Identifying and selecting high-quality seeds is crucial for improving crop yield.  The purpose of this study was to improve the selection of crop seeds based on separating vital seeds from dead seeds, by predicting the potential germination ability of each seed, and thus improving seed quality.  The methods of oxygen consumption (Q) of seeds and the headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) were evaluated for identifying the viability of individual seeds.  Firstly, the oxygen consumption technique showed clear differences among the values related to respiratory characteristics for seeds that were either vital or not, and the discrimination ability of final oxygen consumption (Q₁₂₀) was achieved not only in sweet corn seeds but also in pepper and wheat seeds.  Besides, Q_t was established as a new variable to shorten the measuring process in the Q2 (oxygen sensor) procedure, which was significantly related to the viability of individual seeds.  To minimize seed damage during measurement, the timing for viability evaluation was pinpointed at the 12, 6 and 9 h for pepper, sweet corn, and wheat seeds based on the new variables concerning oxygen consumption (i.e., Q₁₂, Q₆ and Q₉, respectively).  The accuracies of viability prediction were 91.9, 97.7 and 96.2%, respectively.  Dead seeds were identified and hence discarded, leading to an enhancement in the quality of the seed lot as indicated by an increase in germination percentage, from 86.6, 90.9, and 53.8% to all at 100%.  We then used the HS-GC-IMS to determine the viability of individual sweet corn seeds, noting that corn seed has a heavier weight so the volatile gas components are more likely to be detected.  A total of 48 chromatographic peaks were identified, among which 38 target compounds were characterized, including alcohols, aldehydes, acids and esters.  However, there were no significant differences between the vital and dead seeds, due to the trace amount volatile composition differences among the individual seeds.  Furthermore, a PCA based on the signal intensities of the target volatile compounds obtained was found to lose its effectiveness, as it was unable to distinguish those two types of sweet corn seeds.  These strategies can provide a reference for the rapid detection of single seed viability.

One of the most important objectives for breeders is to develop high-yield cultivars.  The increase in crop yield has met with bottlenecks after the first green revolution, and more recent efforts have been focusing on achieving high photosynthetic efficiency traits in order to enhance the yield.  Leaf shape is a significant agronomic trait of upland cotton that affects plant and canopy architecture, yield, and other production attributes.  The major leaf shape types, including normal, sub-okra, okra, and super-okra, with varying levels of lobe severity, are controlled by a multiple allelic series of the D-genome locus L-D₁.  To analyze the effects of L-D₁ alleles on leaf morphology, photosynthetic related traits and yield of cotton, two sets of near isogenic lines (NILs) with different alleles were constructed in Lumianyan 22 (LMY22) and Lumianyan 28 (LMY28) backgrounds.  The analysis of morphological parameters and the results of virus-induced gene silencing (VIGS) showed that the regulation of leaf shape by L-D₁ alleles was similar to a gene-dosage effect.  Compared with the normal leaf, deeper lobes of the sub-okra leaf improved plant canopy structure by decreasing the leaf area index (LAI) and increasing the light transmittance rate (LTR), and the mid-range LAI of sub-okra leaf also guaranteed the accumulation of cotton biomass.  Although the chlorophyll content (SPAD) of sub-okra leaf was lower than those of the other two leaf shapes, the net photosynthetic rate (P_n) of sub-okra leaf was higher than those of okra leaf and normal leaf at most stages.  Thus, the improvements in canopy structure, as well as photosynthetic and physiological characteristics, contributed to optimizing the light environment, thereby increasing the total biomass and yield in the lines with a sub-okra leaf shape.  Our results suggest that the sub-okra leaf may have practical application in cultivating varieties, and could enhance sustainable and profitable cotton production.

