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 process-based 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.

生产中，强优势单果穗玉米品种通常拥有较高的产量潜力及资源利用效率。为了明确幼穗强、弱势差异分化的关键时期及内源激素在该时期的调控作用，本研究选用穗间强弱势差异显著的玉米品种苏玉41号 (单穗型，幼穗间强弱势差异显著和AN101(双穗型，幼穗间强弱势差异较小)，于2017和2018年在江苏大丰稻麦原种场进行试验。结果表明：弱势幼果穗发育较强势穗分化滞后，其滞后分化不仅与分化起始时间延后有关，还与其在小穗分化期和性器官形成期的持续时间延长有关。该时期强弱势幼穗间激素差异显著。从吐丝前12天开始到吐丝当日，吲哚-3-乙酸(IAA)，玉米素+玉米素核苷(ZR+ZT)和赤霉素(GA₃)的含量在两品种强、弱势幼穗内均先上升后急剧下降且在两品种间差异显著。脱落酸(ABA)则是在强、弱势幼穗内先缓慢上升，然后在苏玉41号中逐渐下降，在AN101中维持较高水平。吐丝前8天是形态上强弱势分化的关键时期，此时上位幼穗(强势穗)处于小花分化到性器官形成的过渡期。此期，在苏玉41中强、弱势幼穗日生长量差值、IAA、(ZR+ZT)和GA₃含量差值均高于AN101。同时，苏玉41号强、弱势间IAA比值及(ZR+ZT)比值均要高于AN101，而GA₃和ABA则无明显差异。强、弱势幼穗间日生长量差值及内源激素差值的相关性分析表明内源激素在调控幼穗强、弱势差异分化中的作用存在差异。本研究结果表明，弱势果穗的滞后发育及其完成小穗分化和性器官形成时间过长有关；IAA和ZR+ZT在此过程中发挥重要调控作用，GA₃似乎在更早时期参与强、弱势幼穗分化，而ABA未能观察到在此过程中发挥重要作用。

Two cotton (Gossypium hirsutum L.) cultivars, Kemian 1 (cool temperature-tolerant) and Sumian 15 (cool temperature-sensitive) were used to study the effects of cool temperature on carbohydrates, yield, and fiber quality in cotton bolls located at different fruiting positions (FP).  Cool temperatures were created using late planting and low light.  The experiment was conducted in 2010 and 2011 using two planting dates (OPD, the optimized planting date, 25 April; LPD, the late planting date, 10 June) and two shading levels of crop relative light rate (CRLR, 100 and 60%).  Compared with fruiting position 1 (FP1), cotton yield and yield components (fiber quality, leaf sucrose and starch content, and fiber cellulose) were all decreased on FP3 under all treatments.  Compared with OPD-CRLR 100%, other treatments (OPD-CRLR 60%, LPD-CRLR 100%, and LPD-CRLR 60%) had significantly decreased lint yield at both FPs of both cultivars, but especially at FP3 and in Sumian 15; this decrease was mainly caused by a large decline in boll number.  All fiber quality indices decreased under late planting and shading except fiber length at FP1 with OPD-CRLR 60%, and a greater reduction was observed at FP3 and in Sumian 15.  Sucrose content of the subtending leaf and fiber increased under LPD compared to OPD, whereas it decreased under CRLR 60% compared to CRLR 100%, which led to decreased fiber cellulose content.  Therefore, shading primarily decreased the “source” sucrose content in the subtending leaf whereas late planting diminished translocation of sucrose towards cotton fiber.  Notably, as planting date was delayed and light was decreased, more carbohydrates were distributed to leaf and bolls at FP1 than those at FP3, resulting in higher yield and better fiber quality at FP1, and a higher proportion of bolls and carbohydrates allocated at FP3 of Kemian 1 compared to that of Sumian 15.  In conclusion, cotton yield and fiber quality were reduced less at FP1 compared to those at FP3 under low temperature and low light conditions.  Thus, reduced cotton yield and fiber quality loss can be minimized by selecting low temperature tolerant cultivars under both low temperature and light conditions.

