20 percent, respectively. The coefficients for Fresno County are the highest and statistically different from 0 at 1 percent level of significance. San Bernardino County has the next highest impact on total value of sales per acre, which ranges between $10 and $82. Thethird highest statistically significant impact is obtained for Tulare County, which ranges between $10 and $72. The coefficient estimates for Los Angeles and Santa Clara counties indicate no significant impact of UCCE expenditures stock. Kern, Monterey, San Joaquin, Stanislaus, and Ventura counties, which are among the top 10 agricultural counties, have positive and statistically significant impacts reported in columns – of Table 3. Amador, Calaveras, Humboldt-Del Norte, Modoc, and Siskiyou counties have negative statistically significant coefficient estimates for knowledge depreciation rates ranging from 0 to 20 percent.For Imperial County, we observe that for 20 percent knowledge depreciation rate, the value of the coefficient estimate does not remain statistically different from 0. This result implies that adoption of new technologies at these rates may incur high costs and can stop impacting productivity positively. Los Angeles, San Francisco-San Mateo, and Santa Cruz counties do not report high impact on productivity, even though they are among the counties recording some of the highest expenditures made by UCCE.Overall, Fresno, Kern, Monterey, Tulare, and San Bernardino counties record the largest impacts of UCCE expenditure stock.

The first four counties are among the top 10 agricultural producers in the state. All these counties are also among the biggest producers of some of the most high-profile agricultural products in terms of receipts, e.g. grapes, almonds, strawberries, and citrus among fruits and nuts, tomatoes and lettuce among vegetables, and dairy, livestock, and poultry. The results discussed above provide better understanding of UCCE’s impact on individual county-level productivity. More productive counties in general report higher impact of UCCE presence.A pertinent issue with respect to this paper is the substitutability between UCCE expenditure stock and other inputs of production. This is particularly relevant because some counties may face scarcity of one or more of the traditional inputs, and it would be an important contribution if expenditures on UCCE can be a substitute for the said input. For this analysis, we use the inputs that have been found to have a statistically significant positive impact on productivity, such as hired labor, and acres of chemical application. Since number of primary occupation farmers brings down productivity, it is a ‘bad’ input. We have used a linear model in this paper, which makes the calculations simpler, under the assumption of constant marginal productivity. This means that a $1 increase in UCCE extension expenditure stock per acre of farmland will lead to a reduction in hired labor per acre by nearly 0.0003 workers, keeping total value of sales per acre constant. This is a reduction of nearly 1.5 percent, compared to the mean value of this variable . For the next significant input, which is acres of chemicals applied as a share of total farmland acres, we find that MRTS equals −0.00556 . This means that a $1 increase in UCCE expenditure stock per acre of farmland will lead to reduction in the share of chemicals applied per acre by nearly 0.006, keeping total value of sales per acre constant. This again is a reduction of about 1 percent, compared to the mean value of this variable . Similar trends in substitution were reported in Goodhue, Klonsky, and Mohapatra , suggesting that almond grower education programs can have a significant effect on pesticide use decisions.

We observe that substitution effect is low between the aforementioned traditional inputs and UCCE expenditures, thereby hinting at complementarity between each of them and UCCE expenditures. These estimates are a starting point in the discussion on the topic, which has very important policy implications not only for California but also for the entire nation. Using the coefficient estimates, we calculate the rise in total value of sales per acre for our sample, using mean UCCE extension expenditures per acre. That amounts to $41 . Multiplying this $ value by mean farmland acres in our dataset over the analyzed period provides a total increase in value of sales amounting to $22,165,359 , on average, per county. The average per county real UCCE extension expenditure for the 20-year period between 1992 and 2012 amounts to $1,778,146, which implies an average per county profit of nearly $20 million , due to the UCCE extension expenditures on research and development, and outreach. This provides some evidence of the scale of impact UCCE expenditures stock has on average county productivity. The same calculations for individual counties can provide a more in-depth understanding of the effects on them for policy planning.We observe allocated extension expenditures per acre with a mean of 6.21 and a standard deviation of 8.59, suggesting a wide difference across the counties. Decisions on allocation of extension funding at the county level depend on many criteria, including the county’s productivity and long-term planning criteria , and even political considerations and lobbying, as was already suggested in our paper. While we are running contemporaneous regressions , the decision making does not take place contemporaneously. That is, the yearly spending budgets are set prior to whatever economic activity goes on in the county during that year. The budget process happens before the total sales for that year are known. It seems natural to think that the effect runs from spending budget to sales,barley fodder system rather than the other way around. Nevertheless, we have only five years of production and sales data, and it may be reasonable to think that productive counties in a year can be favored with larger budgets the following years. But this is not the case. Scrutiny of Figure 1 suggests, for example, that Fresno, which is one of the most productive counties, had UCCE expenditure of about $3 per acre in 1992 and in 2007. On the other extreme, Alameda, which is one of the least productive counties, had UCCE expenditure of about $7 per acre in 1992 and in 2007. Thus, over time we do not observe overall big changes in UCCE expenditure that are triggered by the productivity of the county, and the case for endogeneity becomes weaker, if not irrelevant.