Deep-sowing is an important method for avoiding drought stress in crop species, including maize.  Identifying candidate genes is the groundwork for investigating the molecular mechanism underlying maize deep-sowing tolerance.  This study evaluated four traits (mesocotyl length at 10 and 20 cm planting depths and seedling emergence rate on days 6 and 12) related to deep-sowing tolerance using a large maize population containing 386 inbred lines genotyped with 0.5 million high-quality single nucleotide polymorphisms (SNPs).  The genome-wide association study detected that 273 SNPs were in linkage disequilibrium (LD) with the genetic basis of maize deep-sowing tolerance.  The RNA-sequencing analysis identified 1 944 and 2 098 differentially expressed genes (DEGs) in two comparisons, which shared 281 DEGs.  By comparing the genomic locations of the 273 SNPs with those of the 281 DEGs, we identified seven candidate genes, of which GRMZM2G119769 encoded a sucrose non-fermenting 1 kinase interactor-like protein.  GRMZM2G119769 was selected as the candidate gene because its homologs in other plants were related to organ length, auxin, or light response.  Candidate gene association mapping revealed that natural variations in GRMZM2G119769 were related to phenotypic variations in maize mesocotyl length.  Gene expression of GRMZM2G119769 was higher in deep-sowing tolerant inbred lines.  These results suggest that GRMZM2G119769 is the most likely candidate gene.  This study provides information on the deep-sowing tolerance of maize germplasms and identifies candidate genes, which would be useful for further research on maize deep-sowing tolerance.

The peroxisomal matrix oxidase, catalase and peroxidase are imported peroxisomes through the shuttling receptors, which regulates the cellular oxidative homeostasis and function.  Here, we report that PTS1 shuttling receptor FvPex5 is involved in the localization of PTS1, utilization of carbon sources and lipids, elimination ROS, cell wall stress, conidiation, fumonisin B₁ (FB₁) production, and virulence in maize pathogen Fusarium verticillioides.  Significantly, differential expression of PTS1-, PTS2-, PEX- and FB₁ toxin-related genes in wild type and ΔFvpex5 mutant were examined by RNA-Seq analyses and confirmed by RT-PCR assay.  In addition, different expression of PTS1 and PTS2 genes of the ΔFvpex5 mutant were enriched in diverse biochemical pathways, such as carbon metabolism, nitrogen metabolism, lipid metabolism and the oxidation balance by combining GO and KEGG annotations.  Overall, we showed that FvPex5 is involved in the regulation of genes associated with PTS, thereby affecting the oxidation balance, FB₁ and virulence in F. verticillioides.  The results help to clarify the functional divergence of Pex5 orthologs, and may provide a possible target for controlling F. verticillioides infections and FB₁ biosynthesis.

Litchi chinensis Sonn is widely cultivated in subtropical regions and has an important economic value.  A high-density genetic map is a valuable tool for mapping quantitative trait loci (QTL) and marker-assisted breeding programs.   In this study, a single nucleotide polymorphism (SNP)-based high-density linkage map was constructed by a genotyping-by-sequencing (GBS) protocol using an F1 population of 178 progenies between two commercial litchi cultivars, ‘Ziniangxi’ (dwarf) and ‘Feizixiao’ (vigorous).  The genetic map consisted of 3 027 SNP markers with a total length of 1 711.97 cM in 15 linkage groups (LGs) and an average marker distance of 0.57 cM.  Based on this high-density linkage map and three years of phenotyping, a total of 37 QTLs were detected for eight dwarf-related traits, including length of new branch (LNB), diameter of new branch (DNB), length of common petiole (LCP), diameter of common petiole (DCP), length of internode (LI), length of single leaf (LSL), width of single leaf (WSL), and plant height (PH).  These QTLs could explain 8.0 to 14.7% (mean=9.7%) of the phenotypic variation.  Among them, several QTL clusters were observed, particularly on LG04 and LG11, which might show enrichment for genes regulating the dwarf-related traits in litchi.  There were 126 candidate genes identified within the QTL regions, 55 of which are differentially expressed genes by RNA-seq analysis between ‘Ziniangxi’ and ‘Feizixiao’.  These DEGs were found to participate in the regulation of cell development, material transportation, signal transduction, and plant morphogenesis, so they might play important roles in regulating plant dwarf-related traits.  The high-density genetic map and QTLs identification related to dwarf traits can provide a valuable genetic resource and a basis for marker-assisted selection and genomic studies of litchi.

