Sustainability Assessment of Banana (Musa spp.) Yield Gap Reduction through Value Chain Development Interventions in Smallholder Farming Systems in Manicaland, Zimbabwe

This study evaluated the effectiveness of donor supported agricultural value chain development projects in sustainably narrowing yield gaps for banana smallholder farmer producers in Manicaland, Zimbabwe. The study used a mixed methods research design that relied on farmers records for the quantitative analysis and focus group discussion and in-depth interviews for key experts for the qualitative aspects. A mix of regression analysis, t-tests, Pearsons’s correlation and analysis of variance statistical methods were used for the quantitative analysis while thematic response analysis was used for the qualitative engagements. The findings showed that by the end of the activity, the project had successfully narrowed the banana yield gaps to 18.66 tons per hectare working with a potential yield base of 40 tons. However, 5 years after the project closure the yield gap had fallen to 24.7 tons indicating a lack of sustainability of yield gap reduction. However, the yield gap slump does not override the fact that farmers on average were still able to sell approximately 5 tons per every 6 months after 5 years from the project closure which is beyond any poverty threshold. This suggests genuine upward economic mobility. Additionally, in analyzing what factors had the greatest influence on yield gap reduction, the access to fertilizer ranked highest where genetics, irrigation and improved agronomy followed in that respective order. The study further showed that farmers who receive value chain development support whilst at an already commercialized state tend to maintain productivity thresholds higher in comparison to those who are at a pre commercial state. This is evidenced by the fact that the pre commercial farmers had a yield reduction of 30.83 percent after 5 years of the project closure whereas the former realized a productivity growth of 7.84%. In conclusion, whilst the intervention was successful in transitioning farmers out of poverty, more investment should be made towards transitioning smallholder farmers to integrated soil fertility management practices and improvement of agronomic efficiency through stronger on field collaboration between research institutions, the government and development institutions.

Towards sustainable intensification of apple production in China—Yield gaps and nutrient use effi ciency in apple farming systems

China is in a dominant position in apple production globally with both the largest apple growing area and the largest export of fresh apple fruits. However, the annual productivity of China＇s apple is significantly lower than that of other dominant apple producing countries. In addition, apple production is based on excessive application of chemical fertilizers and the nutrient use efficiency （especially nitrogen） is therefore low and the nutrient emissions to the environment are high. Apple production in China is considerably contributes to farmers＇ incomes and is important as export product. There is an urgent need to enhance apple productivity and improve nutrient use efficiencies in intensive apple production systems in the country. These can be attained by improved understanding of production potential, yield gaps, nutrient use and best management in apple orchards. To the end, priorities in research on apple production systems and required political support are described which may lead to more sustainable and environmental-friendly intensification of apple production in China.

Potato yield gaps across the rainfed Yin-mountain Hilly Area of China

Yin-mountain Hilly Area is one of the ideal regions for potato （Solanum tuberosum） production in China. However, potato yield is severely limited as a result of rain-fed crop mode due to water deficiency, as well as an inadequate farming practices. In this study, yield gaps were determined by using attainable yield （Ya） as a benchmark under optimized management practices, i.e., micro-ridge and side planting with plastic-mulching （MS）, and flat planting with plastic-mulching （PM）. The yields under MS and PM modes are defined as Yal and Ya2, respectively. Under the same field with MS and PM modes but different densities and fertilizer usages and so on, it was defined as simulated farmers＇ practices. The yield of simulated farmers＇ practices （Yfl） reached 57.3 and 69.6% of Yal and Ya2, respectively, while the average yield of 298 randomly surveyed farmers （Yf2） reached only 37.0 and 47.8% of Yal and Ya2 for rain-fed potato, respectively. The gaps of water use efficiency exhibited similar pattern. Further analysis shows that improper measures in rainwater conservation and accumulation, and other management practices contributed to 18.5, 18.2, and 42.6% of yield gap between Yal and Yf2. Improper nutrition management, including overuse of nitrogen and the deficiency of phosphorus andpotassium supplication, was one of the important reasons of yield gap. The results indicate the possibilities of increasing rain-fed potato yields by optimized water and fertilizermanagements in the Yin-mountain Hilly Area.