The large SD of the extension expenditures reinforces the aim of our analysis that explains the variation in sales as a function of the variability of UCCE expenditures. A caveat of this paper is that spillover effects across counties have not been included in the model. The empirical model assumes that there is no spillover, but this effect can be incorporated in future work. This paper estimates a simplified model of agricultural sales as a function of inputs, including UCCE expenditures stock, to provide a county-level impact of UCCE expenditures on R&D and outreach on productivity, which can provide policymakers with a reference point for policy decisions in California. Another caveat is the relatively short period of time , considered in our analysis. Longer time-series data would lead to higher values of benefits from the estimated impact equations.We estimate the impact of the University of California Cooperative Extension on county-level agricultural productivity in California, using a model representing a relationship between value of agricultural sales as a proxy for productivity, and quantitative inputs of production, including UCCE expenditures. Our analysis is aggregated to the county level because UCCE operates from county offices across the state. We obtained data for UCCE budgets for all agricultural research and development , and outreach/dissemination projects for 50 county offices statewide for the years 1992–2012 . Stock of knowledge produced through UCCE extension expenditures on R&D and outreach is modeled as a function of a stream of current and depreciated past expenditures, and used as our independent variable. Data on factors of agricultural production, such as harvested acreage, hired labor, chemical applications, machinery, average farmer age, and number of primary occupation farmers were obtained from the Census of Agriculture conducted by United States Department of Agriculture for five census years, spanning over 1992–2012. Productivity is represented by total value of sales per acre of farmland, using data from the Census of Agriculture. To estimate the impact of UCCE expenditures on agricultural R&D and outreach/dissemination on productivity, we construct a stock of expenditures. We use current and five lagged values of UCCE expenditures, and a range of different depreciation rates from the literature. The intuition is that old knowledge depreciates over time, therefore older expenditures enter the model at a depreciated value. We analyze our model using depreciation rates ranging from 0 to 9 percent, and then 10, 15, and 20 percent following Griliches . Regression results indicate that UCCE’s stock of expenditures has a statistically significant impact on total value of sales per acre, which varies from nearly $1 to $9, for depreciation rates between 0 and 20 percent. For higher rates of depreciation of expenditure, the coefficient becomes statistically insignificant. Results therefore suggest that for more dynamic systems with frequent innovations, UCCE’s efforts have a higher impact on productivity. This effect, however, becomes insignificant with very high levels of depreciation. For a knowledge depreciation rate of 100 percent, we find that the coefficient becomes negative , and this effect is statistically different from 0. This result likely captures the allocation of higher expenditures on counties that have reported lower performance during the year, or cutbacks for a particular county that is performing well.

According to Berry et al., farmers’ health is a critical component of their ability to adapt to climate change; thus, providing improved health care facilities would be a useful support tool for the Dalsinghpara village.Most of the households having a moderate and high adaptive capacity level are found in the Ballalguri village.This village has scored well in most capital assets except for the main road accessibility during the monsoon season.During the rainy season, the village becomes isolated from the rest of the district since all roads get submerged under the water.Moreover, there are no bridges over the rivers in this area, and the river bed is used as a means of transportation.Consequently, during the monsoon months, access to health care units and marketplaces becomes extremely difficult, and sample farmers from the Ballalguri village stated that they need to stockpile dry foods for this period in order to survive.However, the rivers are mainly rainfed and remain dry the rest of the year.Therefore, improving road conditions, especially in this area, should help to reduce the vulnerability.This result is consistent with the empirical findings of Nelson et al.and Choden et al., which stressed the need for investments towards the improvements of the rural roads for enhancing the adaptive capacity of the farmers.Improvement of physical capital would provide households with more opportunities not only for making profits via better farming practices but also for generating incomes from offfarm and non-farm activities.This would help enhance the adaptive capacity of rural households in these areas by diversifying their income sources.The households having a high level of adaptive capacity also attained relatively higher scores in financial capital.

Also, the households having at least one member working outside face lesser financial stress,stacking pots and they are relatively less vulnerable.However, owing to the COVID-19 pandemic and lock downs to prevent the spread of such a deadly infection, many migrants were forced to return to their villages.In 14.77 percent of the surveyed households, the respondents stated that their household members lost work during the pandemic and were unable to find alternative employment owing to a lack of employment opportunities.Apart from these, access to credit is comparatively high amongst the high adaptive capacity households.Although, only 7.38 percent of the households accessed credit during the last five years.Low educational level, distance to the formal financial institutes, and lack of land ownership rights could be constraints for accessing the credit facilities.It was also found that the farmers who owned larger farms had more adaptive capacity.Likewise, Jamshidi et al.reported that larger landholders are less vulnerable due to their higher adaptive capacity.However, our study also pointed out that soil quality and land ownership are more important than the landholding size.In this line, the households with higher adaptive capacity also scored more in the aforementioned natural capital indicators.Adaptation to climate change at the agricultural level entails farmers’ strategies/measures to reduce their crop damage or utilize different beneficial opportunities in response to the current or expected impacts of climate change.However, it is difficult to compile all of these strategies and determine whether or not those are climate induced.Therefore, in this study, firstly, we identified the local-level climatic stressors and finally reported the farm-level adaptation measures that are specifically targeted to minimize the impacts of the identified stressors.In Fig.6, different adaptation measures as opted by the farming households from different levels of adaptive capacity have been reported.A large number of farming households with low adaptive capacity from the village Turturi Khanda left their land as fallow as their land has filled with stones and pebbles from flood, making it uncultivable.Whereas the households whose landholdings are partially infertile cultivate paddy in small land that is not affected by the floods, and some also planted woody trees like Teak and Sal in those flood-affected lands.

These woody trees, according to the respondents, are quite resistant to flooding and pest attacks and also generate additional income for the household.Likewise, Dhungana et al.also reported that several farmers from the Nepal Himalaya planted trees in response to floods.The moderate and higher adaptive capacity households were found growing different crops and trees such as paddy, areca nuts, and woody trees.Meanwhile, only one sample household in the TurturiKhanda village had access to irrigation water by means of channeling the spring water into the field.In the Dalsinghpara village, irrespective of the adaptive capacity, all the households switched from the cultivation of traditional cereals to cash crops.The respondents reported that they perceived an irregular and decreased rainfall which was not sufficient for paddy cultivation.Over the years, low rainfall in the region coupled with decreased yields and pest intensifications have induced farmers to stop cultivating the cereals and moving to less water-intensive cash crops like areca nuts , black pepper , cassava , and pineapple.All these crops are low maintenance and increased households’ income.Similarly, a shift from traditional staple cereals to commercial crops in the Western-Himalayan landscape was reported in Rana et al.and.Some farmers also planted different woody trees to increase their income which requires minimal water and low maintenance.All the horticultural crops and woods are sold to the wholesalers, who collect those directly from the farms or households.The sample households from Dalsinghpara village mainly use watering buckets to water in their fields as there were no improved irrigation facilities.Both the moderate and high adaptive capacity households from the Ballalguri village were found to be engaged in paddy cultivation, and a large proportion of them also diversified their production system by planting areca nuts.Plantation of areca nut as a commercial crop recently became popular in the Sub-Himalayan region of West Bengal.As few households have access to improved irrigation facilities , paddy cultivation is mainly done in the monsoon season only.Also, all the sample households are found to use shorter-duration varieties of paddy as traditional varieties are no longer available in the markets.The farmers also reported that the onset and withdrawal of monsoon have become irregular, and they alter their transplantation of paddy as per the arrival of monsoon for obtaining the benefits of natural rainfall.