    The development of the cotton fiber is very sensitive to temperature variation, and high temperature stress often causes reduced fiber yield and fiber quality.  Short-term high temperature stress often occurs during cotton production, but little is known about the specific timing and duration of stress that affects fiber development.  To make this clear, pot experiments were carried in 2014 and 2015 in a climate chamber using cotton cultivars HY370WR (less sensitive variety) and Sumian 15 (heat sensitive variety), which present different temperature sensitivities.  Changes of the most important fiber quality indices (i.e., fiber length, fiber strength and marcironaire) and three very important fiber development components (i.e., cellulose, sucrose and callose) were analyzed to define the time window and critical duration to the high temperature stress at 34°C (max38°C/min30°C).  When developing bolls were subjected to 5 days of high temperature stress at different days post-anthesis (DPA), the changes (Δ%) of fiber length, strength and micronire, as a function of imposed time followed square polynomial eq. as y=a+bx+cx2, and the time around 15 DPA was the most sensitive period for fiber quality development in response to heat stress.  When 15 DPA bolls were heat-stressed for different durations (2, 3, 4, 5, 6, 7 days), the changes (Δ%) of fiber length, strength and micronire, as a function of stress duration followed logistic equations .  Referred to that 5, 10 and 15% are usually used as criteria to decide whether techniques are effective or changes are significant in crop culture practice and reguard to the fiber quality indices change range, we suggested that 5% changes of the major fiber quality indices (fiber length, fiber strength and micronaire) and 10% changes of fiber development components (cellulose, sucrose and callose) could be taken as criteria to judge whether fiber development and fiber quality have been significantly affected by high temperature stress.  The key time window for cotton fiber development in response to the high temperature stress was 13–19 DPA, and the critical duration was about 5 days.

    With increased cultivation of transgenic Bacillus thuringiensis (Bt) cotton in the saline alkaline soil of China, assessments of transgenic crop biosafety have focused on the effects of soil salinity on rhizosphere microbes and Bt protein residues. In 2013 and 2014, investigations were conducted on the rhizosphere microbial biomass, soil enzyme activities and Bt protein contents of the soil under transgenic Bt cotton (variety GK19) and its parental non-transgenic cotton (Simian 3) cultivated at various salinity levels (1.15, 6.00 and 11.46 dS m⁻¹). Under soil salinity stress, trace amounts of Bt proteins were observed in the Bt cotton GK19 rhizosphere soil, although the protein content increased with cotton growth and increased soil salinity levels. The populations of slight halophilic bacteria, phosphate solubilizing bacteria, ammonifying bacteria, nitrifying bacteria and denitrifying bacteria decreased with increased soil salinity in the Bt and non-Bt cotton rhizosphere soil, and the microbial biomass carbon, microbial respiration and soil catalase, urease and alkaline phosphatase activity also decreased. Correlation analyses showed that the increased Bt protein content in the Bt cotton rhizosphere soil may have been caused by the slower decomposition of soil microorganisms, which suggests that salinity was the main factor influencing the relevant activities of the soil microorganisms and indicates that Bt proteins had no clear adverse effects on the soil microorganisms. The results of this study may provide a theoretical basis for risk assessments of genetically modified cotton in saline alkaline soil.

A two-year field experiment was conducted to illustrate the effects of sowing date on cottonseed properties at different fruiting-branch positions (FBPs).  Two cotton cultivars (Kemian 1 and Sumian 15) were sowed on 25 April, 25 May, and 10 June in 2010 and 2011, respectively.  The boll maturation period increased with the delaying of sowing date.  Normal sowing treatment (25 April) had higher seed weight, embryo weight, embryo oil content and protein content than late sowing treatments (25 May and 10 June).  The flowering date, seed weight, embryo weight, embryo oil and protein contents, and the dynamic changes of embryo oil and protein contents were altered by different FBPs.  A significant interaction of sowing date×FBP was observed on embryo weight, embryo oil content, embryo protein content and the dynamic changes of embryo oil and protein contents, but was not observed on seed weight.  Seed weight, embryo weight, embryo oil and protein content had significant positive correlations with the mean daily temperature (MDT), mean daily maximum temperature (MDT_max), mean daily minimum temperature (MDT_min), and mean daily solar radiation (MDSR), indicating that temperature and light resources were the main reasons for different sowing dates affecting the cottonseed properties at different FBPs.  Moreover, the difference in MDT was the main difference in climatic factors among different sowing dates.