Modelling the crop yield gap with a remote sensing-based process model:A case study of winter wheat in the North China Plain

Understanding the spatial distribution of the crop yield gap(YG)is essential for improving crop yields.Recent studies have typically focused on the site scale,which may lead to considerable uncertainties when scaled to the regional scale.To mitigate this issue,this study used a process-based and remote sensing driven crop yield model for winter wheat(PRYM-Wheat),which was derived from the boreal ecosystem productivity simulator(BEPS),to simulate the YG of winter wheat in the North China Plain from 2015 to 2019.Yield validation based on statistical yield data revealed good performance of the PRYM-Wheat Model in simulating winter wheat actual yield(Ya).The distribution of Ya across the North China Plain showed great heterogeneity,decreasing from southeast to northwest.The remote sensing-estimated results show that the average YG of the study area was 6400.6 kg ha^(–1).The YG of Jiangsu Province was the largest,at7307.4 kg ha^(–1),while the YG of Anhui Province was the smallest,at 5842.1 kg ha^(–1).An analysis of the responses of YG to environmental factors showed no obvious correlation between YG and precipitation,but there was a weak negative correlation between YG and accumulated temperature.In addition,the YG was positively correlated with elevation.In general,studying the specific features of the YG can provide directions for increasing crop yields in the future.

Quantifying the spatial variation in the potential productivity and yield gap of winter wheat in China

Despite the improvement in cultivar characters and management practices, large gaps between the attainable and potential yields still exist in winter wheat of China. Quantifying the crop potential yield is essential for estimating the food production capacity and improving agricultural policies to ensure food security. Gradually descending models and geographic infor- mation system （GIS） technology were employed to characterize the spatial variability of potential yields and yield gaps in winter wheat across the main production region of China. The results showed that during 2000-2010, the average potential yield limited by thermal resource （YGT） was 23.2 Mg ha-1, with larger value in the northern area relative to the southern area. The potential yield limited by the water supply （YGw） generally decreased from north to south, with an average value of 1.9 Mg ha-1 across the entire study region. The highest YGw in the north sub-region （NS） implied that the irrigation and drainage conditions in this sub-region must be improved. The averaged yield loss of winter wheat from nutrient deficiency （YGH） varied between 2.1 and 3.1 Mg ha-1 in the study area, which was greater than the yield loss caused by water limitation. The potential decrease in yield from photo-thermal-water-nutrient-limited production to actual yield （YGo） was over 6.0 Mg ha-1, ranging from 4.9 to 8.3 Mg ha^-1 across the entire study region, and it was more obvious in the southern area than in the northern area. These findings suggest that across the main winter wheat production region, the highest yield gap was induced by thermal resources, followed by other factors, such as the level of farming technology, social policy and economic feasibility. Furthermore, there are opportunities to narrow the yield gaps by making full use of climatic resources and developing a reasonable production plan for winter wheat crops. Thus, meeting the challenges of food security and sustainability in the coming decades is possible but will require considerable changes in water and nutrient management and socio-economic policies.