Changing the transplanting date as an adaptation measure is widely reported throughout the world.All the sample households who grow paddy also sow a higher quantity of seeds in order to get some extra paddy seedlings.These excess seedlings are re-transplanted if the previously transplanted seedlings are damaged due to heavy rainfalls.Whereas during the time of harvesting, if households face crop failure due to heavy rainfall, they usually dry the wet paddy, and later on, depending on the quality, those are either used for their own consumption or as animal fodder.The farmers also reported that during the non-monsoon period, this area faces a water crisis; however, as the households diversified their production by incorporating areca nuts and by selling these nuts, their vulnerability has significantly reduced.Even those households which are not cultivating areca nuts are planning to invest in it.On the other hand, irrespective of perceiving increased pest attacks, the application of chemical pesticides was limited in all the villages as the farmers believed that chemicals would deteriorate soil fertility.The contribution of greenhouse gasses from agriculture is estimated to be 11−15% of the entire emissions.In which, the release from agricultural soils and rice cultivation report 39% and 9% of the total release, respectively.Nitrous oxide , which accounts for a third of the agricultural sector GHG emissions, has a global warming potential of 265 over a hundred year lifespan.The potential for N2O emissions increases when the availability of N rises because it is claimed that N2O production in agricultural soil arises mostly through the microbial transformation of inorganic N.Until 2030, the Intergovernmental Panel on Climate Change – IPCC evaluates that GHG emissions will increase by 35% to 60%.The increasing GHG emissions from paddy cultivation have become a major concern in recent years.It is reported that, together with the intensive farming policy, the total GHG emissions from the agriculture sector in Vietnam increased significantly from 1994 to 2013.specifically, the emissions were at 52.4, 65.1, 88.3, 89.4 million tons of CO2 equivalent in 1994, 2000, 2010, and 2013, respectively.According to the data reported in the two national GHG emission inventories in 2010 and 2013,sawtooth greenhouse the amount of emitted CO2 from irrigated rice cultivation increased from 41.31 million tons to 42.51 million tons, respectively.In addition, the direct N2O emissions from agricultural soils increased from 12.91 million tons in 2010 to 13.17 million tons in 2013.Therefore, the most important criterion in the socioeconomic development progress of Vietnam and the Mekong Delta is to develop crops that simultaneously ensure food production and reduce GHG emissions.Regarding N2O flux from agricultural soils, a significant source of this effusion comes from the consumption of synthetic N fertilizers in crop cultivating steps.Chai et al.recognized the application of N as the major cause to direct N2O emissions.In paddy cultivation, increasing N use increases 4.56–7.11 g N2O/kg N of the seasonal N2O flux; the GWP also shows a squared reaction to N rate, peaking at 122–130 kg N/ ha.

Moreover, the experiments by Zhang et al.in China helped to calculate the cumulative N2O emissions during the 2011 growing season under different levels of N application.The results were at 23.09, 40.10, and 71.08 mg N2O/m2 at low-150 kg/ha, moderate-210 kg/ha and high-300 kg/ha of N application, respectively.Thus, it is recommended that the cultivators should reduce the high N fertilizer application in order to lessen the GWP while the optimum paddy yield is still maintained.It is claimed that the intensive farming and expanded demand scenario create such an extreme pressure on the rice fields, thereby causing soil degradation and imbalanced paddy ecosystem resulting in increasing environmental GHG emissions.About 90% of the world’s rice is produced by Asian countries , and 90% of the CH4 produced in the world’s paddy fields comes from this region.For this reason, understanding the CH4 and N2O release mechanisms in rice fields is necessary for developing well-organized strategies and changing conventional crop management regimes.Therefore, reducing GHG emissions becomes potential.Zou et al., with their on- field assessment, concluded that the seasonal total N2O is equivalent to 0.02% of the nitrogen applied under continuous flooding of paddy fields.The emission factor of nitrogen for N2O was proposed to be 0.42% from the result of the ordinary least squared regression model.Moreover, Yan et al.also indicated that CH4 emissions are significantly affected by organic fertilizer modification and water regimes in the growing seasons.Regarding the climate smart strategies for paddy cultivation, controlled irrigation or the alternative wetting and drying 1 technique is believed to be effective for mitigating the CO2 equivalents of CH4 and N2O emissions from fields.Multiple drainage , a simplified form of AWD, has also been practiced in the MKD.Uno et al.evaluated the consequence of this technique on yield and GHG emissions in paddy fields in An Giang province, where full dike systems are constructed for fresh water paddy production.The authors concluded that multiple drainage system can at the same time improve the output and reduce CH4 emissions in paddy fields if it is adequately implemented.Specifically, MD fields report a significant increase at 22% in yield compared to traditional flooding fields.Although there is no difference in N2O emissions found, seasonal total CH4 emissions were markedly declined by 35% in MD plots.A study of CH4 measurement by Vo et al.was conducted in paddy farms from different agro-ecological zones of the MKD.Through the emissions collected by using the closed chamber method, the overall emission factor of the entire delta is approximately 1.92 kg CH4/ha/day, which is about 48% higher compared to the globally default value set by the IPCC.However, this study by Vo et al.did not record the difference in farming patterns.Interestingly, the rice-beef-biogas integrated system presented in the study by Ogino et al.is believed to mitigate GHG emissions and energy consumption compared to the specialized rice and beef production system in Vietnam.Hanh et al.evaluated the nitrogen use efficiency of six rice varieties, including Chiem Tay, Te Tep, Re Bac Ninh, IR24, P6DB, and Khang Dan 18 in North Vietnam.P6DB and CT vari-eties, which present the smallest and largest effectiveness of nitrogen use, were chosen for a genetic testing in the next step.The results on nitrogen use efficiency are considered useful for further genetic analyses of sustainable agriculture.