Bleeding canker, a devastating disease of pear trees (Pyrus pyrifolia L.), was first reported in the 1970s in Jiangsu, China and more recently in other provinces in China.  Trees infected with bleeding canker pathogen, Dickeya fangzhongdai, develop cankers on the trunks and branches, and a rust-colored mixture of bacterial ooze and tree sap could be seen all over the trunks and branches.  In this study, we provided detail descriptions of the symptoms and epidemiology of bleeding canker disease.  Based on pathogenic and phenotypic characterizations, we identified the causal agent of bleeding canker of pear as D. fangzhongdai.  Dickeya fangzhongdai strains isolated from pear were also pathogenic on Solanum tuberosum, Brassica pekinensis, Lycopersicon esculentum, and Phalaenopsis aphrodite based on artificial inoculation, and the pathogen were more virulent on potato than that of D. solani strain.  This study provides new information about this disease and bleeding canker disease of pear.

Resistance gene analog (RGA) screening of mapped disease-resistant genes not only helps to clone these genes but also helps to develop efficient molecular markers for resistance breeding. The present study focused on the PmU region located on chromosome 7A^uL of Triticum urartu, and recently, a nucleotide binding site (NBS)-encoding gene, Pm60, was cloned from the same chromosome arm. In this research, NBS, protein kinase (PK), and ATP-binding cassette (ABC), the three disease resistance-related gene families, were analyzed within PmU region by using informatics tools, and an expression experiment was conducted to verify their functions in vivo. Comparative genomic analysis revealed that 126 RGAs were included on chromosome 7A^uL, and 30 of the RGAs as well as Pm60 were found in the PmU region. Transcriptome database analysis of T. urartu revealed 14 PmU-RGAs with expression data, and three PmU-NBSs exhibited significant changes in expression after inoculation with Blumeria graminis f. sp. tritici (Bgt); TRIUR3_14879 was up-regulated, while TRIUR3_00450 and TRIUR3_06270 were down-regulated. Cluster analysis showed that these three PmU-NBSs were clustered far from the cloned wheat resistance genes. Then, qRT-PCR was performed to investigate the expression of 14 PmU-RGAs and Pm60 after inoculation with Bgt race E09; the results showed that Pm60 was specifically expressed in UR206 which carrying PmU, but not in susceptible UR203; while TRIUR3_14879 was significantly up-regulated and TRIUR3_00450 was downregulated in UR206 after inoculation. These results indicated that PmU is Pm60, and TRIUR3_14879 and TRIUR3_00450 may also be involved in the defense against Bgt.

This research aimed to improve selection of pepper seeds for separating high-quality seeds from low-quality seeds. Past research has shown that seed vigor is significantly related to the seed color and size, thus several physical features were identified as candidate predictors of high seed quality. Image recognition software was used to automate recognition of seed feature quality using 400 kernels of pepper cultivar 101. In addition, binary logistic regression and a neural network were applied to determine models with high predictive value of seed germination. Single-kernel germination tests were conducted to validate the predictive value of the identified features. The best predictors of seed vigor were determined by the highest correlation observed between the physical features and the subsequent fresh weight of seedlings that germinated from the 400 seeds. Correlation analysis showed that fresh weight was significantly positively correlated with eight physical features: three color features (R, a*, brightness), width, length, projected area, and single-kernel density, and weight. In contrast, fresh weight significantly negatively correlated with the feature of hue. In analyses of two of the highest correlating single features, germination percentage increased from 59.3 to 71.8% when a*≥3, and selection rate peaked at 57.8%. Germination percentage increased from 59.3 to 79.4%, and the selection rate reached 76.8%, when single-kernel weight ≥0.0064 g. The most effective model was based on a multilayer perceptron (MLP) neural network, consisting of 15 physical traits as variables, and a stability calculated as 99.4%. Germination percentage in a calibration set of seeds was 79.1% and the selection rate was 90.0%. These results indicated that the model was effective in predicting seed germination based on physical features and could be used as a guide for quality control in seed selection. Automated systems based on machine vision and model classifiers can contribute to reducing the costs and labor required in the selection of pepper seeds.