Reducing maize yield gap by matching plant density and solar radiation

Yield gap exists because the current attained actual grain yield cannot yet achieve the estimated yield potential. Chinese high yield maize belt has a wide span from east to west which results in different solar radiations between different regions and thus different grain yields. We used multi-site experimental data, surveyed farmer yield data, the highest recorded yield data in the literatures, and simulations with Hybrid-Maize Model to assess the yield gap and tried to reduce the yield gap by matching the solar radiation and plant density. The maize belt was divided into five regions from east to west according to distribution of accumulated solar radiation. The results showed that there were more than 5.8 Mg ha^(–1) yield gaps between surveyed farmer yield and the yield potential in different regions of China from east to west, which just achieved less than 65% of the yield potential. By analyzing the multi-site density experimental data, we found that the accumulated solar radiation was significantly correlated to optimum plant density which is the density with the highest yield in the multi-site density experiment(y=0.09895 x–32.49, P<0.01), according to which the optimum plant densities in different regions from east to west were calculated. It showed that the optimum plant density could be increased by 60.0, 55.2, 47.3, 84.8, and 59.6% compared to the actual density, the grain yield could be increased by 20.2, 18.3, 10.9, 18.1, and 15.3% through increasing plant density, which could reduce the yield gaps of 33.7, 23.0, 13.4, 17.3, and 10.4% in R(region)-1, R-2, R-3, R-4, and R-5, respectively. This study indicates that matching maize plant density and solar radiation is an effective approach to reduce yield gaps in different regions of China.

Yield gap and resource utilization efficiency of three major food crops in the world——A review

Yield gap analysis could provide management suggestions to increase crop yields,while the understandings of resource utilization efficiency could help judge the rationality of the management.Based on more than 110 published papers and data from Food and Agriculture Organization (FAO,www.fao.org/faostat) and the Global Yield Gap and Water Productivity Atlas (www.yieldgap.org),this study summarized the concept,quantitative method of yield gap,yield-limiting factors,and resource utilization efficiency of the three major food crops (wheat,maize and rice).Currently,global potential yields of wheat,maize and rice were 7.7,10.4 and 8.5 t ha^(–1),respectively.However,actual yields of wheat,maize and rice were just 4.1,5.5 and 4.0 t ha^(–1),respectively.Climate,nutrients,moisture,crop varieties,planting dates,and socioeconomic conditions are the most mentioned yield-limiting factors.In terms of resource utilization,nitrogen utilization,water utilization,and radiation utilization efficiencies are still not optimal,and this review has summarized the main improvement measures.The current research focuses on quantitative potential yield and yield gap,with a rough explanation of yield-limiting factors.Subsequent research should use remote sensing data to improve the accuracy of the regional scale and use machine learning to quantify the role of yield-limiting factors in yield gaps and the impact of change crop management on resource utilization efficiency,so as to propose reasonable and effective measures to close yield gaps.

A new feasible method for yield gap analysis in regions dominanted by smallholder farmers, with a case study of Jiangsu Province, China

In the regions where crops were mostly produced by smallholder farmers, the analysis of yield gap is difficult due to diverse cultivars, crop managements and yield levels. In order to find an effective method that can reasonably verify the yield gap and the limiting cultivation factors in narrowing yield gaps in areas that are dominanted by smallholder farmers, we worked out a method consisting five progressive procedures as follows: questionnaire investigation of farmer cultivation regime, identification of yield levels and yield gaps, generalization of key cultivation measurements, reconstruction of representative maize populations, and process-based analysis of yield gap. A case study was carried out in Jiangsu Province, China, in which maize is mostly produced by smallholder farmers. A questionnaire investigation of 1 023 smallholder farmers was carried out firstly, then the frequency distribution of maize yield was simulated by an normal distribution function, and then the covering range and average value of the basic yield, farmer yield and high-yield farmer yield levels were calculated out from the equation. Hereby, the yield gaps 1, 2 and 3 were calculated along with the record highest yield from literature and experts, which were 2 564, 2 346 and 2 073 kg ha^(–1), respectively. Moreover, with the covering range of each yield level, the suveyed farmers belonging to each yield level were grouped together and then their major cultivation measures were traced and generalized. With the generalized cultivation measures, representative maize populations of the four yield levels were reconstructed, and thereby clarifing lots of characters of the populations or single plant of each population with processbased analysis of the reconstructed populations. In this case, the main factors causing the yield gap were plant density, fertilizer application rate, logging caused by hurricane, and damages caused by pests. The case study primarily indicated that this five-step method is feasible and effective in yield gap study, especially in smallholder farmers dominant regions.