Ten mL of the upper layer was transferred to a 15 mL centrifuge tube containing 500 mg of Primary Secondary Amine and 1.5 g of anhydrous magnesium sulfate.The centrifuge tube was shaken for 30 s followed by centrifugation for one min.at 1500 rpm.Six mL from the upper layer was taken, concentrated to dryness using Turbovap , and the final volume was made up to one mL using n-hexane and analyzed by Gas Chromatograph.For recovery studies, pesticides at two levels organochlorines at 0.01 and 0.05 mg kg−1 and organophosphates at 0.025 and 0.125 mgkg−1 were undertaken.Certified reference materials of pesticides were purchased from Sigma Aldrich and stock solutions were prepared using pesticide grade solvents.Single laboratory method validation was carried out to found the recovery of pesticides.Spiking solutions were prepared from stock solution for measuring percentage recovery.For calibration were undertaken with six levels of serially diluted standard mixture prepared from stock solutions.Based on these working standard solutions, calibration curves were obtained and were used to evaluate the linearity of the gas chromatograph response helps to quantify the pesticide residue of the samples.The data on the moisture and nutrient composition of different types of weeds used in the study are illustrated in Table 2.0.Among the different types of weeds, moisture content varied from 68.8 to 86.7%, with higher value in mikania and lower in macranga.Normally a certain amount of moisture is essential for composting because the main site of microbial activity is in the thin water film on the surface of particles.The chemical nature of all the weeds under study was acidic in reaction with pH values varying between 5.1 and 6.3.

Content of oxidizable OC in general varied from 30.6 to 55.0%, higher values with lantana and lower with mikania.As in the case of oxidizable OC, relatively higher N was also observed in lantana followed by macranga , chromolaena and mikania.C:N ratio was almost similar in all the species,hydroponic nft ranging between 26.0:1.0 and 30.0:1.0.However, the substrate materials with higher N content or with narrow C/N ratio are always desirable in decomposition process, since N is supposed to promote the multiplication and activity of microorganisms, there by shooting up the decomposition at an increasing rate.Among the other major nutrients, P varied between 0.09 and 0.29%and K between 1.8 and 2.2%.Both P and K were higher in chromolaena.The percentage content of important mineral nutrients did not vary widely between the weeds, whereas the C:N ratio of the weeds varied between 26.0 and 30.0, the desired value being 25.0–30.0.The optimal start up conditions helps to promote the decomposition of weeds.The proper balancing of nutrients, content of moisture and aeration were noted as essential factors for effective conversion to humic mass.All the weeds such as chromolaena, lantana, macaranga and mikania used as feed stock in this study meet the required C:N with adequate content of nutrients.Temperature is one of the most important indicators, which rebound in the process of decomposition of organics and changes in microbial activities.The change in temperature occurred in the weed biomass with the elapsed time are illustrated in Fig.1.This figure portrayed that the temperature in the weed stack, applied with various inocula viz; cow dung, urea, microbial consortium and jeevamrutham got elevated and reached to a peak of about 54.0 °C, 63.0 °C, 53.0 °C and 66.0 °C respectively after 10 days of decomposition process while the control pile remained with 48.0 °C.It was also noted that all the piles attained thermophilic temperature shortly after stack establishment.The temperature in the weed biomass applied with urea, microbial consortium and jeevamrutham reached the highest levels on 3rd day and continued to remain at higher levels in the following days.This high temperature was enough for destroying the microbial pathogens, and to assure rapid degradation of weeds.During the formation of humic substance, the heap applied with urea attained the highest temperature at 4th day and the lowest at 50th day of composting.However, the maximum temperature attained in the heap applied with jeevamrutham was on par with urea and microbial consortium, and the same heaps attained a temperature of >70.0 °C on 3rd day itself, which is definitely due to the intense activity of microorganisms.During the initial activation days, the simple organic compounds such as sugars are mineralized by microbial communities and produced CO2, NH3, organic acids and heat.The optimum range of temperature in the decomposition process was 40.0–65.0 °C allowing to kill pathogens above 55.0 °C.During this phase, thermophilic microorganisms deteriorate cellulose and lignin in the substrate materials.

Finally, during the maturation stage, the temperature slowly decreased owing to the reduced microbial activity resulting from a diminishing stock of biodegradable compounds.The hike in temperature during the initial days of the experiment is due to mineralization and transformation of organic matter,whereas in the later stage, the stabilized condition resulted in scaling down the production of heat.The initial boosting of temperature varying between 48.0 °C and 72.0 °C within a short time of stack establishment in this study is due to the intense microbial activities triggered by the application of additives; cow dung, urea, microbial consortium and the farm derived microbial formulation.Normally, temperature varies over time and by the shape of the decomposing stack, and followed a pattern consistent with degradation of organic feed stock by microorganisms.In the last phase of maturation, bacterial numbers decline and fungal population increases in all the treatments as easily decomposed material got exhausted.At this stage recalcitrant materials dominate and temperature decline to the ambient level.Application of additives to decomposing organics is supposed to have significant impact on the period of decomposition.In the present study, the time taken for decomposition of weed biomass without any additives was 120 days.But, the period got reduced to 100, 70, 94 and 75 days with the addition of cow dung, urea, microbial consortium and jeevamrutham respectively.Application of microbial consortium and jeevamrutham could reduce the decomposition period from 120 days to 70–75 days, while the reduction was only up to 100 days with cow dung.The intense activity of vast numbers of microorganisms such as bacteria, fungi and actinomycetes coupled with relatively higher content of N, contributed from cow urine as well as pulse flour might be the probable reason for intense decomposition and subsequent reduction in jeevamrutham applied piles.Results of the study pointed out that microbial formulation namely jeevamrutham was equally effective with laboratory produced microbial consortium in reducing the period for converting weed biomass to humic substance.Moreover, the practice of application of urea during the process of decomposition can be eliminated by the use of microbial inoculum.Quality evaluation of humic mass produced from weeds was carried out with respect to various basic physico-chemical properties, nutrient potential, and presence of toxic contaminants.Those humic substances in general were with acceptable color, i.e., coffee brown.The heat generated during the initial period of experiment is believed to have profound effect on the color of the final product.