In the process to the marketing of cultivars, identification of superior test locations within multi-environment variety trial schemes is of critical relevance. It is relevant to breeding organizations as well as to governmental organizations in charge of cultivar registration. Where competition among breeding companies exists, effective and fair multi-environment variety trials are of utmost importance to motivate investment in breeding. The objective of this study was to use genotype main effect plus genotype by environment interaction (GGE) biplot analysis to evaluate test locations in terms of discrimination ability, representativeness and desirability, and to investigate the presence of multiple mega-environments in cotton production in the Yangtze River Valley (YaRV), China. Four traits (cotton lint yield, fiber length, lint breaking tenacity, micronaire) and two composite selection indices were considered. It was found that the assumption of a single mega-environment in the YaRV for cotton production does not hold. The YaRV consists of three cotton mega-environments: a main one represented by 11 locations and two minor ones represented by two test locations each. This demands that the strategy of cotton variety registration or recommendation must be adjusted. GGE biplot analysis has also led to the identification of test location superior for cotton variety evaluation. Although test location desirable for selecting different traits varied greatly, Jinzhou, Hubei Province, China, was found to be desirable for selecting for all traits considered while Jianyang, Sichuan Province, China, was found to be desirable for none.

Nitrogen (N) fertilizer experiments were conducted to investigate the optimal subtending leaf N concentration for fiber strength, and its relationship with activities of key enzymes (sucrose synthase and β-1,3-glucanase) and contents of key constituents (sucrose and β-1,3-glucan) involved in fiber strength development in the lower, middle and upper fruiting branches of two cotton cultivars (Kemian 1 and NuCOTN 33B). For each sampling day, we simulated changes in fiber strength, activity of sucrose synthase and β-1,3-glucanase and levels of sucrose and β-1,3-glucan in response to leaf N concentration using quadratic eqs.; the optimal subtending leaf N concentrations were deduced from the eqs. For the same fruiting branch, changes in the optimal leaf N concentration based on fiber development (DPA) could be simulated by power functions. From these functions, the average optimal subtending leaf N concentrations during fiber development for the cultivar, Kemian 1, were 2.84% in the lower fruiting branches, 3.15% in the middle fruiting branches and 3.04% in the upper fruiting branches. For the cultivar, NuCOTN 33B, the optimum concentrations were 3.04, 3.28 and 3.18% in the lower, middle and upper fruiting branches, respectively. This quantification may be used as a monitoring index for evaluating fiber strength and its related key enzymes and constituents during fiber formation at the lower, middle and upper fruiting branches.

Crop performance is determined by the combined effects of the genotype of the crop and the environmental conditions of the production system. This study was undertaken to develop a dynamic model for simulating environmental (temperature and solar radiation) and N supply effects on fiber fineness, maturity and micronaire. Three different experiments involving genotypes, sowing dates, and N fertilization rates were conducted to support model development and model evaluation. The growth and development duration of fiber fineness, maturity, and micronaire were scaled by using physiological development time of secondary wall synthesis (PDTSWSP), which was determined based on the constant ratio of SWSP/ BMP. PTP (product of relative thermal effectiveness (RTE) and photosynthetically active radiation (PAR), MJ m-2) and subtending leaf N content per unit area (NA, g m-2) and critical subtending leaf N content per unit area (CNA, g m-2) of cotton boll were calculated or simulated to evaluate effects of temperature and radiation, and N supply. Besides, the interactions among temperature, radiation and N supply were also explained by piecewise function. The overall performance of the model was calibrated and validated with independent data sets from three field experiments with two sowing dates, three or five flowering dates and three or four N fertilization rates for three subsequent years (2005, 2007, and 2009) at three ecological locations. The average RMSE and RE for fiber fineness, maturity, and micronaire predictions were 372 m g-1 and 5.0%, 0.11 m g-1 and 11.4%, 0.3 m g-1 and 12.3%, respectively, indicating a good fit between the simulated and observed data. It appears that the model can give a reliable prediction for fiber fineness, maturity and micronaire formation under various growing conditions.

This experiments were conducted in Nanjing (118º50´E, 32º02´N) and Xuzhou (117°11´E, 34°15´N), Jiangsu Province, China, to study the response of fiber quality to the N concentration of the leaf subtending boll in cotton (Gossypium hirsutum L.). Results suggested that the N dilution curve of the leaf subtending boll can accurately indicate the stagespecific plant N status for fiber development. Fiber strength is likely to be the most variable fiber quality index responding to the leaf N variation which is different in cultivars. Fiber length was the most stable index among strength, length, micronaire, and elongation. There existed an optimum leaf N concentration for fiber strength development in each stage. The optimum leaf N regression curve was very close to the N dilution curve in the middle positional fruiting branches under the 240 kg N ha-1 soil N application rate.