The effect of solar radiation change on the maize yield gap from the perspectives of dry matter accumulation and distribution

The uneven distribution of solar radiation is one of the main reasons for the variations in the yield gap between different regions in China and other countries of the world.In this study,different solar radiation levels were created by shading and the yield gaps induced by those levels were analyzed by measuring the aboveground and underground growth of maize.The experiments were conducted in Qitai,Xinjiang,China,in 2018 and 2019.The maize cultivars Xianyu 335 (XY335)and Zhengdan 958 (ZD958) were used with planting density of 12×10^(4) plants ha^(–1) under either high solar radiation (HSR)or low solar radiation (LSR,70%of HSR).The results showed that variation in the solar radiation resulted in a yield gap and different cultivars behaved differently.The yield gaps of XY335 and ZD958 were 8.9 and 5.8 t ha^(–1) induced by the decreased total intercepted photosynthetically active radiation (TIPAR) of 323.1 and 403.9 MJ m^(–2) from emergence to the maturity stage,respectively.The average yield of XY335 was higher than that of ZD958 under HSR,while the average yield of ZD958 was higher than that of XY335 under LSR.The light intercepted by the canopy and the photosynthetic rates both decreased with decreasing solar radiation.The aboveground dry matter decreased by 11.1% at silking and 21% at maturity,and the dry matter of vegetative organs and reproductive organs decreased by 9.8 and 20.9%at silking and by 12.1 and 25.5% at physiological maturity,respectively.Compared to the HSR,the root weights of XY335 and ZD958 decreased by 54.6 and 45.5%,respectively,in the 0–60 cm soil layer under LSR at silking stage.The aboveground and underground growth responses to different solar radiation levels explained the difference in yield gap.Selecting suitable cultivars can increase maize yield and reduce the yield gaps induced by variation of the solar radiation levels in different regions or under climate change.

The priority of management factors for reducing the yield gap of summer maize in the north of Huang-Huai-Hai region, China

Understanding yield potential, yield gap and the priority of management factors for reducing the yield gap in current intensive maize production is essential for meeting future food demand with the limited resources. In this study, we conducted field experiments using different planting modes, which were basic productivity(CK), farmer practice(FP), high yield and high efficiency(HH), and super high yield(SH), to estimate the yield gap. Different factorial experiments(fertilizer, planting density, hybrids, and irrigation) were also conducted to evaluate the priority of individual management factors for reducing the yield gap between the different planting modes. We found significant differences between the maize yields of different planting modes. The treatments of CK, FP, HH, and SH achieved 54.26, 58.76, 65.77, and 71.99% of the yield potential, respectively. The yield gaps between three pairs: CK and FP, FP and HH, and HH and SH, were 0.76, 1.23 and 0.85 t ha^(–1), respectively. By further analyzing the priority of management factors for reducing the yield gap between FP and HH, as well as HH and SH, we found that the priorities of the management factors(contribution rates) were plant density(13.29%)>fertilizer(11.95%)>hybrids(8.19%)>irrigation(4%) for FP to HH, and hybrids(8.94%)>plant density(4.84%)>fertilizer(1.91%) for HH to SH. Therefore, increasing the planting density of FP was the key factor for decreasing the yield gap between FP and HH, while choosing hybrids with density and lodging tolerance was the key factor for decreasing the yield gap between HH and SH.

Determination of soybean yield gap and potential production in Iran using modeling approach and GIS

Increasing crop production is necessary to maintain food security for the growing global population.Reducing the gap between actual and potential yield is one of the important ways to increase yield per unit area.Potential yield and the yield gap of soybean were determined for Golestan Province,Iran,using Soybean Simulation Model (SSM-i Crop2) and Geographical Information System (GIS).Information from 24 weather stations and soil data of the region were used.Yield gap and production gap were calculated at county and province levels.The average actual yield of soybean in this province was2.28 t ha^(–1) while the province’s potential yield was 4.73 t ha^(–1),so the yield gap was estimated 2.44 t ha^(–1).Thus,there is a great potential for increasing soybean yield in Golestan,which is possible through improving crop management of soybean in farmers’fields.The average water productivity of soybean was estimated to be 0.81 kg m^(–3).Spatial distribution of water productivity in soybean farms showed that the highest and the lowest water productivities (0.99 and 0.44 kg m^(–3)) were in western and eastern regions of the province,respectively,in accordance to vapour pressure deficit.It was concluded that soybean production in the province could increase by 66%(from 109 970 to 182 170 tons) if 80% of the current yield gap could be removed.