The heat generated during the process generally depends up on the type of feed stock and activity of microorganisms.The coffee brown color of humic substances generally indicates high content of OC, which is considered as the key factor for organic farming.The content of moisture in the final humic substances were 20.3%, 20.8%, 22.3%, 22.1% and 23.6% in control, cow dung, urea, microbial consortium and jeevamrutham applied treatments respectively.The higher content of moisture was associated with jeevamrutham applied treatment and lower in weed biomass alone.In the composting technology, moisture content between 40.0–60.0% of raw materials is normally recommended for the success of composting.Biological activity will be slow if the compost heaps start to dry and virtually cease if it dries out.During the maturation stage, lower moisture content is desirable as the compost become lighter, hydroponic channel making it easier to mix and increasing the shelf life.Content of moisture in the compost samples normally varied with the type of the raw material and season of the climate.According to the FAI , 15.0– 25.0% is the desired level of moisture in the finished composts.Moisture content less in the composts may not have been stored for longer period due to the preeminent moisture loss, whereas the excessively dry composts is usually dusty and unpleasant to handle.The bulk density of composts varied from 0.56 to 0.82 g/cm3 dry matter, with highest values with control.Application of various inocula could reduce the bulk density of final compost as observed in the treatments with urea , microbial con-sortium , cow dung and jeevamrutham.According to Indian regulatory rule of organic manure, bulk density is measured on dry weight basis as an indicator of particle size, and also indicates organic matter as well as inert material/ash content.The lower bulk density of the composts is desirable because it helps to increase the water holding capacity of soil when applied continuously for longer period of time.The important chemical characteristics of humic mass such as pH, TOC, oxidizable OC, N, C/N are given in the Fig.6.pH is an important property deciding the quality of this final decomposed product.In the present study the humic mass produced in all the treatments were alkaline in reaction with the values varying between 7.7– 8.3.

The lower pH was reported in weed biomass alone and the higher value in the treatment applied with jeevamrutham.Compared to the substrate materials, pH was high in the finished products of all the treatments.A good quality compost is supposed to have a pH between 6.5 and 7.5.However, considering the acidic nature of the soils of Kerala, the matured decomposed mass with pH more than 6.0 are beneficial for improving the chemical condition of the soil.pH was found to scale down at the end of decomposition, and this decline is mainly due to the volatilization of ammoniacal N and hydrogen ions released through the nitrification activities of nitrifying bacteria as well as the emission of large volumes of CO2.Carbon farming is mainly intended to enrich the soil with carbon, which is mainly dictated by the total organic carbon and dichromate oxidizable OC, and the values in this study varied between 22.8 – 39.4% dm and 19.6 – 33.8% respectively.There has been a strong relationship between oxidizable organic C and TOC valuesin the humic mass produced from weeds.They were with higher content of TOC obviously due to the higher carbon stock in the feed stock.As per the FAI guide lines, the oxidizable organic C in an ideal compost for soil application must be ≥ 16.0%.The decline in oxidizable organic C observed during the process of decomposition is definitely due to the microbial decomposition of organic substrates , as microorganisms consume carbon for energy.A decrease of oxidizable OC was considered as an indicator of maturity and stability of composts.C/N ratio is an important property governing the quality of humic substances produced after decomposition, the ideal value being < 20.0:1.0.The C/N ratios of most of the humic mass produced in this study were below 16.0:1.0, indicating a relatively higher content of N than C, which automatically leads to faster mineralization process, on application to soil.The CFU values of bacteria, fungus actinomycetes were more in the humic mass produced using farm derived jeevamrutham and comparatively very less in control and urea applied treatment.The treatment with microbial consortium ranked second after jeevamrutham.The species isolated were Bacillus sp, Pseudomonas sp, Erwinia sp.etc.Among these, Bacillus sp.are normal inhabitants in soil.Some fungal pathogens were present in all the samples and the major fungal species were aspergillus, rhizopus, mucor etc.The fungi Fusarium oxysporium was isolated from the treatment without any inoculum.These organisms prevent the proliferation of bacterial pathogens by increasing temperature, and thus facilitating the growth of thermophilic microbes.The phenolic and carboxylic acid groups of phyto chemicals present in the humic mass are also supposed to impart resistance against pathogens.The world population is expected to increase to 9.5 billion people in the next 40 years.This calls for an increase of over 60% in food production worldwide at least by 2050 to combat the crisis faced by the continuously increasing population.Unfortunately, natural resources such as: land meant to sustain food production and meet the demands of such an expected population increase are diminishing coupled with the high cost of the limited existing land.

The management of this crop by flooding requires more water per unit area than in other irrigation systems.In Brazil, the Federal States that produce rice in greater quantities are Rio Grande do Sul, Santa Catarina, and Tocantins, responsible for, respectively, 73%, 8%, and 11% of national production.In general, the rice crop is produced from irrigation by furrows or flooding.Although the levels of exposure of receptors to hazard may differ among the irrigation methods, the similar approach was adopted in the application of the methodology, as both take into account the flooding of the area.It is also worth noting that the SqMRA methodology must be applied in each project, individually, considering that the exposure levels may vary depending on the local characteristics and operational conditions of irrigation, harvesting, and storage.Thus, this generalized approach, adopted in the present study, is configured only for scientific studies, since the action can lead to a high degree of uncertainty.The data adopted for the application of the SqMRA methodology in rice cultivation in Brazil are presented in Table 8, according to the model previously described its stages and steps.Notes: 1 The SqMRA was applied in two scenarios, in which the first considers the effluent to be disinfected , and the second considers the reality of sewage treatment conditions in Brazil.2 Inhalation is attributed to aerosols,hydroponic gutter generally produced in a sprinkler irrigation system.Although intense winds can also produce these types of micro-droplets in flooded systems, inhalation was not scenarioized in the present paper, for simplification purposes.

However, in cases of application of the methodology in places with the possibility of high winds, it should be adopted for farmers and neighborhoods.The barriers adopted, defined as actions after the harvest, relate only to consumers since the farmer harvests the rice in nature.Given the perspectives and the Brazilian reality, in terms of the quality of treated wastewater, the SqRMA was applied in two different scenarios.In the first one, we chose to adopt Hazard equal to 7, due to the prerogative that a disinfected effluent guarantees more safety to the practice.However, the reality about wastewater treatment in Brazil shows that most of the effluent is treated at a secondary level, without disinfection.Thus, the second scenario relies on the application of the methodology, considering Hazard equal to 9.The complete spreadsheet is available as Supplementary Material.This spreadsheet was developed to facilitate the use of the methodology in other applications and regions, but care must be taken, each case is a case and this methodology represents a real portrait of this case.However, it is important to pay attention to the indiscriminate use of the available spreadsheet, since the user must always apply it with great care, considering the real local characteristics of each irrigation water reuse project.The results presented in Table 6 demonstrate the feasibility of applying water reuse for rice cultivation in Brazil, about aspects of epidemiological risk.As expected, and in accordance with previous observations from other authors, there is an estimate of a higher risk of microbiological contamination for the farmer than for other receptors.Despite the high possibility of contact between the farmer and the RW, the estimated global risk is still in the acceptable level.