In order to clarify the main pathogens of tomato Fusarium wilt in Shanxi Province, China, morphological identification, elongation factor 1 alpha (EF-1α) sequence analysis, specific primer amplification and pathogenicity tests were applied to study the isolates which were recovered from diseased plants collected from 17 different districts of Shanxi Province.  The results were as follows: 1) Through morphological and molecular identification, the following 7 species of Fusarium were identified: F. oxysporum, F. solani, F. verticillioides, F. subglutinans, F. chlamydosporum, F. sporotrichioides, and F. semitectum; 2) 56 isolates of F. oxysporum were identified using specific primer amplification, among which, 29, 5 and 6 isolates were respectively identified as F. oxysporum f. sp. lycopersici physiological race 1, race 2, and race 3; 3) pathogenicity test indicated the significant pathogenicity of F. oxysporum, F. solani, F. verticillioides, and F. subglutinans to tomato plant.  Therefore, among these 4 species confirmed as pathogenic to tomato in Shanxi, the highest isolation rate (53.3%) corresponded to F. oxysporum.  Three physiological species, race 1, race 2, and race 3 of F. oxysporum f. sp. lycopersici are detected in Shanxi, among which race 1 is the most widespread pathogen and is also considered as the predominant race.

To improve efficiency in the use of water resources in water-limited environments such as the North China Plain (NCP), where winter wheat is a major and groundwater-consuming crop, the application of water-saving irrigation strategies must be considered as a method for the sustainable development of water resources.  The initial objective of this study was to evaluate and validate the ability of the CERES-Wheat model simulation to predict the winter wheat grain yield, biomass yield and water use efficiency (WUE) responses to different irrigation management methods in the NCP.  The results from evaluation and validation analyses were compared to observed data from 8 field experiments, and the results indicated that the model can accurately predict these parameters.  The modified CERES-Wheat model was then used to simulate the development and growth of winter wheat under different irrigation treatments ranging from rainfed to four irrigation applications (full irrigation) using historical weather data from crop seasons over 33 years (1981–2014).  The data were classified into three types according to seasonal precipitation: <100 mm, 100–140 mm, and >140 mm.  Our results showed that the grain and biomass yield, harvest index (HI) and WUE responses to irrigation management were influenced by precipitation among years, whereby yield increased with higher precipitation.  Scenario simulation analysis also showed that two irrigation applications of 75 mm each at the jointing stage and anthesis stage (T3) resulted in the highest grain yield and WUE among the irrigation treatments.  Meanwhile, productivity in this treatment remained stable through different precipitation levels among years.  One irrigation at the jointing stage (T1) improved grain yield compared to the rainfed treatment and resulted in yield values near those of T3, especially when precipitation was higher.  These results indicate that T3 is the most suitable irrigation strategy under variable precipitation regimes for stable yield of winter wheat with maximum water savings in the NCP.  The application of one irrigation at the jointing stage may also serve as an alternative irrigation strategy for further reducing irrigation for sustainable water resources management in this area.

This experiment was conducted to evaluate the effects of Bupleurum extract (BE) on blood metabolites, antioxidant status, and immune function in dairy cows under heat stress.  Forty lactating Holstein cows were randomly assigned to 1 of 4 treatments.  The treatments consisted of 0, 0.25, 0.5, and 1.0 g of BE kg^–1 dry matter.  Supplementation with BE decreased (P<0.05) blood urea nitrogen (BUN) contents and increased blood total protein (TP) and albumin (ALB) levels compared with control cows, but it had no effects (P>0.05) on blood glucose (GLU), nonesterified fatty acid (NEFA), total triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high density lipoprotein cholesterol (HDL-C).  Compared with control cows, cows fed BE had higher (P<0.05) superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activity.  However, supplementation with BE had no effect (P>0.05) on total antioxidant capacity (T-AOC) or malondialdehyde (MDA) levels.  The immunoglobulin (Ig) A and G contents increased (P<0.05) in cows fed 0.25 or 0.5 g of BE kg^–1.  Interleukin (IL)-2 and IL-4 levels were higher (P<0.05) in cows fed 0.5 and 1.0 g of BE kg^–1, and IL-6 was significantly elevated (P<0.05) in cows fed 0.5 g of BE kg^–1.  There were no treatment effects (P>0.05) on the CD4⁺ and CD8⁺ T lymphocyte ratios, CD4⁺/CD8⁺ ratio, or tumor necrosis factor-α (TNF-α) level among the groups.  These findings suggest that BE supplementation may improve protein metabolism, in addition to enhancing antioxidant activity and immune function in heat-stressed dairy cows.  