Effects of different agricultural treatments on narrowing winter wheat yield gap and nitrogen use efficiency in China

Under the limited cultivated land area and the pursuit of sustainable agricultural development,it is essential for the safety of grain production to study agricultural management approaches on narrowing the winter wheat yield gap and improving nitrogen use efficiency (NUE) in China.In this study,DSSAT-CERES-Wheat Model is used to simulate winter wheat yield under different agricultural treatments,and we analyze yield gaps and NUE with different management scenarios at regional scales and evaluate the suitable approaches for reducing yield gap and increasing NUE.The results show that,the potential of narrowing yield gap ranges 300–900 kg ha^(–1) with soil nutrients increase,400–1 200 kg ha^(–1) with sowing date adjustment and 0–400 kg ha^(–1) with planting density increase as well as 700–2 200 kg ha^(–1) with adding nitrogen fertilizer.Contribution rates of management measures of soil nutrients,sowing date adjusting,planting density,and nitrogen fertilizers are 5–15%,5–15%,0–4%,and 10–20%,respectively.Difference in nitrogen partial productivity ranges 3–10 kg kg^(–1) for soil nutrients,1–10 kg kg^(–1) for sowing date adjusting,1–5 kg kg^(–1) for planting density increase,and–12–0 kg kg^(–1) for adding nitrogen fertilizers,respectively.It indicates that four treatments can narrow yield gap and improve the NUE in varying degrees,but increasing nitrogen fertilizer leads to the decrease of NUE.

Detecting the linkage between arable land use and poverty using machine learning methods at global perspective

Eradicating extreme poverty is one of the UN’s primary sustainable development goals(SDG).Arable land is related to eradicating poverty(SDG1)and hunger(SDG2).However,the linkage between arable land use and poverty reduction is ambiguous and has seldom been investigated globally.Six indicators of agricultural inputs,crop intensification and extensification were used to explore the relationship between arable land use and poverty.Non-parametric machine learning methods were used to analyze the linkage between agriculture and poverty at the global scale,including the classification and regression tree(CART)and random forest models.We found that the yield gap,fertilizer consumption and potential cropland ratio in protected areas correlated with poverty.Developing countries usually had a ratio of actual to potential yield less than 0.33 and fertilizer consumption less than 7.31 kg/ha.Overall,crop extensification,intensification and agricultural inputs were related to poverty at the global level.

Production potential and yield gaps of summer maize in the Beijing-Tianjin-Hebei Region

Crop potential productivity is a key index of scientifically appraising crop production and land population-supporting capacity. This study firstly simulated the potential and waterlimited yield of summer maize in the Beijing-Tianjin-Hebei （BTH） region using WOFOST model with meteorological data of 40 years, and then analyzed yield gaps between the actual and potential yield based on statistical data at county level. The potential and water-limited yield of summer maize in the BTH region is 6854–8789 kg/hm2 and 6434–8741 kg/hm2, and the weighted average for whole region is 7861 kg/hm2 and 7185 kg/hm2, respectively. The simulated yields gradually decrease from northeast to southwest with changes in climatic conditions particularly temperature and precipitation. Annual variation of potential yield is higher in the central and southern parts than the northeastern part. Compared to potential yield, the water-limited yield has higher coefficient of variation （CV）, because of precipitation effects. The actual yield of summer maize was 2537–8730 kg/hm2, regionally averaged at 5582 kg/hm2, about 70% of the potential yield, implying that the region has room to increase the yield by improving crop management and irrigation systems.