In the case of the neighborhood, the risk is greatly reduced because the irrigation method is different from sprinkling and presents a lower possibility of producing micro-droplets that could be inhaled, as already mentioned.But still, it is in the acceptable category.For the consumer, low risk was also expected, due to the processing and cooking of the rice before consumption.However, it should be noted that these risk values may vary depending on the specifics of the configuration of each reuse system, since there may be situations that enhance certain types of contact.For this reason, to calculate the global risk, two procedures were adopted: i) considering the three receptors adopted in the study; and ii) considering only the 2 main receptors involved since the possibility of several receptors, with multiple handling criteria, involved after harvest could change the final value of the global risk.Thus, should be emphasized that for the application of the methodology in a real project, all possible receptors, from irrigation to the final consumer, must be taken into account in conjunction with the food safety procedures needs according to respective regulations, when in place.It should also be noted that when considering all workers involved in the production process of rice irrigated with RW, is possible to minimize risks by introducing capacity building and systematic use of equipment and safety habits.The States of Rio Grande do Sul and Santa Catarina, identified in the present study as responsible for 80% of the Brazilian production of rice, are comprised, almost entirely, in the River Basin of Uruguai andAtl^antico Sul and require, in general, approximately 382 m3 /s of water for irrigation.However, the two RBs present a service rate with domestic wastewater treatment at 30%.

Similarly, the RB Tocantins-Araguaia, which involves practically the entire State of Tocantins, has a demand of approximately 60 m3 /s for irrigation but also has a low rate of wastewater treatment.The relationship between the Brazilian states highlighted in the study and the River Basin Districts also highlighted can be seen in the schematic map in Fig.3.The scenario of high demand for water for irrigation and low production of treated effluent shows the difficulty of structuring water reuse, although the water demand for rice crop production in these regions is high and the risk of contamination of human beings is moderate, as demonstrated by the application of methodology.The RW was defined in two categories to assess the potential for reuse in Brazilian RB, as a function of water quality: Category 1 – RW from wastewater treatment plants that have an organic matter removal higher than 80%; and Category 2 – RW from wastewater treatment plants which, in addition to having an organic matter removal of more than 80%, have disinfection.In this sense, considering the three RB , the potential for supply of reclaimed water in Category 1 is 2.53 m3 /s and in Categories 2 , of 1.12 m3 /s.Since Category 2 , equivalent to Hazard equal to 7 , represents the lowest available water potential for reuse, it was decided to repeat the process of applying the SqRMA methodology, considering hazard equal to 9, which represents Category 1.The results for this reiteration can be seen in Table 10.This reiteration in the application of the methodology presents a very relevant result, in which when offering water corresponding to a secondary effluent , even the estimation of risk for the farmer changing from acceptable to unacceptable, the overall risk remains in the acceptable level, although quite close to the limit of the maximum value.Furthermore, the risk for the farmer can be reduced with equivalent barriers, such as rubber gloves and boots, consequently reducing overall risk.In this sense, it can be highlighted that Uruguai, Atlantico Sul, and Tocantins-Araguaia River Basin have a high potential for the application of water reuse in the irrigation of rice crops by furrows or by flooding, with an acceptable risk of microbiological contamination of human beings involved in the practice.

However, it should be noted that the study deals with a generalized scientific approach and, in the case of a real application, all those involved must be carefully evaluated and the scenarios must be exhaustively studied, also considering the use of additional risk minimization means, such as equipment and safety habits among the workers in each sector, to provide more safety for the practice.It is also noteworthy that in Asia, the largest producer of irrigated rice in the world, the crop represents 40–46% of the irrigated area among all other crops.The water reuse in China has become the main objective of WWTP in the new era of wastewater treatment in the country.In this sense, a good way to solve the problem of water scarcity is to increase water productivity, corroborates the results of the present research.In the case of irrigated rice, it is important to determine the economic and energy implications when considering water reuse options to improve water productivity at the system level.The novel coronavirus has killed millions and shut down entire countries.Yet the danger was not always this clear.In late December 2019, China reported over 40 cases of unusual pneumonia to the World Health Organization.By January 25th, Beijing, Shanghai,u planting gutter and many other provinces had declared public health emergencies, and most cities in Hubei went into lockdown.During this time span, it was unclear whether the virus was a rumor, how deadly it was, or how it spread.In three studies, we investigate how people in China reacted to COVID-19 during this early window of uncertainty.We find evidence that people in some regions reacted more proactively to this ambiguous threat.We test two broad categories of predictors: objective risk factors and subjective cultural factors.Analyses reveal that culture—not simply objective risk—explains meaningful differences in how people responded.At the onset of the COVID-19 pandemic, our research team observed whether people wore masks in public spaces.Day 0 of our observations was January 23rd, 2020, the day Wuhan went into lockdown.We observed people at eight sites across seven Chinese cities for two weeks.We ended our observations when mask use was nearly universal.However, a limitation to the data was the number of researchers we could deploy quickly and safely.Thus, to supplement the data, we surveyed people from a broader range of provinces on when they started wearing masks.Finally, we triangulated the findings against web searches for “masks,” which are less direct but provide more data points and a complete geographic coverage.