Blast resistance and grain quality are major problems in hybrid rice production in China.  In this study, two resistance (R) genes, Pi46 and Pita, along with the gene Wx^b, which mainly affects rice endosperm amylose content (AC), were introgressed into an elite indica restoring line, R8166, which has little blast resistance and poor grain quality through marker-assisted selection (MAS).  Eight improved lines were found to have recurrent genome recovery ratios ranging from 88.68 to 96.23%.  Two improved lines, R163 and R167, were selected for subsequent studies.  R167, which has the highest recovery ratio (96.23%), showed no significant differences in multiple agronomic traits.  In contrast, R163 with the lowest recovery ratio (88.68%) exhibited significant differences in heading date and yield per plant compared with the recurrent parent.  At two developmental stages, R163 and R167 had greatly enhanced resistance to blast over the recurrent parent.  Similar trends were also observed for agronomic traits and blast resistance in R163- and R167-derived hybrids when compared with the counterparts from R8166.  In addition, R163, R167, and their derived hybrids significantly improved the grain quality traits, including amylose content (AC), gel consistency (GC), chalky grain rate (CGR), and degree of endosperm chalkiness (DEC).  It confirmed the success of efficiently developing elite restoring lines using MAS in this study.

    The increasing demand for fresh sweet maize (Zea mays L. saccharata) in southern China has prioritized the need to find solutions to the environmental pollution caused by its continuous production and high inputs of chemical nitrogen fertilizers.  A promising method for improving crop production and environmental conditions is to intercrop sweet maize with legumes.  Here, a three-year field experiment was conducted to assess the influence of four different cropping systems (sole sweet maize (SS), sole soybean (SB), two rows sweet maize-three rows soybean (S2B3) intercropping, and two rows sweet maize-four rows soybean (S2B4) intercropping), together with two rates of N fertilizer application (300 and 360 kg N ha^–1) on grain yield, residual soil mineral N, and soil N₂O emissions in southern China.  Results showed that in most case, intercropping achieved yield advantages (total land equivalent ratio (TLER=0.87–1.25) was above one).  Moreover, intercropping resulted in 39.8% less soil mineral N than SS at the time of crop harvest, averaged over six seasons (spring and autumn in each of the three years of the field experiment).  Generally, intercropping and reduced-N application (300 kg N ha^–1) produced lower cumulative soil N₂O and yield-scaled soil N₂O emissions than SS and conventional-N application (360 kg N ha^–1), respectively.  S2B4 intercropping with reduced-N rate (300 kg N ha^–1) showed the lowest cumulative soil N₂O (mean value=0.61 kg ha^–1) and yield-scaled soil N₂O (mean value=0.04 kg t^–1) emissions.  Overall, intercropping with reduced-N rate maintained sweet maize production, while also reducing environmental impacts.  The system of S2B4 intercropping with reduced-N rate may be the most sustainable and environmentally friendly cropping system.   