Simulating potential yields of Chinese super hybrid rice in Bangladesh,India and Myanmar with EPIC model

In this study, information is collected on the weather, soils, field management and agricultural statistics in the Bangladesh, India and Myanmar（BIM） region. Crop growth parameters within the EPIC（Environmental Policy Integrated Climate） model are calibrated using cultivar data and regional experimental records of indica hybrid rice Fyou498 and Fengliangyou4 in China. Potential yields of rice are then simulated in the BIM region from 1996 to 2005. The effects of local irrigation and fertilization levels on super hybrid rice yield are examined. The potential yields of Chinese hybrid rice at local irrigation and fertilization levels in 2000 and at full irrigation and rational fertilization levels are found to be 10.22 t/ha and 11.33 t/ha, respectively. The potential for increasing monsoon rice production in the study region is 227.71 million tons. The eastern Indo-Gangetic Plain in India, the southeast coast of India Peninsula and the Ayeyarwady Delta in Myanmar have the largest potentials for monsoon rice production. The northeastern and southwestern areas of the Deccan Plateau and the northwestern region of the Indo-Gangetic Plain need to improve irrigation equipment to meet the water-use requirements of high-yield rice. The central and southern plains in Myanmar and northeastern India need greater access to nitrogen fertilization for high-yield rice.

PLANT DENSITY,IRRIGATION AND NITROGEN MANAGEMENT:THREE MAJOR PRACTICES IN CLOSING YIELD GAPS FOR AGRICULTURAL SUSTAINABILITY IN NORTH-WEST CHINA

Agriculture faces the dual challenges of food security and environmental sustainability.Here,we investigate current maize production at the field scale,analyze the yield gaps and impacting factors,and recommend measures for sustainably closing yield gaps.An experiment was conducted on a 3.9-ha maize seed production field in arid north-west China,managed with border and drip irrigation,respectively,in 2015 and 2016.The relative yield reached 70%in both years.However,drip irrigation saved 227 mm irrigation water during a drier growing season compared with traditional border irrigation,accounting for 44%of the maize evapotranspiration(ET).Yield variability under drip irrigation was12.1%,lower than the 18.8%under border irrigation.Boundary line analysis indicates that a relative yield increase of 8%to 10%might be obtained by optimizing the yield-limiting factors.Plant density and soil available water content and available nitrogen were the three major factors involved.In conclusion,closing yield gaps with agricultural sustainability may be realized by optimizing agronomic,irrigation and fertilizer management,using water-saving irrigation methods and using site-specific management.

Heat units-based potential yield assessment for cotton production in Uzbekistan

Cotton yields in Uzbekistan are significantly lower than those in similar agro-climatic regions,requiring the estimation of crop potential and baseline yield to track progress of production enhancement efforts.The current study estimated potential cotton development and baseline yield(maximum given no production constraints)using total heat units(THU)and potential cotton yield(PCY),respectively.Calculations were based on heat units(HU)for a 30-year(1984-2013)period.Long-term average THU and PCY,as well as PCY at three different exceedance probabilities(p=0.99,p=0.80,and p=0.75),were calculated for 21 selected weather stations across cotton-growing areas of Uzbekistan.After confirmation that the current planting date(April 15)is optimal,a comparison of THU with the accepted cotton production cutoff threshold(1444°C)suggested that areas with lower elevations and latitudes are more appropriate for cotton production.Yield gap analysis(relative difference between long-term average PCY and actual yields)confirmed that Uzbekistan cotton production is below potential,while the spatial distribution of yield gaps outlined where efforts should be targeted.Areas near the stations of Nukus,Kungrad,Chimbay,and Syrdarya should be further investigated as benefit/cost ratio is highest in these areas.A comparison between state-set yield targets and PCY values,taking into account climatic variability,suggested that all areas except Jaslyk,Nurata,and Samarkand have safe,appropriate targets.These results present a starting-point to aid in strategic actions for Uzbekistan cotton production improvement.