In reviewing previous studies on mask use, we identified three limitations.First, most studies relied solely on self-reported data.This could be problematic as people may feel pressured to report that they wore masks even if they did not—meaning self-reports may not reflects actual mask use.In this study, we measure both self-reports and observed behavior, which allowed us to test whether the results converge.Second, few studies have tracked mask use over time.One notable exception is a Hong Kong study, which found that mask use increased from 12% to 67% during the first seven days of the SARS outbreak.Studying response change over time is crucial as early action can save lives.For example, analyses estimated that implementing COVID-19 measures seven days earlier in the United States could have drastically reduced cases.Third, the few observational studies of mask use we found were limited in the locations and lengths of time tracked.For example, a study of mask use during H1N1 only observed two subway stations in Mexico City.Our study expands on this approach by covering multiple, diverse regions.This richer dataset allows us to explore a range of cultural factors beyond basic demographics like age and gender.We move beyond prior research on masks by testing for less obvious cultural differences that might influence mask use.One feature of collectivistic cultures is interdependence—a view that people are, or should be, dependent on each other.Such a worldview could increase mask use because, even if people are unafraid of risking their own health, masks could prevent them from transmitting the virus to others.Even before the COVID-19 outbreak, some cultural observers argued that wearing masks in Japan symbolized an obligation to protect others from the wearer.In contrast, some people argue that mask mandates infringe on individual freedoms in individualistic cultures like the US.One important study found that mask use was higher in more collectivistic nations and US states that scored higher on collectivism measures.Another cultural influence on mask use could be norm tightness.All societies have social norms—ideas about what behaviors are proper and not.Yet some societies have tighter norms than others.Recent research suggests that tightness varies within China.Specifically, norms are tighter in more developed provinces, as well as provinces that farmed rice in the past.Tight norms come with costs and benefits.Tight societies generally have stricter rules— which seems to conflict with out-of-the-box thinking and innovation.For example, tighter societies have fewer patents for inventions.However, tight norms can help societies respond to danger.Tighter societies tend to have more social order , which might facilitate strict mask policies.

Furthermore, organic farming encourages on-farm agrobiodiversity, both through the diversity of plant varieties cultivated , and improves farmers economic profitability.Organic farming aims at creating a sustainable agricultural production system, including economic, environmental, and social sustainability.In Ghana, the potential of organic and its suitability as a future solution to some key farming system challenges is still not recognised.Studies on cocoa production in Ghana often focus on one dimension of sustainability.Thus, this study to the best of our knowledge will provide the first holistic sustainability assessment of organic and conventional cocoa farming systems in Ghana.The study seeks to answer the question, does the sustainability performance of organic cocoa farming system in Ghana differ from conventional farming? The Organic Farm System for Africa database made available by Research Institute of Organic Agriculture for analysis.The dataset provided information for over 300 indicators covering 6 themes and 14 sub-themes for the environmental integrity, four themes and 14 sub-themes for economic resilience, six themes and 16 social well-being sub-themes and five themes and 14 sub-themes for good governance.In Atwima Mponua District , a typical cocoa farming system is defined based on the predominance of smallholder cocoa farming households, engaged in either practicing conventional i.e., “business-asusual” or based on initiatives termed environmentally friendly.Cocoa farming systems are characterised by the different crops grown,vertical grow system and the livestock types reared.Cocoa farming systems used both family and hired labour for farming activities.

The organic cocoa farms are certified through Internal Certification System.These criteria guided the selection of 398 cocoa farmers, out of which 71 were organic cocoa farmers, with 327 conventional cocoa farmers.The OFSA covered three months data collection period from December 2016 to February 2017.Sustainability performance in terms of environmental integrity is illustrated in Fig.3.The five sub-themes, waste reduction and disposal, energy use, material use, genetic diversity and species diversity showed the highest sustainability performance between 60% and 80% for both organic and conventional cocoa farming systems.The lowest sustainability performance was shown by soil quality and freedom from stress for both organic and conventional farming systems that fell between the scale of 20% and 40%.Sustainability performance with respect to greenhouse gases fell within the scales 61%–80% and 40%–60% for organic and conventional farming systems, respectively.Sustainability performance of animal health and land degradation fell within the scales 41%–60% and 21%–40% for organic and conventional farming systems, respectively.Mean rank difference between the different farming systems based on the sub-themes of Environmental Integrity is shown in Table 2.Mean rank scores for the organic farming system ranged between126.3 and 260.6.Mean rank scores for conventional farming system ranged between 103.2 and 199.6.The two cocoa farming systems differed significantly for all the sub-themes except for waste reduction and disposal, and freedom from stress, where the pvalues were above p = 0.05.Economic resilience sustainability performance is illustrated in Fig.4.The risk management and profitability sub-themes showed the highest sustainability performance between 61% and 80% for both organic and conventional cocoa farming systems.The seven sub-themes, community investment, long-ranging investment, the stability of production, the stability of the market, product information, liquidity and value creation showed moderate sustainability performance for both organic and conventional farming systems that fell between the scale 41% and 60%.

A lower sustainability performance was shown by internal investment and stability of supply for both organic and conventional farming systems that fell between the scale 21% and 40%.Food safety and local procurement showed the lowest sustainability performance between the scale 0%–20%, for both organic and conventional farming systems.Mean rank difference between the different farming systems based on the sub-themes of Economic resilience is shown in Table 3.Mean rank scores for the organic farming system ranged between 191.2 and 259.2.Mean rank scores for conventional farming system ranged between 186.6 and 202.0.The two cocoa farming systems differed significantly for most sub-themes with the exception of, community investment, long-ranging investment, the stability of production, the stability of supply, risk management, food safety, value creation and local procurement, where the p-values were above p = 0.05.Social well being sustainability performance is illustrated in Fig.5.Workplace safety and health provisions showed the highest sustainability performance between 60% and 80% for both organic and conventional cocoa farming systems.The lowest sustainability performance was shown by seven sub-themes, capacity development, rights of suppliers, forced labour, child labour, freedom of association and bargaining rights, non-discrimination and food sovereignty for both organic and conventional farming systems that fell between the scale 20% and 40%.Sustainability performance of fair access to means of production fell within the scales 21%–40% and 0%–20% for organic and conventional farming systems, respectively.Sustainability performance for gender equality and support to vulnerable people fell within the scales 61%–80% and 41%–60% for organic and conventional farming systems, respectively.The mean rank differences between the two farming systems within the sub-themes of Social well-being are shown in Table 4.Mean rank scores for the organic farming system ranged between 189.2 and 266.2.Mean rank scores for conventional farming system ranged between 185.0 and 201.7.