Potato (Solanum tuberosum L.) is an important staple food and economic crop in many countries.  China has led world potato production in recent years.  To understand the genetic diversity of potato germplasms and to enrich the current gene pool for potato improvement, we made a global collection consisted of 288 potato germplasms from eight countries and the International Potato Center (CIP).  Using SSR and AFLP techniques, we evaluated the genetic diversity and population structure of these 288 potato accessions.  A total of 190 alleles on 20 SSR loci were detected and all of the SSR alleles were polymorphic among these potato germplasms with an average of 9.5 alleles per SSR locus ranging from 2 to 23.  The effective number of alleles per locus (Ne*), Nei’s genetic diversity (H*), and Shannon’s information index (I*) was from (0.1709±0.3698) to (1.6166±0.3414), (0.076±0.1388) to (0.3812±0.1886), and (0.1324±0.1970) to (0.5347±0.1440), respectively, and the mean polymorphic information content (PIC) value was 0.7312.  A total of 988 AFLP alleles were detected by 10 AFLP primer combinations with 983 polymorphic alleles, and 99.49% alleles was polymorphic with an average of 98.3 polymorphic alleles per primer combination ranging from 91 to 116.  The values of Ne*, H* and I* were from (1.5162±0.311) to (1.6423±0.3278), (0.3114±0.145) to (0.3675±0.1121), and (0.4761±0.1792) to (0.547±0.1322), respectively, and the average PIC value was 0.9871.  Bayesian analysis discriminated the accessions into seven subgroup and an admix group.  The majority of accessions from CIP and China were assigned into SG1, SG5, SG6, SG7 and admix group.  Accessions in SG3 were mainly from CIP and two small groups SG2 and SG4 were mainly from northeastern China.  In general, the results obtained from Bayesian statistical analysis, cluster analysis and principal coordinate analysis consistently revealed the lack of geographical differentiation among country-wide collections, indicating germplasm introduction was common for the countries out of potato origin center.  The polymorphic markers and the differentiate genetic lineages found in this study provide useful information for potato improvement and conservation programs.  

Recent studies have shown that the R2R3-MYB transcription factor MdMYB73 is involved in salt stress response in apple. However, no research was done whether MdMYB73 mediated cold tolerance in apple or not. In this study, we found that the expression of MdMYB73 was obviously induced by cold stress. Functional analysis showed that MdMYB73 significantly increased cold tolerance in transgenic apple calli and Arabidopsis. Quantitative real-time PCR (qRT-PCR) assay indicated that the expression levels of cold-responsive genes including MdCBF2, MdCBF3, MdCBF4, and MdCBF5 were obviously enhanced in MdMYB73 transgenic calli, suggesting that MdMYB73 increased cold tolerance via C-repeat binding factor (CBF) cold response pathway. Finally, we found that soluble sugar, which provides an osmoticum for cells, was increased in MdMYB73 transgenic calli compared to that in the wild type control. These findings provide a new insights into how MdMYB73 is involved in cold stress response.

Seed storability (SS) is an important trait for agronomic production and germplasm preservation in rice (Oryza sativa L.).  Quantitative trait locus (QTL) for seed storability in three storage periods was identified using two sets of recombinant inbred lines (RILs) derived from the crosses with a common female parent Shennong 265 (SN265).  Ten QTLs for seed storability were detected on chromosomes 1, 2, 3, 4, 6, 8, and 12 in SL-RILs (SN265/Lijiangxingtuanheigui (LTH)), and a total of 12 QTLs were identified on chromosomes 2, 3, 4, 6, 9, and 10 in SH-RILs (SN265/Luhui 99 (LH99)) in different storage periods.  Among these QTLs, five major QTLs were identified in more than one storage period.  The qSS3-1, qSS3-2, qSS12-1, and qSS12-2 were detected in SL-RILs.  Similarly, qSS2-2, qSS2-3, qSS6-2, qSS6-3, qSS6-4, qSS9-1, and qSS9-2 were detected in SH-RILs.  In addition, the maximum phenotypic variation was derived from the qSS6-1 and qSS9-2, explaining 53.58 and 29.09%, respectively, while qSS6-1 was a new stable QTL for seed storability.  These results provide an opportunity for pyramiding and map-based cloning major QTLs for seed storability in rice.

