RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      검색결과 좁혀 보기

      선택해제

      오늘 본 자료

      • 오늘 본 자료가 없습니다.
      더보기
      • A degree day model of sheep grazing influence on alfalfa weevil, Hypera postica

        Goosey, Hayes Blake Montana State University 2009 해외공개박사

        RANK : 247343

        Alfalfa, Medicago sativa (L.), is produced on approximately 720,000 ha in Montana and is the foremost forage crop in many high, semiarid, intermountain states. Two biological stressors (insects and weeds) combined with poor field management are primarily responsible for reduced alfalfa production. In the U.S. alone, arthropods cause an estimated $260 million loss to alfalfa with the alfalfa weevil (AW), Hypera postica Gyllenhal, being the most damaging phytophagous pest in the United States. Using degree days as predictors for initiation and cessation of arthropod IPM programs is a common practice and on-line degree day calculators using regional temperature data are providing equal accuracy as on-site estimates. Grazing is emerging as a legitimate IPM tactic however there is no published literature using degree days to implement an IPM based grazing systems. A degree day predictive model is needed, as a producer decision and support tool, to improve the effectiveness of strategic sheep grazing to manage alfalfa weevil. Grazing treatments exclosures were established in a randomized complete block design at weekly intervals giving each treatment a unique degree day and stocking rate. Degree days calculated from both on-site and near-site data produced the same model accuracy. Therefore, the near-site model was selected to encourage use by producers. Treatments meeting the selection criteria (G3, G4, G5) were 'modeled' together and a simple linear regression (P < 0.01) was calculated predicting AW larval populations based on stocking rate and degree day. Harvest sample treatment DM did not differ (P > 0.16). However, NDF, CP, and Yield differed (P < 0.01) between treatments. Due to an interaction (P < 0.01), ADF and TDN were separated by year and did not differ P = 0.93 during 2008, but did (P < 0.01) during 2009. Based on yield and nutritive differences between treatments, a simple regression (P < 0.01) of plant RGR was calculated to predict when yield and nutritive characteristics of the modeled and less extensively grazed 'alternative' (NG, G1, G2) treatments would equal. The equation predicted that producers would need to wait an average of four days for treatment harvest characteristics to equal.

      연관 검색어 추천

      이 검색어로 많이 본 자료

      활용도 높은 자료

      해외이동버튼