The two cocoa farming systems differed significantly for some subthemes with the exception of, quality of life, capacity development, fair access to means of production, responsible buyers, rights of suppliers, employment relations, forced labour, workplace safety and health provision, public health and food sovereignty, where the p-values were above p = 0.05.In a review of farming systems by Seufert & Ramankutty , they also concluded that overall farm sizes of organic production are smaller.The current study is consistent with a study by Seufert & Ramankutty who found that organic farming is labour intensive in terms of weeding.Overall, the organic cocoa farming system spends more labour hours per season on various cultural activities compared to conventional.The organic farming system requires more labour than conventional systems , especially for labour-intensive commodities, fruits, and tree crops.As suggested in the literature, organic can have positive effects on environmental outcomes.In the case study, a limited to good performance was found in the two cocoa farming systems, not only for the organic farming system.Indeed, the studied conventionally managed cocoa farms are characterised by low-input operations with low use of synthetic fertilisers and pesticides.The organic farms, on the other hand, use low or no organic inputs explaining the greenhouse gases scales of 61%–80% and 40%–60% for organic and conventional farming systems.Akrofi-Atitianti et al.also found low input use in Atwima Mponua District.Similarly, in Ethiopia, Winter et al.found a moderate to good environmental performance for conventional and certified coffee systems and attributed it to the low use of external inputs.Our analysis showed that the organic farming system is better in greenhouse gases emission reduction and in terms of improvement in air quality.According to Akrofi-Atitianti et al., a major driving force for an improved performance for organic in terms of greenhouse gases is the low or no use of inputs.Similar studies in Ecuador by Bonisoli et al.for banana cropping system is consistent with the findings.The finding is also verified by Fess and Benedito that organic farming promotes carbon sequestration and reduce greenhouse gas emissions.

Organic farming systems showed better water management practices, such as the treatment of waste water in terms of disposal or reuse, water storage capacity and the use of rainwater compared to the conventional farming system.Studies conducted by Bonisoli et al., Berbe´c et al.and De Olde et al.found a statistical difference between organic and conventional in Poland, Denmark, and Ecuador, respectively.We observed measures that reduce land degradation in organic farming system to be significantly higher compared to the conventional farming system.Other studies show that organic farming contributes to soil building and soil structure by improving the cation exchange capacity of soil biotic and physical properties.In our case study,mobile grow system organic farming systems are more diverse in terms of ecosystems, species and genetics compared to conventional.Those findings are consistent with Bandanaa et al.who found high flora diversity in organic cocoa farming system compared to conventional in the same geographic context.In terms of material use, energy use and waste reduction, the current study found the organic farming system to be significantly better in performance compared to conventional.The literature says organic farms tend to be more energy-efficient than conventional.Our results showed that in most sub-themes, the sustainability performance ranged from unacceptable to good performance for both organic and conventional cocoa farming systems.In many sub-themes such as, community investment, long-ranging investment, the stability of production, the stability of the market, product information, liquidity and value creation, the performance is moderate for both organic and conventional farming systems.Moderate performance exposes farmers of both cocoa farming systems to market shocks in terms of cocoa prices.In the case study, the organic market is not well established.Some farmers sell most of their organic beans as rain forest beans or conventional.This is because the premium obtained by selling organic beans is often delayed.Winter et al.also made similar observations for coffee farming systems in Ethiopia, as farmers sell their coffee to private buyers as conventional produce.

The mean difference between organic and conventional farming systems explained that six of the sub themes in organic were significantly different from conventional.Other empirical studies showed that organic farming is economically better than conventional in terms of investment.The organic farming system is more profitable than the conventional system due to price premiums, most especially so when the crops are grown for exports.The current study found in many sub-themes, such as “Internal Investment,” “Profitability,” and “Liquidity,” that organic farming system is significantly better than conventional.Though both cocoa farming systems are exposed to market shocks, organic cocoa farmers will always receive a premium on the cocoa beans either sold as organic or RA.Also, the organic farming system enhances food quality and product information compared to the conventional due to improved traceability.The social well being sustainability performance ranges from limited to good performance.The lowest sustainability performance of most sub-themes was labour related.In the case study, mostly family labour or hired labour is used in farm operations.Berlan verifies the finding on the use of family labour in cocoa production in Ghana but adds that, it is unacceptable if children are being involved in hazardous activities.Other studies in Nigeria confirms the use of family or hired labour in cocoa production and suggests sharecropping as a dominant labour option due to dishonesty and dedication of family/hired labour.Capacity development, forced labour, child labour, freedom of association and bargaining rights were among the lowest for both organic and conventional farming systems.Especially for child labour, there was no difference between the farming systems because children within the case study were not engaged in hazardous works.According to a U.S.Embassy-Accra, January 2020 report, there is low incidence of child labour in the cocoa sector due to the enforcement of child labor laws and the “conduct of national dialogue on Child Labor Free Zones in the cocoa industry”.The organic and conventional farming system mean rank scores for social well being showed significant differences for mostly labour related sub themes.The results for ‘Freedom of association’ and ‘right to bargaining’ suggest that organic farmers have access to more external labour and the workers bargaining rights.This finding is consistent with Giovannucci et al.study of certified coffee farming system in Kenya, Peru, Costa Rica, Honduras, and Nicaragua.With regards to gender equality, child labour, and support to vulnerable people, there is a significant trend in favour of organic farming system.Studies in Asante Bekwai, Atwima Mponua Districts and India have suggested that organic cocoa farming is a welfare and livelihood enhancer, and promotes gender equality in the workplace and encourages full participation for vulnerable in vibrant rural communities.The organic farming system performed significantly better compared to conventional in terms of indigenous knowledge since traditional and cultural knowledge used by farmers is protected.This is consistent with findings by Ssebunya et al.on coffee farming systems in Uganda and Schader et al.in Africa and Europe.The performance of both farming systems mostly ranges between the scale unacceptable and best performance for this dimension.The lowest sustainability performance was shown by the sub-themes’ mission statement’ and ‘legitimacy’ for both organic and conventional farming systems.Employment conditions on farms are not stable, explaining the low performance in legitimacy.Organic farmers are verbally committed to sustainability topics more than conventional, hence better performance in full cost accounting and mission statement.Similarly, Winter et al.found mission statements to score low among coffee farming systems in Ethiopia.This was explained as Ethiopian coffee farmers partial commitment to sustainability topics and their lack of evidence to show for specific planned improvements.