japonica rice is mainly distributed in Northeast China and accounts for 44.6% of the total cultivated area of japonica rice in China.  The comprehensive using of inter-subspecies heterosis is the main breeding mode of super japonica rice varieties in this region.  Improving rice quality at relative high yielding level is the current research focus.  Performing crosses between indica and japonica lines allows for the recombination of regulatory genes and genetic backgrounds, leading to complicated genetic rice quality characteristics, which can be used to explore patterns of quality improvement.  In the present study, we utilize recombinant inbred lines (RILs) derived from indica-japonica hybridization to analyze the effect factors of rice quality derived from genetic factors, which contain both regulatory genes concerning rice quality and genetic backgrounds’ random introduction frequency coming from indica (Di value), and the improvement strategy was further discussed.  The regulatory genes involved in amylase content (Wx) and nitrogen utilization efficiency (NRT1.1B) were the major factors affecting the amylose content (AC) and protein content (PC) in RILs, respectively.  Both the Di value and the major grain width gene (GS5) had regulatory effects on milled rice width (MRW) in RILs, and their interaction explained the major variance of MRW in the RILs.  With the mediation of MRW and chalkiness degree (C), Di value had a further impact on head rice rate (HR), which was relatively poor when the Di value was over 40%.  In Northeast China, the Di value should be lowered by backcrossing or multiple crosses during the breeding of indica-japonica hybridization to maintain the whole better HR and further to emphasize the use of favorable genes in individual selection.

This experiment was conducted to study the effect of molasses on the fermentation characteristics of mixed silage ensiled rice straw and vegetable by-products with alfalfa.  Mixture (202 g kg^–1 dry matter (DM)) consisting of rice straw, broccoli residue and alfalfa at the ratio of 5:4:1 was ensiled with three experimental treatments: (1) no additives (control); (2) molasses at 2.5% (M1); (3) molasses at 5% (M2) on a fresh matter basis of mixture, respectively.  All treatments were packed into laboratory-scale silos, and three silos per treatment were sampled on days 1, 3, 5, 14 and 30.  The result showed that the pH value of all mixed silages decreased gradually with the time of ensiling except for the control silage, in which a significant increase (P<0.05) on day 30 occurred.  The lactic acid content increased gradually with the time of ensiling and reached the highest value on day 14, and a marked decrease (P<0.05) was found in the control silage on day 30.  The changes of acetic acid content showed similar pattern with lactic acid content.  A trace amount of propionic and butyric acid contents were found in the three mixed silages during the fermentation period.  Comparing to the control, M1 and M2 treatments improved the fermentation quality of mixed silages as indicated by higher (P<0.05) lactic acid contents and lower (P<0.05) pH and ammonia-N contents.  The Flieg points also showed that M1 and M2 silages were well preserved, whereas the control silage had a bad quality.  Overall, the findings of this study suggested that adding molasses could improve fermentation quality of mixed silage, and M1 was more suitable for practical application.

To better interpret summer maize stomatal conductance (g_s) variation under conditions of changing water status at different growth stages, three water stress indicators, soil water content (SWC), leaf-air temperature difference (?T) and leaf level water stress index (CWSI_L) were employed in Jarvis model, which were J_S, J_T and J_C models respectively.  Measurements of g_s were conducted in a summer maize field experiment during the year 2012–2013.  In the insufficient irrigation experiment, three levels of irrigation amount were applied at four different growth stages of summer maize.  We constructed three scenarios to evaluate the performance of the three water stress indicators for estimating maize g_s in a modified Jarvis model.  Results showed that J_T and J_C models had better simulation accuracy than the J_S model, especially at the late growth stage (Scenario 1) or considering the plant recovery compensation effects (Scenario 2).  Scenario 3 indicated that the more environmental factors were adopted, the better prediction performance would be for J_S model.  While for J_T model, two environmental factors (photosynthesis active radiation (PAR), and vapor pressure deficit (VPD)) seemed good enough to obtain a reliable simulation.  When there were insufficient environmental data, CWSI_L would be the best option.  This study can be useful to understand the response of plant stomatal to changing water conditions and will further facilitate the application of the Jarvis model in various environments.